The 100 most-cited articles in Energies, 2024

The global energy crisis, which began in 2021 due to the extraordinary economic recovery after the pandemic and intensified after Russia’s invasion of Ukraine in February 2022, has changed the conditions of energy management, paying more attention to energy efficiency. Natural gas prices have reached record levels and, consequently, so have electricity prices in some markets. Oil prices have reached their highest level since 2008. Higher energy prices have contributed to sharply increased inflation. Households are again becoming interested in buying coal as a source of heat. High energy and gas prices have pushed many families into poverty and forced some factories to cut production or even close. They have also slowed economic growth to the point where some countries are heading for a serious recession. Paradoxically, the negative effects of the energy crisis may accelerate the introduction of cleaner, sustainable, renewable energy such as wind and solar energy. The energy crisis is comparable to the oil crisis of the 1970s, when it contributed to significant advances in energy…

This review examines the central role of hydrogen, particularly green hydrogen from renewable sources, in the global search for energy solutions that are sustainable and safe by design. Using the hydrogen square, safety measures across the hydrogen value chain—production, storage, transport, and utilisation—are discussed, thereby highlighting the need for a balanced approach to ensure a sustainable and efficient hydrogen economy. The review also underlines the challenges in safety assessments, points to past incidents, and argues for a comprehensive risk assessment that uses empirical modelling, simulation-based computational fluid dynamics (CFDs) for hydrogen dispersion, and quantitative risk assessments. It also highlights the activities carried out by our research group SaRAH (Safety, Risk Analysis, and Hydrogen) relative to a more rigorous risk assessment of hydrogen-related systems through the use of a combined approach of CFD simulations and the appropriate risk assessment tools. Our research activities are currently focused on underground hydrogen storage and hydrogen…

As the global demand for clean and sustainable energy sources intensifies, hydrogen emerges as a promising alternative fuel. The widespread adoption of hydrogen, however, is impeded by the lack of efficient systems for storage and transportation. This review aims to summarize the recent advancements and prevailing challenges within the realm of hydrogen storage and transportation, thereby providing guidance and impetus for future research and practical applications in this domain. Through a systematic selection and analysis of the latest literature, this study highlights the strengths, limitations, and technological progress of various hydrogen storage methods, including compressed gaseous hydrogen, cryogenic liquid hydrogen, organic liquids hydrogen, solid materials hydrogen storage, as well as the feasibility, efficiency, and infrastructure requirements of different transportation modes such as pipelines, road and seaborne transportation. The findings reveal that challenges such as low storage density, high costs, and inadequate infrastructure persist despite progress in…

The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient energy infrastructure. Their integration is vital for achieving energy sustainability among all clean energy sources, including wind, solar, and hydropower. This review paper provides a thoughtful analysis of the current status of the smart grid, focusing on integrating various RES, such as wind and solar, into the smart grid. This review highlights the significant role of RES in reducing greenhouse gas emissions and reducing traditional fossil fuel reliability, thereby contributing to environmental sustainability and empowering energy security. Moreover, key advancements in smart grid technologies, such as Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) systems, are explored to clarify the related topics to the smart grid. The usage of various technologies enhances grid reliability, efficiency, and resilience are introduced. This paper also investigates the…

Pyrolysis is an environmentally friendly and efficient method for converting biomass into a wide range of products, including fuels, chemicals, fertilizers, catalysts, and sorption materials. This review confirms that scientific research on biomass pyrolysis has remained strong over the past 10 years. The authors examine the operating conditions of different types of pyrolysis, including slow, intermediate, fast, and flash, highlighting the distinct heating rates for each. Furthermore, biomass pyrolysis reactors are categorized into four groups, pneumatic bed reactors, gravity reactors, stationary bed reactors, and mechanical reactors, with a discussion on each type. The review then focuses on recent advancements in pyrolysis technologies that have improved efficiency, yield, and product quality, which, in turn, support sustainable energy production and effective waste management. The composition and yields of products from the different types of pyrolysis have been also reviewed. Finally, a techno-economic analysis has been conducted for both the pyrolysis of biomass alone and the…

Distribution System Operators (DSOs) and Aggregators benefit from novel energy forecasting (EF) approaches. Improved forecasting accuracy may make it easier to deal with energy imbalances between generation and consumption. It also helps operations such as Demand Response Management (DRM) in Smart Grid (SG) architectures. For utilities, companies, and consumers to manage energy resources effectively and make educated decisions about energy generation and consumption, EF is essential. For many applications, such as Energy Load Forecasting (ELF), Energy Generation Forecasting (EGF), and grid stability, accurate EF is crucial. The state of the art in EF is examined in this literature review, emphasising cutting-edge forecasting techniques and technologies and their significance for the energy industry. It gives an overview of statistical, Machine Learning (ML)-based, and Deep Learning (DL)-based methods and their ensembles that form the basis of EF. Various time-series forecasting techniques are explored, including sequence-to-sequence, recursive, and direct forecasting. Furthermore,…

This review paper thoroughly explores the impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. With the rapid advancement of artificial intelligence techniques such as machine learning, optimization, and cognitive computing, new opportunities are emerging to enhance the efficiency and reliability of electrical grids. From demand and generation prediction to energy flow optimization and load management, artificial intelligence is playing a pivotal role in the transformation of energy infrastructure. This paper delves deeply into the latest advancements in specific artificial intelligence applications within the context of distributed energy systems, including the coordination of distributed energy resources, the integration of intermittent renewable energies, and the enhancement of demand response. Furthermore, it discusses the technical, economic, and regulatory challenges associated with the implementation of artificial intelligence-based solutions, as well as the ethical considerations related to automation and autonomous…

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal…

This review analyzes the complex relationship between climate change and energy security and their joint impact on global development. It emphasizes the need for sustainable energy solutions to tackle increasing global warming effects and energy demands. A thorough literature analysis highlights the link between energy policies, climate goals, and sustainable development aspirations. Moreover, it examines the effectiveness of energy policies in various national contexts in promoting environmental sustainability and emphasizing regional dynamics, socio-economic factors, and diverse energy planning approaches. The review explains the multifaceted relationship between climate change, energy security, and environmental protection. Key recommendations related to renewable energy transitions are provided as crucial means to address global energy demand and resource constraints while reducing dependence on fossil fuels. The analysis underscores renewable energy’s key role in aligned energy strategies that balance security and sustainability for a low-carbon future. It emphasizes the…

The emergence of Digital Twin (DT) technology presents unique opportunities for society by facilitating real-time data transfer from the physical environment to its digital counterpart. Although progress has been made in various industry sectors such as aerospace, the Architecture, Engineering, Construction, and Operation (AECO) sector still requires further advancements, like the adoption of these technologies over traditional approaches. The use of these technologies should become standard practice rather than an advanced operation. This paper aims to address the existing gap by presenting a comprehensive framework that integrates technologies and concepts derived from purpose-driven case studies and research studies across different industries. The framework is designed to provide best practices for the AECO sector. Moreover, it aims to underscores the potential of DT for optimization through overseeing and digital management of the built environment across the entire life cycle of facilities, encompassing design, construction, operation, and maintenance. It is based on an…

As the worldwide demand for meat per person is continuously increasing, there is a corresponding rise in the number of livestock animals, leading to an increase in livestock manure. Selecting appropriate treatment technologies for livestock manures is still a complex task and considerable debates over this issue persist. To develop a more comprehensive understanding of the manure treatment framework, this review was undertaken to assess the most utilized manure management technologies and underscore their respective challenges. Anaerobic digestion has become a commercial reality for treating livestock manures. However, the mono-digestion of single substrates comes with certain drawbacks associated with manure characteristics. Anaerobic co-digestion, involving the utilization of multiple feedstocks, holds the potential to overcome these limitations. Extensive research and development have underscored numerous intrinsic benefits of co-digestion. These include improved digestibility resulting from the synergistic effects of co-substrates and enhanced process stability. This review…

Despite the tightening of energy performance standards for buildings in various countries and the increased use of efficient and renewable energy technologies, it is clear that the sector needs to change more rapidly to meet the Net Zero Emissions (NZE) scenario by 2050. One of the problems that have been analyzed intensively in recent years is that buildings in operation use much more energy than they were designed to. This problem, known as the energy performance gap, is found in many countries and buildings and is often attributed to the poor management of building energy systems. The application of Artificial Intelligence (AI) to Building Energy Management Systems (BEMS) has untapped potential to address this problem and lead to more sustainable buildings. This paper reviews different AI-based models that have been proposed for different applications and different buildings with the intention to reduce energy consumption. It compares the performance of the different AI-based models evaluated in the reviewed papers by presenting the accuracy and error rates of model performance…

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available…

With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) entail significant energy consumption, potentially undermining carbon neutrality efforts. Key findings include an analysis of 237 scientific publications from 2010 to 2024, which highlights significant advancements and obstacles to AI adoption across sectors, such as construction, transportation, industry, energy and households. The review showed that interest in the use of AI and ML in energy efficiency has grown significantly: over 60% of the documents have been published in the last two years, with the topics of sustainable construction and climate change forecasting…

E-fuels represent a crucial technology for transitioning to fossil-free energy systems, driven by the need to eliminate dependence on fossil fuels, which are major environmental pollutants. This study investigates the production of carbon-neutral synthetic fuels, focusing on e-hydrogen (e-H2) generated from water electrolysis using renewable electricity and carbon dioxide (CO2) captured from industrial sites or the air (CCUS, DAC). E-H2 can be converted into various e-fuels (e-methane, e-methanol, e-DME/OME, e-diesel/kerosene/gasoline) or combined with nitrogen to produce e-ammonia. These e-fuels serve as efficient energy carriers that can be stored, transported, and utilized across different energy sectors, including transportation and industry. The first objective is to establish a clear framework encompassing the required feedstocks and production technologies, such as water electrolysis, carbon capture, and nitrogen production techniques, followed by an analysis of e-fuel synthesis technologies. The second objective is to evaluate these technologies’ technological maturity and…

This perspective article delves into the critical role of hydrogen as a sustainable energy carrier in the context of the ongoing global energy transition. Hydrogen, with its potential to decarbonize various sectors, has emerged as a key player in achieving decarbonization and energy sustainability goals. This article provides an overview of the current state of hydrogen technology, its production methods, and its applications across diverse industries. By exploring the challenges and opportunities associated with hydrogen integration, we aim to shed light on the pathways toward achieving a sustainable hydrogen economy. Additionally, the article underscores the need for collaborative efforts among policymakers, industries, and researchers to overcome existing hurdles and unlock the full potential of hydrogen in the transition to a low-carbon future. Through a balanced analysis of the present landscape and future prospects, this perspective article aims to contribute valuable insights to the discourse surrounding hydrogen’s role in the global energy transition.

Amid rising global demand for sustainable energy, wind energy emerges as a crucial renewable resource, with the aerodynamic optimization of wind turbine blades playing a key role in enhancing energy efficiency. This systematic review scrutinizes recent advancements in blade aerodynamics, focusing on the integration of cutting-edge aerodynamic profiles, variable pitch and twist technologies, and innovative materials. It extensively explores the impact of Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI) on blade design enhancements, illustrating their significant contributions to aerodynamic efficiency improvements. By reviewing research from the last decade, this paper provides a comprehensive overview of current trends, addresses ongoing challenges, and suggests potential future developments in wind turbine blade optimization. Aimed at researchers, engineers, and policymakers, this review serves as a crucial resource, guiding further innovations and aligning with global renewable energy objectives. Ultimately, this work seeks to facilitate technological…

The primary objective of this study is to evaluate the accuracy of different forecasting models for monthly wind farm electricity production. This study compares the effectiveness of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), and Support Vector Regression (SVR). This study utilizes data from two wind farms located in Poland—‘Gizałki’ and ‘Łęki Dukielskie’—to exclude the possibility of biased results due to specific characteristics of a single farm and to allow for a more comprehensive comparison of the effectiveness of both time series analysis methods. Model parameterization was optimized through a grid search based on the Mean Absolute Percentage Error (MAPE). The performance of the best models was evaluated using Mean Bias Error (MBE), MAPE, Mean Absolute Error (MAE), and R2Score. For the Gizałki farm, the ARIMA model outperformed SARIMA and SVR, while for the Łęki Dukielskie farm, SARIMA proved to be the most accurate, highlighting the importance of optimizing seasonal parameters. The SVR method demonstrated the lowest…

The potential energy of compressed air represents a multi-application source of power. Historically employed to drive certain manufacturing or transportation systems, it became a source of vehicle propulsion in the late 19th century. During the second half of the 20th century, significant efforts were directed towards harnessing pressurized air for the storage of electrical energy. Today’s systems, which are based on storing the air at a high pressure, are usually recognized as compressed air energy storage (CAES) installations. This paper aims to provide an overview of different technologies that take advantage of the energy accumulated in the compressed air. Particular attention is paid to the CAES installations that are working as electrical energy storage systems (EESs). These systems, developed originally as large capacity (>100 MWe) and fuel-based installations, may soon become fully scalable, highly efficient, and fuel-free electrical energy storage systems. To present this opportunity, a thorough review encompassing previous and up-to-date advancements in their development…

Proton exchange membrane fuel cells (PEMFCs) have the potential to tackle major challenges associated with fossil fuel-sourced energy consumption. Nafion, a perfluorosulfonic acid (PFSA) membrane that has high proton conductivity and good chemical stability, is a standard proton exchange membrane (PEM) used in PEMFCs. However, PEM degradation is one of the significant issues in the long-term operation of PEMFCs. Membrane degradation can lead to a decrease in the performance and the lifespan of PEMFCs. The membrane can degrade through chemical, mechanical, and thermal pathways. This paper reviews the different causes of all three routes of PFSA degradation, underlying mechanisms, their effects, and mitigation strategies. A better understanding of different degradation pathways and mechanisms is valuable in producing robust fuel cell membranes. Hence, the progress in membrane fabrication for PEMFC application is also explored and summarized.

Economic Dispatch Problems (EDP) refer to the process of determining the power output of generation units such that the electricity demand of the system is satisfied at a minimum cost while technical and operational constraints of the system are satisfied. This procedure is vital in the efficient energy management of electricity networks since it can ensure the reliable and efficient operation of power systems. As power systems transition from conventional to modern ones, new components and constraints are introduced to power systems, making the EDP increasingly complex. This highlights the importance of developing advanced optimization techniques that can efficiently handle these new complexities to ensure optimal operation and cost-effectiveness of power systems. This review paper provides a comprehensive exploration of the EDP, encompassing its mathematical formulation and the examination of commonly used problem formulation techniques, including single and multi-objective optimization methods. It also explores the progression of paradigms in economic dispatch, tracing the…

Proton exchange membrane fuel cells have attracted widespread attention due to their cleanliness and high energy density, but the performance degradation during operation greatly limits their commercialization. Therefore, the reliable degradation prediction of fuel cell performance is of great significance. The recovery phenomenon of the reversible voltage loss that occurs during the operation of fuel cells has posed great difficulties for model training and prediction. Moreover, the models may easily and erroneously learn the combined trends in the recovery of reversible voltage loss and performance degradation. To address this issue, this paper employs the Transformer model to predict the performance degradation of fuel cells. By utilizing the unique self-attention structure and masking mechanism of the Transformer model, the signal for the recovery of the reversible voltage loss is adopted as the input for the model to avoid interference from information before voltage recovery on subsequent predictions. Experimental results show that the model has the highest prediction accuracy…

Accurate and reliable mathematical modeling is essential for the optimal control and performance analysis of polymer electrolyte membrane fuel cell (PEMFC) systems, which are mainly implemented based on accurate parameter estimation. In this paper, a multi-strategy tuna swarm optimization (MS-TSO) is proposed to estimate the parameters of PEMFC voltage models and compare them with other optimizers such as differential evolution, the whale optimization approach, the salp swarm algorithm, particle swarm optimization, Harris hawk optimization and the slime mould algorithm. In the optimizing routine, the unidentified factors of the PEMFCs are used as the decision variables, which are optimized to minimize the sum of square errors between the estimated and measured data. The optimizers are examined based on three PEMFC datasets including BCS500W, NedStackPS6 and harizon500W as well as a set of experimental data which are measured using the Greenlight G20 platform with a 25 cm2 single cell at 353 K. It is confirmed that MS-TSO gives better performance in terms of convergence speed and…

Accurate forecasting of photovoltaic (PV) power is essential for grid scheduling and energy management. In recent years, deep learning technology has made significant progress in time-series forecasting, offering new solutions for PV power forecasting. This study provides a systematic review of deep learning models for PV power forecasting, concentrating on comparisons of the features, advantages, and limitations of different model architectures. First, we analyze the commonly used datasets for PV power forecasting. Additionally, we provide an overview of mainstream deep learning model architectures, including multilayer perceptron (MLP), recurrent neural networks (RNN), convolutional neural networks (CNN), and graph neural networks (GNN), and explain their fundamental principles and technical features. Moreover, we systematically organize the research progress of deep learning models based on different architectures for PV power forecasting. This study indicates that different deep learning model architectures have their own advantages in PV power forecasting. MLP models have…

Accelerating the transition to a cleaner global energy system is essential for tackling the climate crisis, and green hydrogen energy systems hold significant promise for integrating renewable energy sources. This paper offers a thorough evaluation of green hydrogen’s potential as a groundbreaking alternative to achieve near-zero greenhouse gas (GHG) emissions within a renewable energy framework. The paper explores current technological options and assesses the industry’s present status alongside future challenges. It also includes an economic analysis to gauge the feasibility of integrating green hydrogen, providing a critical review of the current and future expectations for the levelized cost of hydrogen (LCOH). Depending on the geographic location and the technology employed, the LCOH for green hydrogen can range from as low as EUR 1.12/kg to as high as EUR 16.06/kg. Nonetheless, the findings suggest that green hydrogen could play a crucial role in reducing GHG emissions, particularly in hard-to-decarbonize sectors. A target LCOH of approximately EUR 1/kg by 2050 seems…

Recently, worldwide attention toward hydrogen and its derivatives as alternative carbon-free or low-carbon options for the electricity sector, the transport sector, and the industry sector increased. Several projects in the field of low-emissions hydrogen production (particularly electrolysis-based green hydrogen) were either constructed or were analyzed in terms of feasibility. This study aims at summarizing some expectations of the level at which hydrogen and its derivatives can spread into the global economy, under two scenarios. The first scenario corresponds to a business-as-usual (BAU) pathway, where the world proceeds with the same existing policies and targets for emissions and low-carbon energy transition. This forms a lower bound for the level of hydrogen role. The second scenario corresponds to an emissions-conscious pathway, where governments cooperate to implement necessary changes to decarbonize the economy by 2050 with net zero (or even negative) emissions of carbon dioxide; thus, limiting the rise in the global mean surface temperature to 1.5 °C by 2100 compared to…

Wastewater Treatment Plants (WWTPs) play a crucial role in maintaining ecological balance, a cornerstone of environmental health for thriving biodiversity and undisturbed natural processes. This balance is crucial for the sustainability of ecosystems, directly influencing human health, biodiversity, and the overall quality of our natural environment. WWTPs contribute to this equilibrium by efficiently removing pollutants and harmful substances from wastewater, thus averting the degradation of water bodies that are essential for numerous ecological processes. WWTPs encompass multiple stages of wastewater and sludge treatment and are significant energy consumers globally, especially in secondary treatment, particularly the activated sludge method which is the most common method. With an upcoming directive from the European Union aiming to reduce energy consumption in WWTPs, this paper focuses on a literature review examining global practices implemented across all stages of WWTP treatment processes. It summarizes the key points of each study, focusing primarily on the outcomes of each…

This paper provides a comprehensive review of machine learning strategies and optimization formulations employed in energy management systems (EMS) tailored for plug-in hybrid electric vehicles (PHEVs). EMS stands as a pivotal component facilitating optimized power distribution, predictive and adaptive control strategies, component health monitoring, and energy harvesting, thereby enabling the maximal exploitation of resources through optimal operation. Recent advancements have introduced innovative solutions such as Model Predictive Control (MPC), machine learning-based techniques, real-time optimization algorithms, hybrid optimization approaches, and the integration of fuzzy logic with neural networks, significantly enhancing the efficiency and performance of EMS. Additionally, multi-objective optimization, stochastic and robust optimization methods, and emerging quantum computing approaches are pushing the boundaries of EMS capabilities. Remarkable advancements have been made in data-driven modeling, decision-making, and real-time adjustments, propelling machine learning and…

The escalating global demand for goods transport via shipping has heightened energy consumption, impacting worldwide health and the environment. To mitigate this, international organizations aim to achieve complete fuel desulphurization and decarbonization by 50% by 2050. Investigating eco-friendly fuels is crucial, particularly those with a reduced carbon and zero sulfur content. Methanol derived mainly from renewable sources and produced by carbon dioxide’s hydrogenation method, stands out as an effective solution for GHG reduction. Leveraging its favorable properties, global scalability, and compatibility with the existing infrastructure, especially LNGs, methanol proves to be a cost-efficient and minimally disruptive alternative. This review explores methanol’s role as a hybrid maritime fuel, emphasizing its ecological production methods, advantages, and challenges in the shipping industry’s green transition. It discusses the environmental impacts of methanol use and analyzes economic factors, positioning methanol not only as an eco-friendly option, but also as a financially…

The global shift towards sustainable energy has positioned photovoltaic (PV) systems as a critical component in the renewable energy landscape. However, maintaining the efficiency and longevity of these systems requires effective fault detection and diagnosis mechanisms. Traditional methods, relying on manual inspections and standard electrical measurements, have proven inadequate, especially for large-scale solar installations. The emergence of machine learning (ML) and deep learning (DL) has sparked significant interest in developing computational strategies to enhance the identification and classification of PV system faults. Despite these advancements, challenges remain, particularly due to the limited availability of public datasets for PV fault detection and the complexity of existing artificial-intelligence (AI)-based methods. This study distinguishes itself by proposing a novel AI-based approach that optimizes fault detection and classification in PV systems, addressing existing gaps in AI-driven fault detection, especially in terms of thermal imaging and current–voltage…

The large integration of inverter-based resources will significantly alter grid dynamics, leading to pronounced stability challenges due to fundamental disparities between inverter-based and traditional energy systems. While grid-following inverters (GFLIs) dominate current inverter configurations, their increased penetration into the grid can result in major stability issues. In contrast, grid-forming inverters (GFMIs) excel over GFLIs by offering features like standalone operation, frequency support, and adaptability in weak grid scenarios. GFMIs, unlike GFLIs, control the AC voltage and frequency at the common coupling point, impacting the inverter dynamic response to grid disturbances and overall stability. Despite the existing literature highlighting differences between GFLIs and GFMIs and their control strategies, a comprehensive review of GFMIs’ stability and the effects of their control schemes on grid stability is lacking. This paper provides an in-depth evaluation of GFMIs’ stability, considering various control schemes and their dynamics. It also explores different types…

The growing emphasis on renewable energy highlights hydrogen’s potential as a clean energy carrier. However, traditional hydrogen production methods contribute significantly to carbon emissions. This review examines the integration of carbon capture and storage (CCS) technologies with hydrogen production processes, focusing on their ability to mitigate carbon emissions. It evaluates various hydrogen production techniques, including steam methane reforming, electrolysis, and biomass gasification, and discusses how CCS can enhance environmental sustainability. Key challenges, such as economic, technical, and regulatory obstacles, are analyzed. Case studies and future trends offer insights into the feasibility of CCS–hydrogen integration, providing pathways for reducing greenhouse gases and facilitating a clean energy transition.

Graphitic carbon Nitride (g-C3N4) is one of the most utilized graphitic materials in hydrogen (H2) production via photocatalytic water splitting. Thus, a detailed critical overview, updated with the most recent works, has been performed on the synthesis methods, modification techniques, characterization, and mechanisms of g-C3N4 and g-C3N4-based composite materials, with the aim of clarifying the optimum course towards highly efficient hydrogen-producing photocatalysts based on this promising material. First, the synthesis methods for different morphologies of pure g-C3N4 (bulk, nanosheets, nanotubes and nanodots) are critically analyzed in detail for every step and parameter involved, with special mention regarding the modification methods of g-C3N4 (doping and composite formation). Next, the most common results of g-C3N4 characterization, regarding structural, morphological, optical, and electrical properties, are presented and analyzed. Then, a detailed critical survey of the mechanisms, using g-C3N4 and g-C3N4-based composites during photocatalytic activity, is performed with a…

Anomaly detection is the process of detecting unusual or unforeseen patterns or events in data. Many factors, such as malfunctioning hardware, malevolent activities, or modifications to the data’s underlying distribution, might cause anomalies. One of the key factors in anomaly detection is balancing the trade-off between sensitivity and specificity. Balancing these trade-offs requires careful tuning of the anomaly detection algorithm and consideration of the specific domain and application. Deep learning techniques’ applications, such as LSTMs (long short-term memory algorithms), which are autoencoders for detecting an anomaly, have garnered increasing attention in recent years. The main goal of this work was to develop an anomaly detection solution for an electrical machine using an LSTM-autoencoder deep learning model. The work focused on detecting anomalies in an electrical motor’s variation vibrations in three axes: axial (X), radial (Y), and tangential (Z), which are indicative of potential faults or failures. The presented model is a combination of the two architectures; LSTM…

The integration of photovoltaic (PV) systems into the global energy landscape has been boosted in recent years, driven by environmental concerns and research into renewable energy sources. The accurate prediction of temperature and solar irradiance is essential for optimizing the performance and grid integration of PV systems. Machine learning (ML) has become an effective tool for improving the accuracy of these predictions. This comprehensive review explores the pioneer techniques and methodologies employed in the field of ML-based forecasting of temperature and solar irradiance for PV systems. This article presents a comparative study between various algorithms and techniques commonly used for temperature and solar radiation forecasting. These include regression models such as decision trees, random forest, XGBoost, and support vector machines (SVM). The beginning of this article highlights the importance of accurate weather forecasts for the operation of PV systems and the challenges associated with traditional meteorological models. Next, fundamental concepts of machine learning…

This paper navigates the critical role of hydrogen in catalyzing a sustainable energy transformation. This review delves into hydrogen production methodologies, spotlighting green and blue hydrogen as pivotal for future energy systems because of their potential to significantly reduce greenhouse gas emissions. Through a comprehensive literature review and a bibliometric analysis, this study underscores the importance of technological advancements, policy support, and market incentives in promoting hydrogen as a key energy vector. It also explores the necessity of expanding renewable energy sources and international cooperation to secure a sustainable, low-carbon future. The analysis highlights the importance of scalable and cost-effective hydrogen production methods, such as solar-thermochemical and photo-electrochemical processes, and addresses the challenges posed by resource availability and geopolitical factors in establishing a hydrogen economy. This paper serves as a guide for policy and innovation toward achieving global sustainability goals, illustrating the essential role…

The field of nanotechnology has shown promise in addressing major problems and improving drilling effectiveness. An overview of the difficulties encountered during oil and gas well drilling operations and the demand for creative solutions opens the debate. This review explores how nanotechnology is transforming the oil industry and enhancing performance as a whole. The evaluation of the uses of nanotechnology for better oil recovery, real-time monitoring, innovative materials, drilling fluids, and reservoir characterization are extensively discussed in this review. The primary function of additives is to improve the fundamental characteristics of drilling fluids. The variety of fluid additives available is a reflection of the complex drilling–fluid systems that are currently being used to enable drilling in increasingly difficult subsurface conditions. Common additives used in water- and oil-based drilling fluids include lubrication, shale stability, filtration control, rheology control, viscosification, and pH regulation. Drilling fluids frequently contain filtration control…

The Green Deal, a cornerstone of the European Union’s climate goals, sets out to achieve a substantial 55% reduction in greenhouse gas emissions by 2030 compared to 1990 levels. The EU’s decarbonization strategies revolve around three pivotal avenues. First, there is a focus on enhancing energy efficiency and decreasing the energy intensity of economies. Second, concerted efforts are made to diminish the reliance on fossil fuels, particularly within industrial sectors. Lastly, there is a deliberate push to augment the share of renewable energy sources in the final energy consumption mix. These measures collectively aim to propel the decarbonization of EU economies, establishing EU member countries as global leaders in implementing these transformative processes. This manuscript seeks to evaluate the efficacy of three primary decarbonization strategies adopted by EU economies, namely the enhancement in energy efficiency, the promotion of renewable energy consumption and the reduction in fossil fuel consumption. The objective is to discern which strategies wield a decisive influence…

With the increasing demand for renewable energy worldwide, lithium-ion batteries are a major candidate for the energy shift due to their superior capabilities. However, the heat generated by these batteries during their operation can lead to serious safety issues and even fires and explosions if not managed effectively. Lithium-ion batteries also suffer from significant performance degradation at low temperatures, including reduced power output, a shorter cycle life, and reduced usable capacity. Deploying an effective battery thermal management system (BTMS) is crucial to address these obstacles and maintain stable battery operation within a safe temperature range. In this study, we review recent developments in the thermal management and heat transfer of Li-ion batteries to offer more effective, secure, and cost-effective solutions. We evaluate different technologies in BTMSs, such as air cooling, liquid cooling, phase change materials, heat pipes, external preheating, and internal preheating, discussing their advantages and disadvantages. Through comparative analyses of…

Electric vehicles (EVs) have seen significant growth due to the increasing awareness about environmental concerns and the negative impacts of internal combustion engine vehicles (ICEVs). The electric vehicle landscape is rapidly evolving, with EV policies, battery, and charging infrastructure and electric vehicle-to-everything (V2X) at its forefront. This review study used a bibliometric analysis of the Scopus database to investigate the development of EV technology. This bibliometric study specifically focuses on analyzing electric vehicle trends, policy implications, lithium-ion batteries, EV battery management systems, charging infrastructure, EV smart charging technologies, and V2X. Through this detailed bibliometric analysis discussion, we aim to provide a better understanding of holistic EV technology and inspire further research in electric vehicles. The analysis covers the period from 1990 to 2022. This bibliometric analysis underscores the interplay of electric vehicle policies, technology, and infrastructure, specifically focusing on developments in battery management and…

The construction sector is a significant contributor to global carbon emissions and a major consumer of non-renewable resources. Architectural design decisions play a critical role in a building’s carbon footprint, making it essential to incorporate environmental analyses at various design stages. Integrating artificial intelligence (AI) and building information modeling (BIM) can support designers in achieving low-carbon architectural design. The proposed solution involves the development of a Life Cycle Assessment (LCA) tool. This study presents a novel approach to optimizing the environmental impact of architectural projects. It combines machine learning (ML), large language models (LLMs), and building information modeling (BIM) technologies. The first case studies present specific examples of tools developed for this purpose. The first case study details a machine learning-assisted tool used for estimating carbon footprints during the design phase and shows numerical carbon footprint optimization results. The second case study explores the use of LLMs, specifically ChatGPT, as…

Short-term load forecasting (STLF) plays a vital role in ensuring the safe, efficient, and economical operation of power systems. Accurate load forecasting provides numerous benefits for power suppliers, such as cost reduction, increased reliability, and informed decision-making. However, STLF is a complex task due to various factors, including non-linear trends, multiple seasonality, variable variance, and significant random interruptions in electricity demand time series. To address these challenges, advanced techniques and models are required. This study focuses on the development of an efficient short-term power load forecasting model using the random forest (RF) algorithm. RF combines regression trees through bagging and random subspace techniques to improve prediction accuracy and reduce model variability. The algorithm constructs a forest of trees using bootstrap samples and selects random feature subsets at each node to enhance diversity. Hyperparameters such as the number of trees, minimum sample leaf size, and maximum features for each split are tuned to optimize…

The development of renewable energy resources significantly impacts economic growth, various aspects of which can be assessed. First, the sector contributes to job creation, as new technologies and projects require specialists in various fields, from engineering to installation. Second, investments in renewable energy drive economic growth as the private and public sectors increasingly invest in innovation and infrastructure. In addition, developing renewable energy sources can lower energy prices for consumers, increase market competition, and reduce dependence on imported resources. However, there are also challenges related to initial investment costs, technological barriers and required political support. To ensure the successful development of renewable energy sources, it is necessary to create a favorable legal and regulatory environment, as well as to promote education and training in this area. In conclusion, the development of renewable energy resources can become an important driver of economic growth but requires a balanced approach and strategic planning. This work aims…

While fossil fuels continue to be used and to increase air pollution across the world, hydrogen gas has been proposed as an alternative energy source and a carrier for the future by scientists. Water electrolysis is a renewable and sustainable chemical energy production method among other hydrogen production methods. Hydrogen production via water electrolysis is a popular and expensive method that meets the high energy requirements of most industrial electrolyzers. Scientists are investigating how to reduce the price of water electrolytes with different methods and materials. The electrolysis structure, equations and thermodynamics are first explored in this paper. Water electrolysis systems are mainly classified as high- and low-temperature electrolysis systems. Alkaline, PEM-type and solid oxide electrolyzers are well known today. These electrolyzer materials for electrode types, electrolyte solutions and membrane systems are investigated in this research. This research aims to shed light on the water electrolysis process and materials developments.

Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability…

Hydrogen embrittlement (HE) remains a pressing issue in materials science and engineering, given its significant impact on the structural integrity of metals and alloys. This exhaustive review aims to thoroughly examine HE, covering a range of aspects that collectively enhance our understanding of this intricate phenomenon. It proceeds to investigate the varied effects of hydrogen on metals, illustrating its ability to profoundly alter mechanical properties, thereby increasing vulnerability to fractures and failures. A crucial section of the review delves into how different metals and their alloys exhibit unique responses to hydrogen exposure, shedding light on their distinct behaviors. This knowledge is essential for customizing materials to specific applications and ensuring structural dependability. Additionally, the paper explores a diverse array of models and classifications of HE, offering a structured framework for comprehending its complexities. These models play a crucial role in forecasting, preventing, and mitigating HE across various domains, ranging from industrial…

This research addresses the increasing importance of understanding how Artificial Intelligence can facilitate the transition of companies to a Circular Economy model. This study focuses on energy management, examining its impact on efficiency and emissions across a multi-case analysis of 18 projects in diverse sectors. The findings indicate that Artificial Intelligence positively influences both variables, with variations across applications and sectors. Notably, Artificial Intelligence significantly enhances energy efficiency in four out of six sectors, achieving over 5% improvement in half of the projects. Regarding emissions, positive effects are observed in 15 out of 18 projects, resulting in over 5% reductions in seven cases. Artificial Intelligence plays a pivotal role in emissions reduction in the Design and Energy sectors, with some projects achieving over 20% reductions. Additionally, this study explores how improved energy efficiency positively affects strategic business variables, such as cost, quality, and delivery time. The impact on emissions contributes to reducing…

In recent years, global efforts towards a future with sustainable energy have intensified the development of renewable energy sources (RESs) such as offshore wind, solar photovoltaics (PVs), hydro, and geothermal. Concurrently, green hydrogen, produced via water electrolysis using these RESs, has been recognized as a promising solution to decarbonizing traditionally hard-to-abate sectors. Furthermore, hydrogen storage provides a long-duration energy storage approach to managing the intermittency of RESs, which ensures a reliable and stable electricity supply and supports electric grid operations with ancillary services like frequency and voltage regulation. Despite significant progress, the hydrogen economy remains nascent, with ongoing developments and persistent uncertainties in economic, technological, and regulatory aspects. This paper provides a comprehensive review of the green hydrogen value chain, encompassing production, transportation logistics, storage methodologies, and end-use applications, while identifying key research gaps. Particular emphasis is placed on the…

Lithium-Ion Batteries (LIBs) usually present several degradation processes, which include their complex Solid-Electrolyte Interphase (SEI) formation process, which can result in mechanical, thermal, and chemical failures. The SEI layer is a protective layer that forms on the anode surface. The SEI layer allows the movement of lithium ions while blocking electrons, which is necessary to prevent short circuits in the battery and ensure safe operation. However, the SEI formation mechanisms reduce battery capacity and power as they consume electrolyte species, resulting in irreversible material loss. Furthermore, it is important to understand the degradation reactions of the LIBs used in Electric Vehicles (EVs), aiming to establish the battery lifespan, predict and minimise material losses, and establish an adequate time for replacement. Moreover, LIBs applied in EVs suffer from two main categories of degradation, which are, specifically, calendar degradation and cycling degradation. There are several studies about battery degradation available in the literature, including different…

The applicability of the ERA5 reanalysis for estimating wind and solar energy generation over the contiguous United States is evaluated using wind speed and irradiance variables from multiple observational data sets. After converting ERA5 and observed meteorological variables into wind power and solar power, comparisons demonstrate that significant errors in the ERA5 reanalysis exist that limit its direct applicability for a wind and solar energy analysis. Overall, ERA5-derived solar power is biased high, while ERA5-derived wind power is biased low. During winter, the ERA5-derived solar power is biased high by 23% on average, while on an annual basis, the ERA5-derived wind power is biased low by 20%. ERA5-derived solar power errors are found to have consistent characteristics across the contiguous United States. Errors for the shortest duration and most extreme solar negative anomaly events are relatively small in the ERA5 when completely overcast conditions occur in both the ERA5 and observations. However, longer-duration anomaly events on weekly to monthly timescales, which…

Energy, gases, and solids in underground sites are stored in mining excavations, natural caverns, salt caverns, and in the pore spaces of rock formations. Aquifer formations are mainly isolated aquifers with significant spreading, permeability, and thickness, possessing highly mineralized non-potable waters. This study discusses the most important aspects that determine the storage of natural gas, hydrogen, or carbon dioxide in deep aquifers. In particular, the selection and characterization of the structure chosen for underground storage, the storage capacity, and the safety of the process are considered. The choice of underground sites is made on the basis of the following factors and criteria: geological, technical, economic, environmental, social, political, or administrative–legal. The geological and dynamic model of the storage site is then drawn based on the characteristics of the structure. Another important factor in choosing a structure for the storage of natural gas, hydrogen, or carbon dioxide is its capacity. In addition to the type and dimensions of the structure and…

The textile industry is global, and most brands export their products to many different markets with different infrastructures, logistics, and regulations. A textile waste recovery system that works in one country may fail in another. European Union legislation (Directive (EU) 2018/851) mandates that post-consumer textile waste must be separately collected in all associated countries. This directive has also stated that, in January 2025, the rate of textile waste recycling in Europe should be increased. Local governments will be under pressure to improve the collection, sorting, and recycling of textiles. Supporting local governments could be part of a more long-term approach to managing high-value textile waste by implementing Extended Producer Responsibility, which would increase the recycling rate of textile companies. This would enable reuse of over 60% of recovered clothes, recycling into fibers of 35%, and only throwing away 5%. Today, most textile waste (85%) is disposed of as solid waste and must be disposed of through municipal or local waste management systems that either…

This comprehensive review examines the role of sustainable aviation fuels (SAFs) in promoting a more environmentally responsible aviation industry. This study explores various types of biofuels, including hydroprocessed esters and fatty acids (HEFAs), Fischer–Tropsch (FT) fuels, alcohol-to-jet (ATJ) fuels, and oil derived from algae. Technological advancements in production and processing have enabled SAF to offer significant reductions in greenhouse gas emissions and other pollutants, contributing to a cleaner environment and better air quality. The review addresses the environmental, economic, and technical benefits of SAF, as well as the challenges associated with their adoption. Lifecycle analyses are used to assess the net environmental benefits of SAF, with a focus on feedstock sustainability, energy efficiency, and potential impacts on biodiversity and land use. Challenges such as economic viability, scalability, and regulatory compliance are discussed, with emphasis on the need for supportive policies and international collaboration to ensure the long-term sustainability of…

Power system flexibility is becoming increasingly critical in modern power systems due to the quick switch from fossil fuel-based power generation to renewables, old-fashioned infrastructures, and a sharp rise in demand. If a power system complies with financial restrictions and responds quickly to unforeseen shifts in supply and demand, it can be considered flexible. It can ramp up production during periods of high demand or increase it during unanticipated or scheduled events. The broad use of renewable energy in the power grid can provide environmental and economic benefits; nevertheless, renewables are highly stochastic in nature, with variability and uncertainty. New management with adequate planning and operation in the power system is necessary to address the challenges incorporated with the penetration of renewable energy. The primary aim of this review is to provide a comprehensive overview of power system flexibility, including appropriate definitions, parameters, requirements, resources, and future planning, in a compact way. Moreover, this paper potentially addresses the…

The increasing level of anthropogenic CO2 in the atmosphere has made it imperative to investigate an efficient method for carbon sequestration. Geological carbon sequestration presents a viable path to mitigate greenhouse gas emissions by sequestering the captured CO2 deep underground in rock formations to store it permanently. Geochemistry, as the cornerstone of geological CO2 sequestration (GCS), plays an indispensable role. Therefore, it is not just timely but also urgent to undertake a comprehensive review of studies conducted in this area, articulate gaps and findings, and give directions for future research areas. This paper reviews geochemistry in terms of the sequestration of CO2 in geological formations, addressing mechanisms of trapping, challenges, and ways of mitigating challenges in trapping mechanisms; mineralization and methods of accelerating mineralization; and the interaction between rock, brine, and CO2 for the long-term containment and storage of CO2. Mixing CO2 with brine before or during injection, using microbes, selecting sedimentary reservoirs with reactive…

This publication explores current and prospective methods for hydrogen production and purification, with a strong emphasis on membrane-based technologies for purification and separation. This focus is justified by the ongoing shift towards renewable energy sources (RESs) in electricity generation, necessitating strategic changes to increase hydrogen utilization, particularly in the automotive, heavy road, and rail sectors, by 2025–2030. The adoption of hydrogen from RESs in the construction, energy, and industrial sectors (e.g., for process heat or fertilizer production) is also under consideration, driving the need for innovative production, separation, and purification methods. Historically, industrial-scale hydrogen has been predominantly derived from fossil fuels, but renewable sources such as electrolysis, biological, and thermal processes now offer alternatives with varying production efficiencies (0.06–80%) and gas compositions. Therefore, selecting appropriate separation and purification methods is critical based on specific usage requirements and the gas composition.…

This paper presents an overview of the status and future prospects of fuel-cell electric vehicles (FC-EVs). As global concerns about emissions escalate, FC-EVs have emerged as a promising substitute for traditional internal combustion engine vehicles. This paper discusses the fundamentals of fuel-cell technology considering the major types of fuel cells that have been researched and delves into the most suitable fuel cells for FC-EV applications, including comparisons with mainstream vehicle technologies. The present state of FC-EVs, ongoing research, and the challenges and opportunities that need to be accounted for are discussed. Furthermore, the comparison between promising proton-exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) technologies used in EVs provides valuable insights into their respective strengths and challenges. By synthesizing these aspects, the paper aims to provide a comprehensive understanding and facilitate decision-making for future advancements in sustainable FC-EV transportation, thereby contributing to the realization of a cleaner,…

This review paper examines acid and alkaline pretreatments on perennial grasses for second-generation (2G) bioethanol production, a relatively unexplored area in this field. It compares the efficiency of these pretreatments in producing fermentable sugar and bioethanol yield. This study finds that alkaline pretreatment is more effective than acidic pretreatment in removing lignin and increasing sugar yield, leading to higher ethanol yields. However, it is costlier and requires longer reaction times than acidic pretreatment, while acidic pretreatment often leads to the formation of inhibitory compounds at higher temperatures, which is undesirable. The economic and environmental impacts of lignocellulosic biomass (LCB) are also assessed. It is revealed that LCB has a lower carbon but higher water footprint and significant costs due to pretreatment compared to first-generation biofuels. This review further explores artificial intelligence (AI) and advanced technologies in optimizing bioethanol production and identified the gap in literature regarding their application to pretreatment…

Photovoltaic panels play a pivotal role in the renewable energy sector, serving as a crucial component for generating environmentally friendly electricity from sunlight. However, a persistent challenge lies in the adverse effects of rising temperatures resulting from prolonged exposure to solar radiation. Consequently, this elevated temperature hinders the efficiency of photovoltaic panels and reduces power production, primarily due to changes in semiconductor properties within the solar cells. Given the depletion of limited fossil fuel resources and the urgent need to reduce carbon gas emissions, scientists and researchers are actively exploring innovative strategies to enhance photovoltaic panel efficiency through advanced cooling methods. This paper conducts a comprehensive review of various cooling technologies employed to enhance the performance of PV panels, encompassing water-based, air-based, and phase-change materials, alongside novel cooling approaches. This study collects and assesses data from recent studies on cooling the PV panel, considering both environmental and…

With the increasing global emphasis on green energy and sustainable development goals, the electrocatalytic oxygen evolution reaction (OER) is gradually becoming a crucial focus in research on water oxidation for hydrogen generation. However, its complicated reaction processes associated with its high energy barrier severely limit the efficiency of energy conversion. Recently, layered double hydroxide (LDH) has been considered as one of the most promising catalysts in alkaline media. Nonetheless, lacking a deep insight into the kinetic process of the electrocatalytic OER process is detrimental to the further optimization of LDH catalysts. Therefore, monitoring the catalytic reaction kinetic process via surface-sensitive in situ spectroscopy is especially important. In particular, the in situ Raman technique is capable of providing fingerprint information for surface species and intermediates in the operating environment. From the perspective of Raman spectroscopy, this paper provides an exhaustive overview of research progress in in situ Raman for the characterization of the…

Electric vehicles (EVs) play a crucial role in the global transition towards decarbonization and renewable energy resources (RERs). As EVs gain popularity, this has resulted in various challenges for the power grid, such as an intensified peak-to-valley load differential, causing transformer overloading. Vehicle-to-grid (V2G) technology has emerged as a promising solution due to its controllable charging and discharging capabilities. Mature business schemes can incentivize the development of V2G technology. However, the business schemes of V2G technology are still unclear. Therefore, this paper provides a comprehensive review of the business schemes associated with V2G technology, especially focusing on its feasibility and challenges with respect to the electricity market. In this paper, several business schemes with respect to the electricity market are explored by conducting extensive literature reviews, including peak-to-valley arbitrage, the spot market, demand–response (DR), frequency regulation, voltage regulation, spinning reserve, and black start. Next, application scenarios…

Today, hydrogen is one of the best options for generating electrical energy, for both industrial and residential use. The greatest volume of hydrogen produced today derives from processes that utilize petroleum. Although hydrogen has numerous benefits, continuing to produce it by these means is undesirable. This document presents a review of the literature on biohydrogen production based on an analysis of over 15 types of terrestrial and marine biomasses. The fundamental components of different production systems are described, with a focus on the thermochemical processes of pyrolysis and gasification, which have been identified as two of the most effective, practical ways to produce hydrogen from biomass. It also discusses catalysts, solid residues, and residual water that are used in the thermochemical production of biohydrogen. The article ends with an analysis of hydrogen and its benefits as an energy option with great potential in the short term to participate in the transition from fossil fuels.

This paper introduces a novel approach for rapidly balancing lithium-ion batteries using a single DC–DC converter, enabling direct energy transfer between high- and low-voltage cells. Utilizing relays for cell pair selection ensures cost-effectiveness in the switch network. The control system integrates a battery-monitoring IC and an MCU to oversee cell voltage and ensure battery protection. A prototype circuit with twelve lithium-ion batteries demonstrates the method’s efficacy, achieving a remarkable balancing time of 48 min during charging with a maximum efficiency of 89.85%. Comparative analysis with other methods underscores the superior performance of the proposed balancing circuit in terms of balancing time and implementation cost. Furthermore, this paper delves into hardware aspects of battery management systems (BMSs) for electric vehicles and stationary applications. It offers an overview of prevailing concepts in state-of-the-art systems, aiding readers in assessing considerations essential for BMS design in various applications. The discussion includes examples of…

The coupling between modern electric power physical and cyber systems is deepening. An increasing number of users are gradually participating in power operation and control, engaging in bidirectional interactions with the grid. The evolving new power system is transforming into a highly intelligent socio–cyber–physical system, featuring increasingly intricate and expansive architectures. Demands for stable system operation are becoming more specific and rigorous. The new power system confronts significant challenges in areas like planning, dispatching, and operational maintenance. Hence, this paper aims to comprehensively explore potential synergies among various power system components from multiple viewpoints. It analyzes numerous core elements and key technologies to fully unlock the efficiency of this coupling. Our objective is to establish a solid theoretical foundation and practical strategies for the precise implementation of integrated planning and operation dispatching of source–grid–load–storage systems. Based on this, the paper first delves into the theoretical concepts…

The increase in global average temperature, mainly due to the high rate of greenhouse gas emissions, has triggered severe global warming and climate change. In Europe, the building sector accounts for a significant portion of emissions and energy consumption, prompting attention on nearly-zero-energy buildings (nZEBs) and zero-carbon buildings, as they play a pivotal role in reaching the goal of climate neutrality by 2050. Passive systems offer a promising solution, optimizing energy usage by better adapting buildings to their local climates. This paper reviews the state-of-the-art of passive heating and cooling techniques, exploring their contributions to contemporary architecture and showcasing their features and adaptability across different climates. Furthermore, the link between traditional and bioclimatic architecture is assessed. Recent years have witnessed a surge in publications on bioclimatic solar passive strategies, reflecting an intensified debate on climate change. Europe leads research in this area, aligned with initiatives like the Green Deal and Fit for 55. While…

Global coal consumption is continuously increasing. It is still the primary fuel used in power plants. Despite policies in the European Union aimed at reducing coal consumption, there are countries in the world where coal use continues to rise (China and India are the largest consumers of coal). Coal combustion produces waste, 70% of which is fly ash. It consists mainly of SiO2 and Al2O3. Fly ash also includes Fe2O3, TiO2, MgO, K2O, and CaO. This article describes various methods of using fly ash. Fly ash can be used in the cement industry, as a filler in materials, in zeolite synthesis, in cenosphere separation, in agriculture, in water purification, in road construction as an asphalt filler, and in mine backfilling. An interesting method of using fly ash as a filler in the production of rigid polyurethane foam was also described. The article concerns potential uses in accordance with the principles of a Circular Economy. The environmental, energy, and material aspects are discussed.

As the adoption of Electric Vehicles (EVs) accelerates, driven by increasing urbanization and the push for sustainable infrastructure, the need for innovative solutions to support this growth has become more pressing. Vehicle-to-Grid (V2G) technology presents a promising solution by enabling EVs to engage in bidirectional interactions with the electrical grid. Through V2G, EVs can supply energy back to the grid during peak demand periods and draw power during off-peak times, offering a valuable tool for enhancing grid stability, improving energy management, and supporting environmental sustainability. Despite its potential, the large-scale implementation of V2G faces significant challenges, particularly from a technological and regulatory standpoint. The success of V2G requires coordinated efforts among various stakeholders, including vehicle manufacturers, infrastructure providers, grid operators, and policymakers. In addition to the technical barriers, such as battery degradation due to frequent charging cycles and the need for advanced bidirectional charging systems, regulatory…

This study aims to provide an overview of the growing need for renewable energy conversion and aligns with the broader context of environmentally friendly energy, specifically through producing syngas from biomass. Unlike natural gas, which is mainly composed of methane, syngas contains a mixture of combustible CO, H2, and CnHm. Therefore, optimizing its production requires a thorough examination of various operational parameters such as the gasifying agent, the equivalence ratio, the biofuel type, and the state, particularly in densified forms like pellets or briquettes. As new biomass sources are continually discovered and tested, operational parameters are also constantly evaluated, and new techniques are continuously developed. Indeed, these techniques include different gasifier types and the use or non-use of catalysts during biofuel conversion. The present study focuses on these critical aspects to examine their effect on the efficiency of syngas production. It is worth mentioning that syngas is the primary gaseous product from gasification. Moreover, it is essential to note…

This paper presents a detailed review of the existing literature on peer-to-peer (P2P) energy trading considering market architectures, trading strategies, and enabling technologies. P2P energy trading enables individual users in the electricity network to act as sellers or buyers and trade energy among each other. To facilitate the discussion on different aspects of P2P energy trading, this paper focuses on P2P market mechanisms, relevant bidding strategies, and auction models. In addition, to solve the energy management problems associated with P2P energy trading, this paper investigates widely used solution methods such as game-theoretic models, mathematical optimisation, as well as more recent machine learning techniques and evaluates them in a critical manner. The outcomes of this investigation along with the identification of the challenges and limitations will allow researchers to find suitable P2P energy trading mechanisms based on different market contexts. Moreover, the discussions on potential future research directions are expected to improve the effectiveness of P2P…

Hydrogen (H2) is positioned as a key solution to the decarbonization challenge in both the energy and transportation sectors. While hydrogen is a clean and versatile energy carrier, it poses significant safety risks due to its wide flammability range and high detonation potential. Hydrogen leaks can occur throughout the hydrogen value chain, including production, storage, transportation, and utilization. Thus, effective leak detection systems are essential for the safe handling, storage, and transportation of hydrogen. This review aims to survey relevant codes and standards governing hydrogen-leak detection and evaluate various sensing technologies based on their working principles and effectiveness. Our analysis highlights the strengths and limitations of the current detection technologies, emphasizing the challenges in achieving sensitive and specific hydrogen detection. The results of this review provide critical insights into the existing technologies and regulatory frameworks, informing future advancements in hydrogen safety protocols.

Solar-based home PV systems are the most amazing eco-friendly energy innovations in the world, which are not only climate-friendly but also cost-effective solutions. The tropical environment of Malaysia makes it difficult to adopt photovoltaic (PV) systems because of the protracted rainy monsoon season, which makes PV systems useless without backup batteries. Large quantities of lithium-ion battery (LIB) trash are being produced by the electric vehicle (EV) sector. A total of 75% of the highest capacity levels have been discarded. By 2035, it is predicted that the wasted LIBs held as a result of expensive recycling and difficult material separation would carry up to 1200 GWh. An economical and sustainable option is offered by our study, which prototypes a replicated LIB pack that is incorporated into a PV home system. This study investigates the transformational power of second-life electric vehicle batteries (SLEVBs) when incorporated into home photovoltaic (PV) systems. The concept entails reusing existing electric vehicle batteries for stationary applications, offering a unique…

Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse discharge sources, making the evaluation of PD data challenging. The reliability of diagnostics for MV cables hinges on the precise interpretation of PD activity. To streamline the repair and maintenance of cables, it becomes crucial to discern and categorize PD types accurately. This paper presents a comprehensive review encompassing the realms of detection, feature extraction, artificial intelligence, and optimization techniques employed in the classification of PD signals/sources. Its exploration encompasses a variety of sensors utilized for PD detection, data processing methodologies for efficient feature extraction, optimization techniques dedicated to selecting optimal features, and artificial intelligence-based approaches for the classification…

As the global demand for renewable energy continues to rise, biogas technology has emerged as a promising solution for sustainable energy generation. This review article presents the advantages of biogas technologies and extensively discusses the main principles of biogas production in the methane fermentation process. In this respect, the main parameters of the process, which require monitoring and are at the same time decisive for its course and efficiency are described, the principles of substrate selection are discussed and the necessity and advantages of the use of organic waste according to the model of a circular economy and the concept of sustainable development, are indicated. The part on biogas production is summarised with an explanation of the necessity to treat and purify biogas, taking into account the share of methane extracted. A special place in this paper is devoted to the design, construction, functioning and operation of biogas plants, based on both scientific and practical aspects. In conclusion of this chapter, the economic aspects and profitability of…

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings and their energy systems, and they are widely used in building energy management. These simulation tools can be categorized into white-box and black-box models based on the level of detail and transparency of the model’s inputs and outputs. This review publication comprehensively analyzes the white-box, black-box, and web tool models for building energy simulation tools. We also examine the different simulation scales, ranging from single-family homes to districts and cities, and the various modelling approaches, such as steady-state, quasi-steady-state, and dynamic. This review aims to pinpoint the advantages and drawbacks of various simulation tools, offering guidance for upcoming research in the field of building energy management. We aim to help…

With the increasingly serious problems of energy shortage and environmental degradation, countries around the world are actively developing safe, environmentally friendly, and renewable energy. Biomass energy has become an ideal substitute for fossil fuels due to its abundant reserves, good renewable performance, and zero carbon emissions. This paper discusses the importance and potential of biomass energy as a renewable energy source for China’s energy development, mainly including the three biomass conversion methods of physics, chemistry, and biology, seven utilization technologies, such as direct combustion, gasification, and pyrolysis, and five application approaches, such as biomass power generation, biomass gas fuel, biomass liquid fuel, and bio-based materials. This review systematically analyzes the challenges faced by China’s development of biomass energy and discusses the future development direction of biomass. The utilization of biomass resources should take a comprehensive and high-value path. China is actively looking for new energy utilization paths, and biomass…

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimising MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based-control and deep learning techniques, including gated recurrent units (GRU), basic recurrent neural network (RNN) and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to…

The conversion of lignocellulosic agricultural waste into biofuels and other economically valuable compounds can reduce dependence on fossil fuels, reduce harmful gas emissions, support the sustainability of natural resources, including water, and minimize the amount of waste in landfills, thus reducing environmental degradation. In this paper, the conversion of agricultural wastes into biomethane, biohydrogen, biodiesel, bioethanol, biobutanol, and bio-oil is reviewed, with special emphasis on primary and secondary agricultural residues as substrates. Some novel approaches are mentioned that offer opportunities to increase the efficiency of waste valorization, e.g., hybrid systems. In addition to physical, chemical, and biological pretreatment of waste, some combined methods to mitigate the negative effects of various recalcitrant compounds on waste processing (alkali-assisted thermal pretreatment, thermal hydrolysis pretreatment, and alkali pretreatment combined with bioaugmentation) are evaluated. In addition, the production of volatile fatty acids, polyhydroxyalkanoates,…

The relentless advancement of digital technologies has the potential to significantly reshape the energy landscape as digital technologies become increasingly integrated into diverse sectors of the economy. This study explores the intricate relationship between digitalization and energy in EU countries, focusing on its direct and indirect impacts on energy consumption, structure, and intensity. Furthermore, this study explores the mediating mechanisms that facilitate these changes, including the role of technological innovation and government efficiency in the relationship between digitalization and energy outcomes. Focusing on EU countries and using the system-GMM method, this research accounts for the heterogeneity in the impact of digitalization on energy across various member states. It examines the varying effects in different countries, considering their income levels, environmental regulations, and green investments. The results demonstrate that the strategic deployment of digitalization in EU countries substantially benefits the energy sector. By optimizing energy…

Significant concerns over energy security and environmental impact reduction will drive all stakeholders to generate proper alternative energies. Biodiesel is a prospective cleaner-burning biofuel that can contribute on addressing these concerns globally. Presently, pure biodiesel (B100) application is still facing several obstacles, principally in terms of its cold flow properties. Improvement in cold flow behavior parameters is the solution to promoting biodiesel implementation at a higher percentage and wider environmental temperature range. This study provides a detailed review of several improvement methods, both physical, chemical, and biological, from various scientific sources, to elevate the cold fluidity characteristics of biodiesel. The investigated methods convincingly offer proper enhancement in the cold flow properties of biodiesel. Mostly, this improvement is accompanied by an alleviation in oxidation stability, cetane number, and/or viscosity. However, the skeletal isomerization method presents promising cold fluidity refinement with minimal reduction in other…

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data…

With the rapid development of the new energy industry, supercapacitors have become key devices in the field of energy storage. To forecast the remaining useful life (RUL) of supercapacitors, we introduce a new technology that integrates variational mode decomposition (VMD) with a bidirectional long short-term memory (BiLSTM) neural network. Firstly, the aging experiments of supercapacitors under various temperatures and voltages were carried out to obtain aging data. Then, VMD was implemented to decompose the aging data, which helped to eliminate disturbances, including capacity recovery and test errors. Then, the hyperparameters of BiLSTM were adjusted, employing the sparrow search algorithm (SSA) to improve the consistency between the input data and the network structure. After obtaining the optimal hyperparameters of BiLSTM, the decomposed aging data were input into BiLSTM for prediction. The experimental results showed that the VMD-SSA-BiLSTM model proposed in this paper has high prediction accuracy and high robustness under different temperatures and voltages, with an average…

As the demand for sustainable energy solutions grows, there is a critical requirement for continuous innovation to optimize the performance and safety of renewable energy systems (RESs). Closed-loop digital twins (CLDTs)—synchronized virtual replicas embedded with real-time data and control loops to mirror the behavior of physical systems—have emerged as a promising tool for achieving this goal. This paper presents a systematic literature review on the application of digital twin (DT) technology in the context of RESs with an emphasis on the impact of DTs on the efficiency, performance, and safety assurance of RESs. It explores the concept of CLDTs, highlighting their key functionalities and potential benefits for various renewable energy technologies. However, their effective implementation requires a structured approach to integrate observation, orientation, decision, and action (OODA) processes. This study presents a novel OODA framework specifically designed for CLDTs to systematically identify and manage their key components. These components include real-time monitoring,…

This comprehensive review explores the application and impact of digital twin (DT) technology in bolstering the reliability of Floating Offshore Wind Turbines (FOWTs) and their supporting platforms. Within the burgeoning domain of offshore wind energy, this study contextualises the need for heightened reliability measures in FOWTs and elucidates how DT technology serves as a transformative tool to address these concerns. Analysing the existing scholarly literature, the review encompasses insights into the historical reliability landscape, DT deployment methodologies, and their influence on FOWT structures. Findings underscore the pivotal role of DT technology in enhancing FOWT reliability through real-time monitoring and predictive maintenance strategies, resulting in improved operational efficiency and reduced downtime. Highlighting the significance of DT technology as a potent mechanism for fortifying FOWT reliability, the review emphasises its potential to foster a robust operational framework while acknowledging the necessity for continued research to address technical…

Kesterite-based copper zinc tin sulfide (CZTS) and copper zinc tin selenide (CZTSe) thin films have attracted considerable attention as promising materials for sustainable and cost-effective thin-film solar cells. However, the successful integration of these materials into photovoltaic devices is hindered by the coexistence of secondary phases, which can significantly affect device performance and stability. This review article provides a comprehensive overview of recent progress and challenges in controlling secondary phases in kesterite CZTS and CZTSe thin films. Drawing from relevant studies, we discuss state-of-the-art strategies and techniques employed to mitigate the formation of secondary phases. These include a range of deposition methods, such as electrodeposition, sol-gel, spray pyrolysis, evaporation, pulsed laser deposition, and sputtering, each presenting distinct benefits in enhancing phase purity. This study highlights the importance of employing various characterization techniques, such as X-ray diffraction, Raman spectroscopy, scanning electron microscopy, and…

This paper introduces an innovative approach to Wind Turbine Blade (WTB) inspection through the synergistic use of thermal and RGB imaging, coupled with advanced deep learning techniques. We curated a unique dataset of 1000 thermal images of healthy and faulty blades using a FLIR C5 Compact Thermal Camera, which is equipped with Multi-Spectral Dynamic Imaging technology for enhanced imaging. This paper focuses on evaluating 35 deep learning classifiers, with a standout ensemble model combining Vision Transformer (ViT) and DenseNet161, achieving a remarkable 100% accuracy on the dataset. This model demonstrates the exceptional potential of deep learning in thermal diagnostic applications, particularly in predictive maintenance within the renewable energy sector. Our findings underscore the synergistic combination of ViT’s global feature analysis and DenseNet161’s dense connectivity, highlighting the importance of controlled environments and sophisticated preprocessing for accurate thermal image capture. This research contributes significantly to the field by providing a comprehensive…

Climate change is a major concern for the sustainable development of global energy systems. Hydrogen produced through water electrolysis offers a crucial solution by storing and generating renewable energy with minimal environmental impact, thereby reducing carbon emissions in the energy sector. Our research evaluates current hydrogen production technologies, such as alkaline water electrolysis (AWE), proton exchange membrane water electrolysis (PEMWE), solid oxide electrolysis (SOEC), and anion exchange membrane water electrolysis (AEMWE). We systematically review life cycle assessments (LCA) for these technologies, analyzing their environmental impacts and recent technological advancements. This study fills essential gaps by providing detailed LCAs for emerging technologies and evaluating their scalability and environmental footprints. Our analysis outlines the strengths and weaknesses of each technology, guiding future research and assisting stakeholders in making informed decisions about integrating hydrogen production into the global energy mix. Our approach highlights…

Carbon Capture, Utilization, and Storage (CCUS) represents a vital technology for addressing pressing global challenges such as climate change and carbon emissions. This research aims to explore the relationship between the CCUS capability and carbon emissions in the United States considering thirteen predictors of CCUS and carbon emissions. Incorporating these predictors, we aim to offer policymakers insights to enhance CCUS capabilities and reduce carbon emissions. We utilize diverse econometric techniques: OLS, Lasso, Ridge, Elastic Net, Generalized Method of Moments, and Seemingly Unrelated Regression. Elastic Net outperforms the other models in explaining CCUS, while OLS is effective for carbon emissions. We observe positive impacts of the number of projects and foreign direct investment on the CCUS capacity, but limited influence from the CCUS technology level. However, the relationship between the CCUS capacity and carbon emissions remains limited. Our study highlights the importance of incentivizing projects to increase CCUS capabilities and recognizes the critical role of…

Carbon dioxide, the leading contributor to anthropogenic climate change, is released mainly via fossil fuel combustion, mostly for energy generation. Carbon capture technologies are employed for reducing the emissions from existing huge point sources, along with capturing them from direct air, to reduce the existing concentration. This paper provides a quantitative analysis of the various subtypes of carbon capture technologies with the aim of providing an assessment of each from technological, social, geo-political, economic, and environmental perspectives. Since the emissions intensity and quantity, along with the social–political–economic conditions, vary in different geographic regions, prioritising and finding the right type of technology is critical for achieving ambitious net-zero targets. Four main types of carbon capture technology were analysed (adsorption, absorption, membrane, and cryogenic) under four scenarios depending on the jurisdiction. The Technique for Order of Preference by Similarity to Ideal Solution (also known as the TOPSIS method) was used to establish a…

Due to the large quantities of carbon emissions generated by the transportation sector, cleaner automotive technologies are needed aiming at a green energy transition. In this scenario, hydrogen is pointed out as a promising fuel that can be employed as the fuel of either a fuel cell or an internal combustion engine vehicle. Therefore, in this work, we propose the design and modeling of a fuel cell versus an internal combustion engine passenger car for a driving cycle. The simulation was carried out using the quasistatic simulation toolbox tool in Simulink considering the main powertrain components for each vehicle. Furthermore, a brief analysis of the carbon emissions associated with the hydrogen production method is addressed to assess the clean potential of hydrogen-powered vehicles compared to conventional fossil fuel-fueled cars. The resulting analysis has shown that the hydrogen fuel cell vehicle is almost twice as efficient compared to internal combustion engines, resulting in a lower fuel consumption of 1.05 kg-H2/100 km in the WLTP driving cycle for the fuel cell vehicle,…

This research, conducted throughout the years 2022 and 2023, examines the role of blockchain technology in optimizing Demand Response (DR) within Smart Grids (SGs). It critically assesses a range of blockchain architectures, evaluating their impact on enhancing DR’s efficiency, security, and consumer engagement. Concurrently, it addresses challenges like scalability, interoperability, and regulatory complexities inherent in merging blockchain with existing energy systems. By integrating theoretical and practical viewpoints, it reveals the potential of blockchain technology to revolutionize Demand Response (DR). Findings affirm that integrating blockchain technology into SGs effectively enhances the efficiency and security of DR, and empirical data illustrate substantial improvements in both cases. Furthermore, key challenges include scalability and interoperability, and also identifying opportunities to enhance consumer engagement and foster system transparency in the adoption of blockchain within DR and SGs. Finally, this work emphasizes the necessity for further investigation to…

Microgrids can assist in managing power supply and demand, increase grid resilience to adverse weather, increase the deployment of zero-emission energy sources, utilise waste heat, and reduce energy wasted through transmission lines. To ensure that the full benefits of microgrid use are realised, hybrid renewable energy-based microgrids must operate at peak efficiency. To offer an optimal solution for managing microgrids with hybrid renewable energy sources (HRESs) while taking microgrid reserve margins into account, the particle swarm optimisation (PSO) method is suggested. The suggested approach demonstrated good performance in terms of charging and discharging BESS and maintaining the necessary reserve margins to supply critical loads if the grid and renewable energy sources are unavailable. On a clear day, the amount of electricity sold to the grid increased by 58%, while on a partially overcast day, it increased by 153%. Microgrids provide a good return on investment for their operators when they are run at peak efficiency. This is because the BESS is largely charged during…

As a key component of transportation decarbonization, the adoption of electric vehicles (EVs) is rapidly increasing. However, EV batteries are typically retired once their state of health drops to around 80%, usually after 10 to 20 years of use. Despite this decline, retired EV batteries still retain 70–80% of their original capacity. Reusing these retired batteries as second-life batteries (SLBs) for battery energy storage systems can offer significant economic and environmental benefits. This article provides a comprehensive analysis of the technical challenges and solutions, economic feasibility, environmental impacts, and case studies of existing projects. It also explores the current battery recycling process. The article concludes with an overview of the feasibility assessment, future development trends, market potential, and policy recommendations for the battery energy storage market.

Solid Oxide Fuel Cells (SOFCs) are emerging as a leading solution in sustainable power generation, boasting high power-to-energy density and minimal emissions. With efficiencies potentially exceeding 60% for electricity generation alone and up to 85% when in cogeneration applications, SOFCs significantly outperform traditional combustion-based technologies, which typically achieve efficiencies of around 35–40%. Operating effectively at elevated temperatures (600 °C to 1000 °C), SOFCs not only offer superior efficiency but also generate high-grade waste heat, making them ideal for cogeneration applications. However, these high operational temperatures pose significant thermal management challenges, necessitating innovative solutions to maintain system stability and longevity. This review aims to address these challenges by offering an exhaustive analysis of the latest advancements in SOFC thermal management. We begin by contextualizing the significance of thermal management in SOFC performance, focusing on its role in enhancing operational stability and minimizing thermal stresses.…

The fast growth of the world’s energy demand in the modernized world has stirred many countries around the globe to focus on power generation by abundantly available renewable energy resources. Among them, wind energy has attained significant attention owing to its environment-friendly nature along with other fabulous advantages. However, wind-integrated power systems experience numerous voltage instability complexities due to the sporadic nature of wind. This paper comprehensively reviews the problems of voltage instability in wind-integrated power systems, its causes, consequences, improvement techniques, and implication of grid codes to keep the operation of the network secure. Thorough understanding of the underlying issues related to voltage instability is necessary for the development of effective mitigation techniques in order to facilitate wind integration into power systems. Therefore, this review delves into the origin and consequences of voltage instability, emphasizing its adverse impacts on the performance and reliability of power systems. Moreover, it sheds light on…

This paper reviews sintered silver (s-Ag) die-attach materials for wide band gap (WBG) semiconductor packaging. WBG devices that die-attach with s-Ag have attracted a lot of attention owing to their low energy loss and high temperature operation capabilities. For their practical operation, a reliability design should be established based on the failure of physics of the s-Ag die layer. This paper first focuses on the material characteristics of the s-Ag and tensile mechanical properties. Then, the s-Ag die-attach reliability is assessed with high-temperature storage, power cycling, and thermal shock tests. Each fracture mode was discussed by considering both the fracture surface analysis results and its mechanical properties. Finally, the effective reliability design parameters of the s-Ag die layer are introduced.

Distributed photovoltaic (PV) in the distribution network accounted for an increasing proportion of the distribution network, and the power quality of the distribution network of the power quality problem is more and more significant. In this paper, the voltage regulation methods for low-voltage distribution networks containing high-penetration PV are investigated. First, the working principles of the four voltage control methods are introduced: energy storage system configuration, regulating the reactive power output of PV inverters, restricting the active power output of PV, adjusting the switching positions of on-load regulator trap changer and distribution network reconfiguration, and then, in combination with the recent related research, the optimization of each method is compared horizontally with its respective concerns and characteristics. The optimization of each method is compared horizontally with the recent studies to find out the focus and characteristics of each method, and the shortcomings of each method are explored. Coordinated voltage control through multiple…

The escalating adoption of low-carbon energy technologies underscores the imperative to transition from conventional fossil fuel-dependent sources to sustainable alternatives. The expansion of Distributed Energy Resources (DERs) signifies an essential shift towards a more resilient and environmentally friendly energy landscape. However, integrating inverter-based DERs introduces challenges, particularly in system inertia and grid instability. This review delves into the critical area of inverter-based grid control strategies, focusing on the primary and secondary control mechanisms. Primary controls are investigated, including traditional droop control and low-voltage ride-through (LVRT) capability. The secondary control strategies, involving virtual impedance (VI) and load frequency control (LFC), are vital in maintaining grid stability and reliability are reviewed. The aim is to offer a comprehensive understanding of the principles, advancements, and challenges associated with inverter-based grid controls, contributing valuable insights for the seamless integration of DERs into…

Hydrothermal carbonization (HTC) has recently emerged as a promising technology for converting diverse forms of waste with a high moisture content into value-added products such as biofuel, biochar, and activated carbon. With an increasing demand for sustainable and carbon-neutral energy sources, HTC has attracted considerable attention in the literature. However, a successful transition from laboratory-scale to large-scale industrial applications entails notable challenges. This review critically assesses the upscaling of hydrothermal carbonization processes, emphasizing the challenges, innovations, and environmental implications associated with this transition. The challenges inherent in upscaling HTC are comprehensively discussed, including aspects such as reactor design, process optimization, and the current treatment technology for process water. This review presents recent innovations and technological advancements that address these challenges and explores integrated solutions to enhancing hydrothermal carbonization’s scalability. Additionally, this review highlights key…

The battery pack is at the heart of electric vehicles, and lithium-ion cells are preferred because of their high power density, long life, high energy density, and viability for usage in relatively high and low temperatures. Lithium-ion batteries are negatively affected by overvoltage, undervoltage, thermal runaway, and cell voltage imbalance. The minimisation of cell imbalance is particularly important because it causes uneven power dissipation by each cell and, hence, temperature distribution that adversely impacts the battery lifetime. Several papers in the literature proposed advanced cell-balancing techniques to increase the effectiveness of basic cell-balancing approaches, reduce power losses, and reduce the number of components in balancing circuits. The new developments and optimisations over the last few years have been particularly intense due to the increased interest in battery technologies for several end-use applications. This paper reviews and discusses recent cell-balancing techniques or methods, covering their operating principles and the optimised utilisation of…

ANNs have become a cornerstone in efficiently managing building energy management systems (BEMSs) as they offer advanced capabilities for prediction, control, and optimization. This paper offers a detailed review of recent, significant research in this domain, highlighting the use of ANNs in optimizing key energy systems, such as HVAC systems, domestic water heating (DHW) systems, lighting systems (LSs), and renewable energy sources (RESs), which have been integrated into the building environment. After illustrating the conceptual background of the most common ANN architectures for controlling BEMSs, the current work dives deep into relative research applications, thereby exhibiting their methodology and outcomes. By summarizing the numerous impactful applications during 2015–2023, this paper categorizes the predominant ANN-based techniques according to their methodological approach, specific energy equipment, and experimental setups. Grounded in the different perspectives that the integrated studies illustrate, the primary focus of this paper is to evaluate the overall status of…