The 100 most-cited articles in Energies, 2017

Electric vehicles (EV), including Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), Fuel Cell Electric Vehicle (FCEV), are becoming more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace internal combustion engine (ICE) vehicles in the near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system could face huge instabilities with enough EV penetration, but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of the smart grid concept. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emissions produced by the transportation sector. However, there are some major obstacles for EVs to overcome before totally replacing ICE…

Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential…

Accurate load forecasting is an important issue for the reliable and efficient operation of a power system. This study presents a hybrid algorithm that combines similar days (SD) selection, empirical mode decomposition (EMD), and long short-term memory (LSTM) neural networks to construct a prediction model (i.e., SD-EMD-LSTM) for short-term load forecasting. The extreme gradient boosting-based weighted k-means algorithm is used to evaluate the similarity between the forecasting and historical days. The EMD method is employed to decompose the SD load to several intrinsic mode functions (IMFs) and residual. Separated LSTM neural networks were also employed to forecast each IMF and residual. Lastly, the forecasting values from each LSTM model were reconstructed. Numerical testing demonstrates that the SD-EMD-LSTM method can accurately forecast the electric load.

With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

The injected fluids in secondary processes supplement the natural energy present in the reservoir to displace oil. The recovery efficiency mainly depends on the mechanism of pressure maintenance. However, the injected fluids in tertiary or enhanced oil recovery (EOR) processes interact with the reservoir rock/oil system. Thus, EOR techniques are receiving substantial attention worldwide as the available oil resources are declining. However, some challenges, such as low sweep efficiency, high costs and potential formation damage, still hinder the further application of these EOR technologies. Current studies on nanoparticles are seen as potential solutions to most of the challenges associated with these traditional EOR techniques. This paper provides an overview of the latest studies about the use of nanoparticles to enhance oil recovery and paves the way for researchers who are interested in the integration of these progresses. The first part of this paper addresses studies about the major EOR mechanisms of nanoparticles used in the forms of nanofluids, nanoemulsions and…

The objective of this study was to study the structure and physicochemical properties of biochar derived from apple tree branches (ATBs), whose valorization is crucial for the sustainable development of the apple industry. ATBs were collected from apple orchards located on the Weibei upland of the Loess Plateau and pyrolyzed at 300, 400, 500 and 600 °C (BC300, BC400, BC500 and BC600), respectively. Different analytical techniques were used for the characterization of the different biochars. In particular, proximate and element analyses were performed. Furthermore, the morphological, and textural properties were investigated using scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, Boehm titration and nitrogen manometry. In addition, the thermal stability of biochars was also studied by thermogravimetric analysis. The results indicated that the increasing temperature increased the content of fixed carbon (C), the C content and inorganic minerals (K, P, Fe, Zn, Ca, Mg), while the yield, the content of volatile matter (VM), O and H, cation exchange…

The negative impact of the automotive industry on climate change can be tackled by changing from fossil driven vehicles towards battery electric vehicles with no tailpipe emissions. However their adoption mainly depends on the willingness to pay for the extra cost of the traction battery. The goal of this paper is to predict the cost of a battery pack in 2030 when considering two aspects: firstly a decade of research will ensure an improvement in material sciences altering a battery’s chemical composition. Secondly by considering the price erosion due to the production cost optimization, by maturing of the market and by evolving towards to a mass-manufacturing situation. The cost of a lithium Nickel Manganese Cobalt Oxide (NMC) battery (Cathode: NMC 6:2:2 ; Anode: graphite) as well as silicon based lithium-ion battery (Cathode: NMC 6:2:2 ; Anode: silicon alloy), expected to be on the market in 10 years, will be predicted to tackle the first aspect. The second aspect will be considered by combining process-based cost calculations with learning curves, which takes the increasing…

Climate change is recognised as one of the key challenges humankind is facing. The Information and Communication Technology (ICT) sector including data centres generates up to 2% of the global CO2 emissions, a number on par to the aviation sector contribution, and data centres are estimated to have the fastest growing carbon footprint from across the whole ICT sector, mainly due to technological advances such as the cloud computing and the rapid growth of the use of Internet services. There are no recent estimations of the total energy consumption of the European data centre and of their energy efficiency. The aim of this paper is to evaluate, analyse and present the current trends in energy consumption and efficiency in data centres in the European Union using the data submitted by companies participating in the European Code of Conduct for Data Centre Energy Efficiency programme, a voluntary initiative created in 2008 in response to the increasing energy consumption in data centres and the need to reduce the related environmental, economic and energy supply security impacts. The…

Nowadays, there is growing interest in all the smart technologies that provide us with information and knowledge about the human environment. In the energy field, thanks to the amount of data received from smart meters and devices and the progress made in both energy software and computers, the quality of energy models is gradually improving and, hence, also the suitability of Energy Conservation Measures (ECMs). For this reason, the measurement of the accuracy of building energy models is an important task, because once the model is validated through a calibration procedure, it can be used, for example, to apply and study different strategies to reduce its energy consumption in maintaining human comfort. There are several agencies that have developed guidelines and methodologies to establish a measure of the accuracy of these models, and the most widely recognized are: ASHRAE Guideline 14-2014, the International Performance Measurement and Verification Protocol (IPMVP) and the Federal Energy Management Program (FEMP). This article intends to shed light on these validation…

With the increase of power generation from renewable energy sources and due to their intermittent nature, the power grid is facing the great challenge in maintaining the power network stability and reliability. To address the challenge, one of the options is to detach the power generation from consumption via energy storage. The intention of this paper is to give an overview of the current technology developments in compressed air energy storage (CAES) and the future direction of the technology development in this area. Compared with other energy storage technologies, CAES is proven to be a clean and sustainable type of energy storage with the unique features of high capacity and long-duration of the storage. Its scale and cost are similar to pumped hydroelectric storage (PHS), thus CAES has attracted much attention in recent years while further development for PHS is restricted by the availability of suitable geological locations. The paper presents the state-of-the-art of current CAES technology development, analyses the major technological barriers/weaknesses and proposes…

In this paper, a hydrothermal carbonization (HTC) process is designed and modeled on the basis of experimental data previously obtained for two representative organic waste materials: off-specification compost and grape marc. The process accounts for all the steps and equipment necessary to convert raw moist biomass into dry and pelletized hydrochar. By means of mass and thermal balances and based on common equations specific to the various equipment, thermal energy and power consumption were calculated at variable process conditions: HTC reactor temperature T: 180, 220, 250 °C; reaction time θ: 1, 3, 8 h. When operating the HTC plant with grape marc (65% moisture content) at optimized process conditions (T = 220 °C; θ = 1 h; dry biomass to water ratio = 0.19), thermal energy and power consumption were equal to 1170 kWh and 160 kWh per ton of hydrochar produced, respectively. Correspondingly, plant efficiency was 78%. In addition, the techno-economical aspects of the HTC process were analyzed in detail, considering both investment and production costs. The production cost of…

Building energy consumption prediction plays an important role in improving the energy utilization rate through helping building managers to make better decisions. However, as a result of randomness and noisy disturbance, it is not an easy task to realize accurate prediction of the building energy consumption. In order to obtain better building energy consumption prediction accuracy, an extreme deep learning approach is presented in this paper. The proposed approach combines stacked autoencoders (SAEs) with the extreme learning machine (ELM) to take advantage of their respective characteristics. In this proposed approach, the SAE is used to extract the building energy consumption features, while the ELM is utilized as a predictor to obtain accurate prediction results. To determine the input variables of the extreme deep learning model, the partial autocorrelation analysis method is adopted. Additionally, in order to examine the performances of the proposed approach, it is compared with some popular machine learning methods, such as the backward propagation neural network (BPNN),…

The black start capability is vital for microgrids, which can potentially improve the reliability of the power grid. This paper proposes a black start strategy for microgrids based on a parallel restoration strategy. Considering the characteristics of distributed generations (DGs), an evaluation model, which is used to assess the black start capability of DGs, is established by adopting the variation coefficient method. Thus, the DGs with good black start capability, which are selected by a diversity sequence method, are restored first in parallel under the constraints of DGs and network. During the selection process of recovery paths, line weight and node importance degree are proposed under the consideration of the node topological importance and the load importance as well as the backbone network restoration time. Therefore, the whole optimization of the reconstructed network is realized. Finally, the simulation results verify the feasibility and effectiveness of the strategy.

Capacitive power transfer (CPT) technology is an effective and important alternative to the conventional inductive power transfer (IPT). It utilizes high-frequency electric fields to transfer electric power, which has three distinguishing advantages: negligible eddy-current loss, relatively low cost and weight, and excellent misalignment performance. In recent years, the power level and efficiency of CPT systems has been significantly improved and has reached the power level suitable for electric vehicle charging applications. This paper reviews the latest developments in CPT technology, focusing on two key technologies: the compensation circuit topology and the capacitive coupler structure. The comparison with the IPT system and some critical issues in practical applications are also discussed. Based on these analyses, the future research direction can be developed and the applications of the CPT technology can be promoted.

Global solar radiation is generally measured on a horizontal surface, whereas the maximum amount of incident solar radiation is measured on an inclined surface. Over the last decade, a number of models were proposed for predicting solar radiation on inclined surfaces. These models have various scopes; applicability to specific surfaces, the requirement for special measuring equipment, or limitations in scope. To find the most suitable model for a given location the hourly outputs predicted by available models are compared with the field measurements of the given location. The main objective of this study is to review on the estimation of the most accurate model or models for estimating solar radiation components for a selected location, by testing various models available in the literature. To increase the amount of incident solar radiation on photovoltaic (PV) panels, the PV panels are mounted on tilted surfaces. This article also provides an up-to-date status of different optimum tilt angles that have been determined in various countries.

The Heat Roadmap Europe (HRE) studies estimated a potential increase of the district heating (DH) share to 50% of the entire heat demand by 2050, with approximately 25–30% of it being supplied using large-scale electric heat pumps. This study builds on this potential and aims to document that such developments can begin now with technologies currently available. We present a database and the status of the technology and its ability of expansion to other European locations by reviewing experiences aimed at further research or application in the heating industry. This is based on a survey of the existing capacity of electric large-scale heat pumps with more than 1 MW thermal output, operating in European DH systems. The survey is the first database of its kind containing the technical characteristics of these heat pumps, and provides the basis for the analysis of this paper. By quantifying the heat sources, refrigerants, efficiency and types of operation of 149 units with 1580 MW of thermal output, the study further uses this data to analyze if the deployment of this technology on a…

Traditional power supply cords have become less important because they prevent large-scale utilization and mobility. In addition, the use of batteries as a substitute for power cords is not an optimal solution because batteries have a short lifetime, thereby increasing the cost, weight, and ecological footprint of the hardware implementation. Their recharging or replacement is impractical and incurs operational costs. Recent progress has allowed electromagnetic wave energy to be transferred from power sources (i.e., transmitters) to destinations (i.e., receivers) wirelessly, the so-called wireless power transfer (WPT) technique. New developments in WPT technique motivate new avenues of research in different applications. Recently, WPT has been used in mobile phones, electric vehicles, medical implants, wireless sensor network, unmanned aerial vehicles, and so on. This review highlights up-to-date studies that are specific to near-field WPT, which include the classification, comparison, and potential applications of these techniques in the real world. In addition, limitations and…

Nanomaterials are engineered materials with at least one dimension in the range of 1–100 nm. Nanofluids—nanoscale colloidal suspensions containing various nanomaterials—have distinctive properties and offer unprecedented potential for various sectors such as the energy, cosmetic, aerospace and biomedical industries. Due to their unique physico-chemical properties, nanoparticles are considered as very good candidates for smart drilling fluid formulation, i.e., fluids with tailor-made rheological and filtration properties. However, due to the great risk of adapting new technologies, their application in oil and gas industry is not, to date, fully implemented. Over the last few years, several researchers have examined the use of various nanoparticles, from commercial to custom made particles, to formulate drilling fluids with enhanced properties that can withstand extreme downhole environments, particularly at high pressure and high temperature (HP/HT) conditions. This article summarizes the recent progress made on the use of nanoparticles as additives in drilling fluids in order to…

Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly focus on industrial consumers. The ignorance of residential and commercial sectors in DSM activities degrades the overall performance of a conventional grid. Therefore, the concept of DSM and demand response (DR) via residential sector makes the smart grid (SG) superior over the traditional grid. In this context, this paper proposes an optimized home energy management system (OHEMS) that not only facilitates the integration of renewable energy source (RES) and energy storage system (ESS) but also incorporates the residential sector into DSM activities. The proposed OHEMS minimizes the electricity bill by scheduling the household appliances and ESS in response to the dynamic pricing of electricity market. First, the constrained optimization problem is mathematically formulated by using multiple knapsack problems, and then solved by using the heuristic algorithms; genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven optimization (WDO), bacterial foraging…

This paper analyses some possible means by which renewable power could be integrated into the steel manufacturing process, with techniques such as blast furnace gas recirculation (BF-GR), furnaces that utilize carbon capture, a higher share of electrical arc furnaces (EAFs) and the use of direct reduced iron with hydrogen as reduction agent (H-DR). It is demonstrated that these processes could lead to less dependence on—and ultimately complete independence from—coal. This opens the possibility of providing the steel industry with power and heat by coupling to renewable power generation (sector coupling). In this context, it is shown using the example of Germany that with these technologies, reductions of 47–95% of CO2 emissions against 1990 levels and 27–95% of primary energy demand against 2008 can be achieved through the integration of 12–274 TWh of renewable electrical power into the steel industry. Thereby, a substantial contribution to reducing CO2 emissions and fuel demand could be made (although it would fall short of realizing the German government’s target of a 50%…

In recent years, several tools and models have been developed and used for the design and analysis of future national energy systems. Many of these models focus on the integration of various renewable energy resources and the transformation of existing fossil-based energy systems into future sustainable energy systems. The models are diverse and often end up with different results and recommendations. This paper analyses this diversity of models and their implicit or explicit theoretical backgrounds. In particular, two archetypes are defined and compared. On the one hand, the prescriptive investment optimisation or optimal solutions approach. On the other hand the analytical simulation or alternatives assessment approach. Awareness of the dissimilar theoretical assumption behind the models clarifies differences between the models, explains dissimilarities in results, and provides a theoretical and methodological foundation for understanding and interpreting results from the two archetypes.

Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of…

Hydrogen has a very diverse chemistry and reacts with most other elements to form compounds, which have fascinating structures, compositions and properties. Complex metal hydrides are a rapidly expanding class of materials, approaching multi-functionality, in particular within the energy storage field. This review illustrates that complex metal hydrides may store hydrogen in the solid state, act as novel battery materials, both as electrolytes and electrode materials, or store solar heat in a more efficient manner as compared to traditional heat storage materials. Furthermore, it is highlighted how complex metal hydrides may act in an integrated setup with a fuel cell. This review focuses on the unique properties of light element complex metal hydrides mainly based on boron, nitrogen and aluminum, e.g., metal borohydrides and metal alanates. Our hope is that this review can provide new inspiration to solve the great challenge of our time: efficient conversion and large-scale storage of renewable energy.

Performance (availability and yield) and reliability of wind turbines can make the difference between success and failure of wind farm projects and these factors are vital to decrease the cost of energy. During the last years, several initiatives started to gather data on the performance and reliability of wind turbines on- and offshore and published findings in different journals and conferences. Even though the scopes of the different initiatives are similar, every initiative follows a different approach and results are therefore difficult to compare. The present paper faces this issue, collects results of different initiatives and harmonizes the results. A short description and assessment of every considered data source is provided. To enable this comparison, the existing reliability characteristics are mapped to a system structure according to the Reference Designation System for Power Plants (RDS-PP®). The review shows a wide variation in the performance and reliability metrics of the individual initiatives. Especially the comparison on onshore wind turbines reveals significant…

This paper develops a path for the global energy system up to 2050, presenting a new application of the open-source energy modeling system (OSeMOSYS) to the community. It allows quite disaggregate energy and emission analysis: Global Energy System Model (GENeSYS-MOD) uses a system of linear equations of the energy system to search for lowest-cost solutions for a secure energy supply, given externally defined constraints, mainly in terms of CO2-emissions. The general algebraic modeling system (GAMS) version of OSeMOSYS is updated to the newest version and, in addition, extended and enhanced to include e.g., a modal split for transport, an improved trading system, and changes to storages. The model can be scaled from small-scale applications, e.g., a company, to cover the global energy system. The paper also includes an application of GENeSYS-MOD to analyze decarbonization scenarios at the global level, broken down into 10 regions. Its main focus is on interdependencies between traditionally segregated sectors: electricity, transportation, and heating; which are all included in the…

High energy density storage device exhibiting a reliable lifecycle is needed in the 21st century. Hence, energy storage research is critical for reducing energy consumption. Supercapacitors exhibit such characteristics via interfacial ion electrosorption and fast redox reactions. They are a feasible solution for transportation applications, among others, due to their superb characteristics. In this paper, we provide a background on supercapacitors, review public data on commercially available supercapacitors for performance characteristics, and finally summarize their performance in terms of energy density, equivalent series resistance, and device time consistency.

Energy is crucial to economic progress, but the contemporary worldwide population increase that demands greater energy generated from conventional exhaustible resources, an energy price upsurge, and environmental concerns, imperils sustainable economic growth. Nevertheless, switching to renewable energy produced from naturally replenished resources promotes energy security, likewise addressing issues such as global warming and climate change. This paper aims at exploring the influence and causal relation between renewable energy, both overall and by type, and sustainable economic growth of European Union (EU)-28 countries for the period of 2003–2014. We notice that the mean share of renewable energy in the gross final energy consumption is 15%, while the mean share of renewable energy in transport fuel consumption is 3%, which are below the thresholds of 20% and 10%, respectively, as set by the EU Directive 2009/28/EC. By estimating panel data fixed-effects regression models, the results provide support for a positive influence of renewable energy overall, as well as by type, namely…

The growing environmental challenge of electrical energy systems has prompted a substantial increase in renewable energy generation. Such generation systems allow for significant reduction of CO2 emissions compared with a traditional fossil fuel plant. Furthermore, several improvements in power systems network configuration and operation combined with new technologies have enabled reduction of losses and energy demand, thus contributing to reduction of CO2 emissions. Another environmental threat identified in electrical networks is the leaking of insulating sulfur hexafluoride (SF6) gas used in electrical gas insulated substations (GIS) and equipment. Because of its Global Warming Potential (GWP) of nearly 24,000 and its long life in the atmosphere (over 3000 years), SF6 gas was recognized as a greenhouse gas at the 1997 COP3; since then its use and emissions in the atmosphere have been regulated by international treaties. It is expected that as soon as an alternative insulating gas is found, SF6 use in high-voltage (HV) equipment will be banned. This paper presents an overview of…

The usage of renewable energy sources (RESs) to achieve greenhouse gas (GHG) emission reduction goals requires a holistic transformation across all sectors. Due to the fluctuating nature of RESs, it is necessary to install more wind and photovoltaics (PVs) generation in terms of nominal power than would otherwise be required in order to ensure that the power demand can always be met. In a near fully RES-based energy system, there will be times when there is an inadequate conventional load to meet the overcapacity of RESs, which will lead to demand regularly being exceeded and thereby a surplus. One approach to making productive use of this surplus, which would lead to a holistic transformation of all sectors, is “sector coupling” (SC). This paper describes the general principles behind this concept and develops a working definition intended to be of utility to the international scientific community. Furthermore, a literature review provides an overview of relevant scientific papers on the topic. Due to the challenge of distinguishing between papers with or without SC, the approach…

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today’s high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the…

Distributed generation (DG) is one of the key components of the emerging microgrid concept that enables renewable energy integration in a distribution network. In DG unit operation, inverters play a vital role in interfacing energy sources with the grid utility. An effective interfacing can successfully be accomplished by operating inverters with effective control techniques. This paper reviews and categorises different control methods (voltage and primary) for improving microgrid power quality, stability and power sharing approaches. In addition, the specific characteristics of microgrids are summarised to distinguish from distribution network control. Moreover, various control approaches including inner-loop controls and primary controls are compared according to their relative advantages and disadvantages. Finally, future research trends for microgrid control are discussed pointing out the research opportunities. This review paper will be a good basis for researchers working in microgrids and for industry to implement the ongoing research improvement in real systems.

Solid char is a product of biomass pyrolysis. It contains a high proportion of carbon, and lower contents of H, O and minerals. This char can have different valorization pathways such as combustion for heat and power, gasification for Syngas production, activation for adsorption applications, or use as a soil amendment. The optimal recovery pathway of the char depends highly on its physical and chemical characteristics. In this study, different chars were prepared from beech wood particles under various pyrolysis operating conditions in an entrained flow reactor (500–1400 °C). Their structural, morphological, surface chemistry properties, as well as their chemical compositions, were determined using different analytical techniques, including elementary analysis, Scanning Electronic Microscopy (SEM) coupled with an energy dispersive X-ray spectrometer (EDX), Fourier Transform Infra-Red spectroscopy (FTIR), and Raman Spectroscopy. The biomass char reactivity was evaluated in air using thermogravimetric analysis (TGA). The yield, chemical composition, surface chemistry, structure,…

Energy harvesting has been attracting attention as a technology that is capable of replacing or supplementing a battery with the development of various mobile electronics. In environments where stable electrical supply is not possible, energy harvesting technology can guarantee an increased leisure and safety for human beings. Harvesting with several watts of power is essential for directly driving or efficiently charging mobile electronic devices such as laptops or cell phones. In this study, we reviewed energy harvesting technologies that harvest biomechanical energy from human motion such as foot strike, joint motion, and upper limb motion. They are classified based on the typical principle of kinetic energy harvesting: piezoelectric, triboelectric, and electromagnetic energy harvesting. We focused on the wearing position of high-power wearable biomechanical energy harvesters (WBEHs) generating watt-level power. In addition, the features and future trends of the watt-level WBEHs are discussed.

The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement maximum power point tracking controllers (MPPT) to obtain the maximum power of a PV system regardless of variations in climatic conditions. The traditional solution for MPPT controllers is the perturbation and observation (P&O) algorithm, which presents oscillation problems around the operating point; the reason why improving the results obtained with this algorithm has become an important goal to reach for researchers. This paper presents the design and modeling of a fuzzy controller for tracking the maximum power point of a PV System. Matlab/Simulink (MathWorks, Natick, MA, USA) was used for the modeling of the components of a 65 W PV system: PV module, buck converter and fuzzy controller; highlighting as main novelty the use of a mathematical model for the PV module, which, unlike diode based models, only needs to calculate the curve fitting parameter. A P&O controller to compare the results obtained with the fuzzy control was…

Motivated by recent developments in batch Reinforcement Learning (RL), this paper contributes to the application of batch RL in energy management in microgrids. We tackle the challenge of finding a closed-loop control policy to optimally schedule the operation of a storage device, in order to maximize self-consumption of local photovoltaic production in a microgrid. In this work, the fitted Q-iteration algorithm, a standard batch RL technique, is used by an RL agent to construct a control policy. The proposed method is data-driven and uses a state-action value function to find an optimal scheduling plan for a battery. The battery’s charge and discharge efficiencies, and the nonlinearity in the microgrid due to the inverter’s efficiency are taken into account. The proposed approach has been tested by simulation in a residential setting using data from Belgian residential consumers. The developed framework is benchmarked with a model-based technique, and the simulation results show a performance gap of 19%. The simulation results provide insight for developing optimal policies in more…

The paper presents a decision-making algorithm that has been developed for the optimum size and placement of distributed generation (DG) units in distribution networks. The algorithm that is very flexible to changes and modifications can define the optimal location for a DG unit (of any type) and can estimate the optimum DG size to be installed, based on the improvement of voltage profiles and the reduction of the network’s total real and reactive power losses. The proposed algorithm has been tested on the IEEE 33-bus radial distribution system. The obtained results are compared with those of earlier studies, proving that the decision-making algorithm is working well with an acceptable accuracy. The algorithm can assist engineers, electric utilities, and distribution network operators with more efficient integration of new DG units in the current distribution networks.

With ever-increasing concerns for the safety and convenience of the power supply, there is a fast growing interest in wireless power transfer (WPT) for industrial devices, consumer electronics, and electric vehicles (EVs). As the resonant circuit is one of the cores of both the near-field and far-field WPT systems, it is a pressing need for researchers to develop a high-efficiency high-frequency resonant circuit, especially for the mid-range near-field WPT system. In this paper, an overview of resonant circuits for the near-field WPT system is presented, with emphasis on the non-resonant converters with a resonant tank and resonant inverters with a resonant tank as well as compensation networks and selective resonant circuits. Moreover, some key issues including the zero-voltage switching, zero-voltage derivative switching and total harmonic distortion are addressed. With the increasing usage of wireless charging for EVs, bidirectional resonant inverters for WPT based vehicle-to-grid systems are elaborated.

Mathematical analysis is an essential tool for the successful development and operation of wave energy converters (WECs). Mathematical models of moorings systems are therefore a requisite in the overall techno-economic design and operation of floating WECs. Mooring models (MMs) can be applied to a range of areas, such as WEC simulation, performance evaluation and optimisation, control design and implementation, extreme load calculation, mooring line fatigue life evaluation, mooring design, and array layout optimisation. The mathematical modelling of mooring systems is a venture from physics to numerics, and as such, there are a broad range of details to consider when applying MMs to WEC analysis. A large body of work exists on MMs, developed within other related ocean engineering fields, due to the common requirement of mooring floating bodies, such as vessels and offshore oil and gas platforms. This paper reviews the mathematical modelling of the mooring systems for WECs, detailing the relevant material developed in other offshore industries and presenting the published usage of…

The monitoring and prognosis of cell degradation in lithium-ion (Li-ion) batteries are essential for assuring the reliability and safety of electric and hybrid vehicles. This paper aims to develop a reliable and accurate model for online, simultaneous state-of-charge (SOC) and state-of-health (SOH) estimations of Li-ion batteries. Through the analysis of battery cycle-life test data, the instantaneous discharging voltage (V) and its unit time voltage drop, V′, are proposed as the model parameters for the SOC equation. The SOH equation is found to have a linear relationship with 1/V′ times the modification factor, which is a function of SOC. Four batteries are tested in the laboratory, and the data are regressed for the model coefficients. The results show that the model built upon the data from one single cell is able to estimate the SOC and SOH of the three other cells within a 5% error bound. The derived model is also proven to be robust. A random sampling test to simulate the online real-time SOC and SOH estimation proves that this model is accurate and can be potentially used in…

The Organic Rankine Cycle (ORC) is widely considered as a promising technology to produce electrical power output from low-grade thermal sources. In the last decade, several power plants have been installed worldwide in the MW range. However, despite its market potential, the commercialization of ORC power plants in the kW range did not reach a high level of maturity, for several reasons. Firstly, the specific price is still too high to offer an attractive payback period, and secondly, potential costumers for small-scale ORCs are typically SMEs (Small-Medium Enterprises), generally less aware of the potential savings this technology could lead to. When it comes to small-scale plants, additional design issues arise that still limit the widespread availability of the technology. This review paper presents the state of the art of the technology, from a technical and economic perspective. Working fluid selection and expander design are illustrated in detail, as they represent the bottleneck of the ORC technology for small-scale power production. In addition, a European market analysis…

In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA), the binary particle swarm optimization (BPSO) algorithm, the bacterial foraging optimization algorithm (BFOA), the wind-driven optimization (WDO) algorithm and our proposed hybrid genetic wind-driven (GWD) algorithm) are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs) and off-peak hours (OPHs) in a real-time pricing (RTP) environment while maximizing user comfort (UC) and minimizing both electricity cost and the peak to average ratio (PAR). Moreover, these algorithms are tested in two scenarios: (i) scheduling the load of a single home and (ii) scheduling the load of multiple homes. Simulation results show that our…

Lithium Sulfur (Li-S) battery is generally considered as a promising technology where high energy density is required at different applications. Over the past decade, there has been an ever increasing volume of Li-S academic research spanning materials development, fundamental understanding and modelling, and application-based control algorithm development. In this study, the Li-S battery technology, its advantages and limitations from the fundamental perspective are firstly discussed. In the second part of this study, state-of-the-art Li-S cell modelling and state estimation techniques are reviewed with a focus on practical applications. The existing studies on Li-S cell equivalent-circuit-network modelling and state estimation techniques are then discussed. A number of challenges in control of Li-S battery are also explained such as the flat open-circuit-voltage curve and high sensitivity of Li-S cell’s behavior to temperature variation. In the last part of this study, current and future applications of Li-S battery are mentioned.

Current harmonics is one of the most significant power quality issues which has attracted tremendous research interest. Shunt active power filter (SAPF) is the best solution to minimize harmonic contamination, but its effectiveness is strictly dependent on how quickly and accurately its control algorithms can perform. This manuscript reviews various types of existing control algorithms which have been employed for controlling operation of SAPF. Harmonic extraction, DC-link capacitor voltage regulation, current control and synchronizer algorithms are examined and discussed. The most relevant techniques which have been applied for each control algorithm are described and contrasted in an organized manner to identify their respective strengths and weaknesses. It is found that the applied control algorithms differ in two conditions: (1) the condition where harmonic current distortion is treated by the SAPF in the presence of non-ideal source voltage; and (2) the condition where multilevel inverter is employed as the circuit topology of SAPF.

The installed capacity of distributed generation (DG) based on renewable energy sources has increased continuously in power systems, and its market-oriented transaction is imperative. However, traditional transaction management based on centralized organizations has many disadvantages, such as high operation cost, low transparency, and potential risk of transaction data modification. Therefore, a decentralized electricity transaction mode for microgrids is proposed in this study based on blockchain and continuous double auction (CDA) mechanism. A buyer and seller initially complete the transaction matching in the CDA market. In view of the frequent price fluctuation in the CDA market, an adaptive aggressiveness strategy is used to adjust the quotation timely according to market changes. DG and consumer exchange digital certificate of power and expenditure on the blockchain system and the interests of consumers are then guaranteed by multi-signature when DG cannot generate power due to failure or other reasons. The digital certification of electricity assets is replaced by the…

Power-to-gas is a promising option for storing interment renewables, nuclear baseload power, and distributed energy and it is a novel concept for the transition to increased renewable content of current fuels with an ultimate goal of transition to a sustainable low-carbon future energy system that interconnects power, transportation sectors and thermal energy demand all together. The aim of this paper is to introduce different Power-to-gas “pathways”, including Power to Hydrogen, Power to Natural Gas End-users, Power to Renewable Content in Petroleum Fuel, Power to Power, Seasonal Energy Storage to Electricity, Power to Zero Emission Transportation, Power to Seasonal Storage for Transportation, Power to Micro grid, Power to Renewable Natural Gas (RNG) to Pipeline (“Methanation”), and Power to Renewable Natural Gas (RNG) to Seasonal Storage. In order to compare the different pathways, the review of key technologies of Power-to-gas systems are studied and the qualitative efficiency and benefits of each pathway is investigated from the technical points of view. Moreover, different…

GaN-based transistors with p-GaN gate are commonly accepted as promising devices for application in power converters, thanks to the positive and stable threshold voltage, the low on-resistance and the high breakdown field. This paper reviews the most recent results on the technology and reliability of these devices by presenting original data. The first part of the paper describes the technological issues related to the development of a p-GaN gate, and the most promising solutions for minimizing the gate leakage current. In the second part of the paper, we describe the most relevant mechanisms that limit the dynamic performance and the reliability of GaN-based normally-off transistors. More specifically, we discuss the following aspects: (i) the trapping effects specific for the p-GaN gate; (ii) the time-dependent breakdown of the p-GaN gate during positive gate stress and the related physics of failure; (iii) the stability of the electrical parameters during operation at high drain voltages. The results presented within this paper provide information on the current status of the…

After a brief historical introduction to the hosting-capacity approach, the hosting capacity is presented in this paper as a tool for distribution-system planning under uncertainty. This tool is illustrated by evaluating the readiness of two low-voltage networks for increasing amounts of customers with PV panels or with EV chargers. Both undervoltage and overvoltage are considered in the studies presented here. Probability distribution functions are calculated for the worst-case overvoltage and undervoltage as a function of the number of customers with PV or EV chargers. These distributions are used to obtain 90th percentile values that act as a performance index. This index is compared with an overvoltage or undervoltage limit to get the hosting capacity. General aspects of the hosting-capacity calculations (performance indices, limits, and calculation methods) are discussed for a number of other phenomena: overcurrent; fast voltage magnitude variations; voltage unbalance; harmonics and supraharmonics. The need for gathering data and further development of models for existing…

In this study, large-eddy simulations are performed to investigate the flow inside and around large finite-size wind farms in conventionally-neutral atmospheric boundary layers. Special emphasis is placed on characterizing the different farm-induced flow regions, including the induction, entrance and development, fully-developed, exit and farm wake regions. The wind farms extend 20 km in the streamwise direction and comprise 36 wind turbine rows arranged in aligned and staggered configurations. Results show that, under weak free-atmosphere stratification ( Γ = 1 K/km), the flow inside and above both wind farms, and thus the turbine power, do not reach the fully-developed regime even though the farm length is two orders of magnitude larger than the boundary layer height. In that case, the wind farm induction region, affected by flow blockage, extends upwind about 0.8 km and leads to a power reduction of 1.3% and 3% at the first row of turbines for the aligned and staggered layouts, respectively. The wind farm wake leads to velocity deficits at hub height of around 3.5% at a downwind…

Limited driving range remains one of the barriers for widespread adoption of electric vehicles (EVs). To address the problem of range anxiety, this paper presents an energy consumption prediction method for EVs, designed for energy-efficient routing. This data-driven methodology combines real-world measured driving data with geographical and weather data to predict the consumption over any given road in a road network. The driving data are linked to the road network using geographic information system software that allows to separate trips into segments with similar road characteristics. The energy consumption over road segments is estimated using a multiple linear regression (MLR) model that links the energy consumption with microscopic driving parameters (such as speed and acceleration) and external parameters (such as temperature). A neural network (NN) is used to predict the unknown microscopic driving parameters over a segment prior to departure, given the road segment characteristics and weather conditions. The complete proposed model predicts the energy consumption with a…

Energy efficiency represents a key resource for economic and social development, providing substantial benefits to different stakeholders, ranging from the entities which develop energy efficient measures to everyone in society. In addition to cost savings, multiple benefits can be achieved by supporting a better alignment between energy issues and strategic business priorities: e.g., improved competitiveness, profitability, quality, etc. Thus, energy efficiency can be a strategic advantage, not just a marginal issue, for companies. However, most firms, especially small and medium enterprises (SMEs), face many problems and, in some cases, hostility when trying to effectively implement energy efficiency actions. The most dominant barriers are the access to capital and the lack of awareness (especially in terms of life cycle cost effects). The supply chain viewpoint represents one of the main opportunities for overcoming those barriers and improving energy performance even for weaker companies. Since the current literature on energy efficiency and practical approaches to ensure energy…

Glycerol is a by-product of biodiesel obtained from biomass, accounting for 10% of the biodiesel production. In the context of a green economy, aiming for a reduction of the emission of atmospheric greenhouse gases emissions, the demand of biodiesel is expected to increase vastly, in parallel with a side glut supply of glycerol. Given the high cost of biodiesel compared with its fossil congener, upgrading of glycerol into added-value products can represent a secondary income source and turn the production of such alternative fuels economically sustainable in the long term. The glycerol obtained as by-product of biodiesel from biomass is in a crude form and must be purified. Some industrial solutions and applications were therein geared. The survey presented in this work, based on a reviewing of the existing literature, examines three routes for the valuing glycerol into energy carriers and chemicals, namely, carbonation, acylation, and steam reforming to hydrogen. The latter is embodied of great interest and importance, insofar that hydrogen by itself is considered as straighforward…

This study was aimed to define a methodology based on existing literature and evaluate the levelized cost of hydrogen (LCOH) for a decentralized hydrogen refueling station (HRS) in Halle, Belgium. The results are based on a comprehensive data collection, along with real cost information. The main results indicated that a LCOH of 10.3 €/kg at the HRS can be reached over a lifetime of 20 years, if an average electricity cost of 0.04 €/kWh could be achieved and if the operating hours are maximized. Furthermore, if the initial capital costs can be reduced by 80%, in the case of direct subsidy, the LCOH could even fall to 6.7 €/kg.

Accurate modeling of the nonlinear relationship between the open circuit voltage (OCV) and the state of charge (SOC) is required for adaptive SOC estimation during the lithium-ion (Li-ion) battery operation. Online SOC estimation should meet several constraints, such as the computational cost, the number of parameters, as well as the accuracy of the model. In this paper, these challenges are considered by proposing an improved simplified and accurate OCV model of a nickel manganese cobalt (NMC) Li-ion battery, based on an empirical analytical characterization approach. In fact, composed of double exponential and simple quadratic functions containing only five parameters, the proposed model accurately follows the experimental curve with a minor fitting error of 1 mV. The model is also valid at a wide temperature range and takes into account the voltage hysteresis of the OCV. Using this model in SOC estimation by the extended Kalman filter (EKF) contributes to minimizing the execution time and to reducing the SOC estimation error to only 3% compared to other existing models where the…

Buildings are the focus of European (EU) policies aimed at a sustainable and competitive low-carbon economy by 2020. Reducing energy consumption of existing buildings and achieving nearly zero energy buildings (NZEBs) are the core of the Energy Efficiency Directive (EED) and the recast of the Energy Performance of Building Directive (EPBD). To comply with these requirements, Member States have to adopt actions to exploit energy savings from the building sector. This paper describes the differences between deep, major and NZEB renovation and then it provides an overview of best practice policies and measures to target retrofit and investment related to non-residential buildings. Energy requirements defined by Member States for NZEB levels are reported comparing both new and existing residential and non-residential buildings. The paper shows how the attention given to refurbishment of NZEBs increased over the last decade, but the achievement of a comprehensive implementation of retrofit remains one of main challenges that Europe is facing.

Generation of electric energy through wind turbines is one of the practically inexhaustible alternatives of generation. It is considered a source of clean energy, but still needs a lot of research for the development of science and technologies that ensures uniformity in generation, providing a greater participation of this source in the energy matrix, since the wind presents abrupt variations in speed, density and other important variables. In wind-based electrical systems, it is essential to predict at least one day in advance the future values of wind behavior, in order to evaluate the availability of energy for the next period, which is relevant information in the dispatch of the generating units and in the control of the electrical system. This paper develops ultra-short, short, medium and long-term prediction models of wind speed, based on computational intelligence techniques, using artificial neural network models, Autoregressive Integrated Moving Average (ARIMA) and hybrid models including forecasting using wavelets. For the application of the methodology, the…

In this work, an extended overview of the marine renewable energy in the Mediterranean Sea is provided as regards current status, potential problems, challenges, and perspectives of development. An integrated and holistic approach is necessary for the economic viability and sustainability of marine renewable energy projects; this approach comprises three different frameworks, not always aligned, i.e., geotechnical/engineering, socio-economic, and environmental/ecological frameworks. In this context, the geomorphological, climatological, socio-economic, and environmental/ecological particularities of the Mediterranean basin are discussed, as they constitute key issues of the spatial context in which marine renewable energy projects are to be implemented. General guidelines for the sustainable development of marine renewable energy in the Mediterranean are also provided.

Industry 4.0 and its impact in the manufacturing sector are well documented. However, the service sector is understudied, and it is also facing the challenges of mass customization, digital enhancement, smart work environment, and efficient supply chain. The aim of this study is to fill this research gap by exploring the issues of Industry 4.0 in the service sector, with cases in the hospitality industry. All the challenges of Industry 4.0 require continuous innovation and learning, which is dependent on people and the enterprise’s capabilities. Appropriate management approaches can play a vital role in the development of dynamic capabilities, and an effective learning and innovation environment. This paper proposes a framework of management practices which can promote the environment of innovation and learning in an organization, and hence facilitate business to match the pace of Industry 4.0 by facilitating technology acceptance e.g., digital enhancements and implementation of cyber physical systems (CPS). This study integrates the literature with logical beliefs to suggest the…

Nowadays, battery storage systems are very important in both stationary and mobile applications. In particular, lithium ion batteries are a good and promising solution because of their high power and energy densities. The modeling of these devices is very crucial to correctly predict their state of charge (SoC) and state of health (SoH). The literature shows that numerous battery models and parameters estimation techniques have been developed and proposed. Moreover, surveys on their electric, thermal, and aging modeling are also reported. This paper presents a more complete overview of the different proposed battery models and estimation techniques. In particular, a method for classifying the proposed models based on their approaches is proposed. For this classification, the models are divided in three categories: mathematical models, physical models, and circuit models.

“Linking the power and transport sectors—Part 1” describes the general principle of “sector coupling” (SC), develops a working definition intended of the concept to be of utility to the international scientific community, contains a literature review that provides an overview of relevant scientific papers on this topic and conducts a rudimentary analysis of the linking of the power and transport sectors on a worldwide, EU and German level. The aim of this follow-on paper is to outline an approach to the modelling of SC. Therefore, a study of Germany as a case study was conducted. This study assumes a high share of renewable energy sources (RES) contributing to the grid and significant proportion of fuel cell vehicles (FCVs) in the year 2050, along with a dedicated hydrogen pipeline grid to meet hydrogen demand. To construct a model of this nature, the model environment “METIS” (models for energy transformation and integration systems) we developed will be described in more detail in this paper. Within this framework, a detailed model of the power and transport sector in Germany will…

This paper provides a comprehensive review of the major concepts associated with the μgrid, such as constant power load (CPL), incremental negative resistance or impedance (INR/I) and its dynamic behaviours on the μgrid, and power system distribution (PSD). In general, a μgrid is defined as a cluster of different types of electrical loads and renewable energy sources (distributed generations) under a unified controller within a certain local area. It is considered a perfect solution to integrate renewable energy sources with loads as well as with a traditional grid. In addition, it can operate with a conventional grid, for example, by energy sourcing or a controllable load, or it can operate alone as an islanding mode to feed required electric energy to a grid. Hence, one of the important issues regarding the μgrid is the constant power load that results from the tightly designed control when it is applied to power electronic converters. The effect of CPL is incremental negative resistance that impacts the power quality of a power system and makes it at negative damping. Also, in…

Buildings consume approximately ¾ of the total electricity generated in the United States, contributing significantly to fossil fuel emissions. Sustainable and renewable energy production can reduce fossil fuel use, but necessitates storage for energy reliability in order to compensate for the intermittency of renewable energy generation. Energy storage is critical for success in developing a sustainable energy grid because it facilitates higher renewable energy penetration by mitigating the gap between energy generation and demand. This review analyzes recent case studies—numerical and field experiments—seen by borehole thermal energy storage (BTES) in space heating and domestic hot water capacities, coupled with solar thermal energy. System design, model development, and working principle(s) are the primary focus of this analysis. A synopsis of the current efforts to effectively model BTES is presented as well. The literature review reveals that: (1) energy storage is most effective when diurnal and seasonal storage are used in conjunction; (2) no established link exists between…

Batteries are promising storage technologies for stationary applications because of their maturity, and the ease with which they are designed and installed compared to other technologies. However, they pose threats to the environment and human health. Several studies have discussed the various battery technologies and applications, but evaluating the environmental impact of batteries in electrical systems remains a gap that requires concerted research efforts. This study first presents an overview of batteries and compares their technical properties such as the cycle life, power and energy densities, efficiencies and the costs. It proposes an optimal battery technology sizing and selection strategy, and then assesses the environmental impact of batteries in a typical renewable energy application by using a stand-alone photovoltaic (PV) system as a case study. The greenhouse gas (GHG) impact of the batteries is evaluated based on the life cycle emission rate parameter. Results reveal that the battery has a significant impact in the energy system, with a GHG impact of about 36–68% in…

Gob-side entry retaining (GER) is a popular non-pillar mining technique regarding how to reserve a gateroad for the use of next panel mining. When used in thick coal seams, the conventional entry retaining method requires a huge amount of filling materials and may cause entry (gateroad) accidents. Thus, an innovative non-pillar longwall mining approach is introduced. First, structural and mechanical models were built to explore the mechanism of the new approach. The modeling results indicate that effective bulking of the gob roof and reasonable support of the entry roof were key governing factors in improving entry stabilities and reducing roof deformations. Accordingly, a directional roof fracturing technique was proposed to contribute to gob roof caving, and a constant resistance and large deformation anchor (CRLDA) cable was used to stabilize the entry roof. Subsequently, the evolutionary laws of the roof structure and stresses were explored using numerical simulation. It was found that the structure of the surrounding rocks around the retained entry changed significantly after…

Energy efficiency is an important factor in the marine industry to help reduce manufacturing and operational costs as well as the impact on the environment. In the face of global competition and cost-effectiveness, ship builders and operators today require a major overhaul in the entire ship design, manufacturing and operation process to achieve these goals. This paper highlights smart design, manufacturing and operation as the way forward in an industry 4.0 (i4) era from designing for better energy efficiency to more intelligent ships and smart operation through-life. The paper (i) draws parallels between ship design, manufacturing and operation processes, (ii) identifies key challenges facing such a temporal (lifecycle) as opposed to spatial (mass) products, (iii) proposes a closed-loop ship lifecycle framework and (iv) outlines potential future directions in smart design, manufacturing and operation of ships in an industry 4.0 value chain so as to achieve more energy-efficient vessels. Through computational intelligence and cyber-physical integration, we envision that industry…

Industrial hydrogen production via alkaline water electrolysis (AEL) is a mature hydrogen production method. One argument in favor of AEL when supplied with renewable energy is its environmental superiority against conventional fossil-based hydrogen production. However, today electricity from the national grid is widely utilized for industrial applications of AEL. Also, the ban on asbestos membranes led to a change in performance patterns, making a detailed assessment necessary. This study presents a comparative Life Cycle Assessment (LCA) using the GaBi software (version 6.115, thinkstep, Leinfelden-Echterdingen, Germany), revealing inventory data and environmental impacts for industrial hydrogen production by latest AELs (6 MW, Zirfon membranes) in three different countries (Austria, Germany and Spain) with corresponding grid mixes. The results confirm the dependence of most environmental effects from the operation phase and specifically the site-dependent electricity mix. Construction of system components and the replacement of cell stacks make a minor contribution. At present,…

During the last decades, standards on building construction have risen sharply to integrate new, ambitious demands regarding energy efficiency, as well as thermal and optical comfort in the design procedure. Building simulation software assists in the accurate calculation of a hypothetical or existing building’s performance on several aspects; but they are, in their vast majority, assessment-oriented, rather than focused on dynamically supporting the decision-making procedure. During the last two decades, a clear shift of design professionals and academia towards addressing performance issues from the conceptual stages of a building’s design is observed. In this review, the methodology of performance-driven design optimization using computational/parametric design and optimization is presented, and the core literature available on the topic is reviewed in order to identify the current status, different approaches, obstacles, and areas of future research on the subject. The review findings confirm that there is enormous potential for the design of better-performing buildings using…

The fast-growing wind power industry faces the challenge of reducing operation and maintenance (O&M) costs for wind power plants. Predictive maintenance is essential to improve wind turbine reliability and prolong operation time, thereby reducing the O&M cost for wind power plants. This study presents a solution for predictive maintenance of wind turbine generators. The proposed solution can: (1) predict the remaining useful life (RUL) of wind turbine generators before a fault occurs and (2) diagnose the state of the wind turbine generator when the fault occurs. Moreover, the proposed solution implies low-deployment costs because it relies solely on the information collected from the widely available supervisory control and data acquisition (SCADA) system. Extra sensing hardware is needless. The proposed solution has been deployed and evaluated in two real-world wind power plants located in China. The experimental study demonstrates that the RUL of the generators can be predicted 18 days ahead with about an 80% prediction accuracy. When faults occur, the specific type of generator…

Inaccurate forecasting of photovoltaic (PV) power generation is a great concern in the planning and operation of stable and reliable electric grid systems as well as in promoting large-scale PV deployment. The paper proposes a generalized PV power forecasting model based on support vector regression, historical PV power output, and corresponding meteorological data. Weather conditions are broadly classified into two categories, namely, normal condition (clear sky) and abnormal condition (rainy or cloudy day). A generalized day-ahead forecasting model is developed to forecast PV power generation at any weather condition in a particular region. The proposed model is applied and experimentally validated by three different types of PV stations in the same location at different weather conditions. Furthermore, a conventional artificial neural network (ANN)-based forecasting model is utilized, using the same experimental data-sets of the proposed model. The analytical results showed that the proposed model achieved better forecasting accuracy with less computational complexity when…

Nuclear power has been questioned almost since its beginnings and one of the major issues concerning its social acceptability around the world is nuclear waste management. In recent years, these issues have led to a rise in public opposition in some countries and, thus, nuclear energy has been facing even more challenges. However, continuous efforts in R&D (research and development) are resulting in new spent nuclear fuel (SNF) management technologies that might be the pathway towards helping the environment and the sustainability of nuclear energy. Thus, reprocessing and recycling of SNF could be one of the key points to improve the social acceptability of nuclear energy. Therefore, the purpose of this paper is to review the state of the nuclear waste management technologies, its evolution through time and the future advanced techniques that are currently under research, in order to obtain a global vision of the nuclear fuel cycle strategies available, their advantages and disadvantages, and their expected evolution in the future.

Rotary-wing unmanned aerial vehicles (UAVs) have the ability to operate in confined spaces and to hover over point of interest, but they have limited flight time and endurance. Conventional contact-based charging system for UAVs has been used, but it requires high landing accuracy for proper docking. Instead of the conventional system, autonomous wireless battery charging system for UAVs in outdoor conditions is proposed in this paper. UAVs can be wirelessly charged using the proposed charging system, regardless of yaw angle between UAVs and wireless charging pad, which can further reduce their control complexity for autonomous landing. The increased overall mission time eventually relaxes the limitations on payload and flight time. In this paper, a cost effective automatic recharging solution for UAVs in outdoor environments is proposed using wireless power transfer (WPT). This research proposes a global positioning system (GPS) and vision-based closed-loop target detection and a tracking system for precise landing of quadcopters in outdoor environments. The system uses the onboard…

Softwoods represent a significant fraction of the available lignocellulosic biomass for conversion into a variety of bio-based products. Its inherent recalcitrance, however, makes its successful utilization an ongoing challenge. In the current work the research efforts for the fractionation and utilization of softwood biomass with the organosolv process are reviewed. A short introduction into the specific challenges of softwood utilization, the development of the biorefinery concept, as well as the initial efforts for the development of organosolv as a pulping method is also provided for better understanding of the related research framework. The effect of organosolv pretreatment at various conditions, in the fractionation efficiency of wood components, enzymatic hydrolysis and bioethanol production yields is then discussed. Specific attention is given in the effect of the pretreated biomass properties such as residual lignin on enzymatic hydrolysis. Finally, the valorization of organosolv lignin via the production of biofuels, chemicals, and materials is also described.

Active shading systems in buildings have emerged as a high performing shading solution that selectively and optimally controls daylight and heat gains. Active shading systems are increasingly used in buildings, due to their ability to mainly improve the building environment, reduce energy consumption and in some cases generate energy. They may be categorized into three classes: smart glazing, kinetic shading and integrated renewable energy shading. This paper reviews the current status of the different types in terms of design principle and working mechanism of the systems, performance, control strategies and building applications. Challenges, limitations and future opportunities of the systems are then discussed. The review highlights that despite its high initial cost, the electrochromic (EC) glazing is the most applied smart glazing due to the extensive use of glass in buildings under all climatic conditions. In terms of external shadings, the rotating shading type is the predominantly used one in buildings due to its low initial cost. Algae façades and folding shading systems…

The use of heavy-duty battery electric trucks for long-haul transportation is challenging because of the required high energy amounts and thus the high capacity of traction batteries. Furthermore a high capacity battery implies high initial costs for the electric vehicle. This study investigates the required battery capacity for battery electric trucks considering the requirements of long-haul transportation in Germany and compares the life cycle costs of battery electric trucks and conventional diesel trucks in different transportation scenarios. The average consumption is simulated for different battery electric truck configurations on the main German highways and transportation scenarios incorporating battery charging during driver rest periods. The results show that in average case the required battery would restrict the payload to only 80% of a usual diesel truck payload that might be acceptable considering the statistical payload use. The life cycle costs in the examined scenarios also considering the charging infrastructure show that battery electric trucks can already…

The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load…

The Smart Meter (SM) is an essential tool for successful balancing the demand-offer energy curve. It allows the linking of the consumption and production measurements with the time information and the customer’s identity, enabling the substitution of flat-price billing with smarter solutions, such as Time-of-Use or Real-Time Pricing. In addition to sending data to the energy operators for billing and monitoring purposes, Smart Meters must be able to send the same data to customer devices in near-real-time conditions, enabling new services such as instant energy awareness and home automation. In this article, we review the ongoing situation in Europe regarding real-time services for the final customers. Then, we review the architectural and technological options that have been considered for the roll-out phase of the Italian second generation of Smart Meters. Finally, we identify a collection of use cases, along with their functional and performance requirements, and discuss what architectures and communications technologies can meet these requirements.

Waste residues produced by agricultural and forestry industries can generate energy and are regarded as a promising source of sustainable fuels. Pyrolysis, where waste biomass is heated under low-oxygen conditions, has recently attracted attention as a means to add value to these residues. The material is carbonized and yields a solid product known as biochar. In this study, eight types of biomass were evaluated for their suitability as raw material to produce biochar. Material was pyrolyzed at either 350 °C or 500 °C and changes in ash content, volatile solids, fixed carbon, higher heating value (HHV) and yield were assessed. For pyrolysis at 350 °C, significant correlations (p < 0.01) between the biochars’ ash and fixed carbon content and their HHVs were observed. Masson pine wood and Chinese fir wood biochars pyrolyzed at 350 °C and the bamboo sawdust biochar pyrolyzed at 500 °C were suitable for direct use in fuel applications, as reflected by their higher HHVs, higher energy density, greater fixed carbon and lower ash contents. Rice straw was a poor substrate as the resultant…

Transaction-based energy (TE) management and control has become an increasingly relevant topic, attracting considerable attention from industry and the research community alike. As a result, new techniques are emerging for its development and actualization. This paper presents a comprehensive review of TE involving peer-to-peer (P2P) energy trading and also covering the concept, enabling technologies, frameworks, active research efforts and the prospects of TE. The formulation of a common approach for TE management modelling is challenging given the diversity of circumstances of prosumers in terms of capacity, profiles and objectives. This has resulted in divergent opinions in the literature. The idea of this paper is therefore to explore these viewpoints and provide some perspectives on this burgeoning topic on P2P TE systems. This study identified that most of the techniques in the literature exclusively formulate energy trade problems as a game, an optimization problem or a variational inequality problem. It was also observed that none of the existing works has considered a…

The paper presents a detailed review of the state-of-the-art research activities on structural reliability analysis of wind turbines between the 1990s and 2017. We describe the reliability methods including the first- and second-order reliability methods and the simulation reliability methods and show the procedure for and application areas of structural reliability analysis of wind turbines. Further, we critically review the various structural reliability studies on rotor blades, bottom-fixed support structures, floating systems and mechanical and electrical components. Finally, future applications of structural reliability methods to wind turbine designs are discussed.

A variety of reasons, specifically contact issues, irregular loads, cracks in insulation, defective relays, terminal junctions and other similar issues, increase the internal temperature of electrical instruments. This results in unexpected disturbances and potential damage to power equipment. Therefore, the initial prevention measures of thermal anomalies in electrical tools are essential to prevent power-equipment failure. In this article, we address this initial prevention mechanism for power substations using a computer-vision approach by taking advantage of infrared thermal images. The thermal images are taken through infrared cameras without disturbing the working operations of power substations. Thus, this article augments the non-destructive approach to defect analysis in electrical power equipment using computer vision and machine learning. We use a total of 150 thermal pictures of different electrical equipment in 10 different substations in operating conditions, using 300 different hotspots. Our approach uses multi-layered perceptron (MLP) to classify the thermal…

This paper presents a literature review on urban design indicators addressing the impact of urban geometry and vegetation on the outdoor thermal environment at the pedestrian level, as urban geometry and vegetation have been regarded as the most influential urban design factors that affect outdoor microclimate. The thermal balance concept is first introduced to elaborate how each component of energy fluxes is affected by the urban built environment, which helps to explore the underlying thermophysical mechanisms of how urban design modifies the outdoor thermal environment. The literature on numerous urban design descriptors addressing urban geometric characteristics is categorized into five groups in this paper according to the design features that the parameters entail, including land use intensity, building form, canyon geometry, space enclosure and descriptive characteristics. The literature on urban vegetation descriptors is reviewed together, followed by the combined effect of urban geometry and vegetation. This paper identifies a series of important urban design parameters and…

State of charge (SOC) estimation is the core of any battery management system. Most closed-loop SOC estimation algorithms are based on the equivalent circuit model with fixed parameters. However, the parameters of the equivalent circuit model will change as temperature or SOC changes, resulting in reduced SOC estimation accuracy. In this paper, two SOC estimation algorithms with online parameter identification are proposed to solve this problem based on forgetting factor recursive least squares (FFRLS) and nonlinear Kalman filter. The parameters of a Thevenin model are constantly updated by FFRLS. The nonlinear Kalman filter is used to perform the recursive operation to estimate SOC. Experiments in variable temperature environments verify the effectiveness of the proposed algorithms. A combination of four driving cycles is loaded on lithium-ion batteries to test the adaptability of the approaches to different working conditions. Under certain conditions, the average error of the SOC estimation dropped from 5.6% to 1.1% after adding the online parameters identification, showing that…

Gear pumps represent the majority of the fixed displacement machines used for flow generation in fluid power systems. In this context, the paper presents a review of the different methodologies used in the last years for the simulation of the flow rates generated by gerotor, external gear and crescent pumps. As far as the lumped parameter models are concerned, different ways of selecting the control volumes into which the pump is split are analyzed and the main governing equations are presented. The principles and the applications of distributed models from 1D to 3D are reported. A specific section is dedicated to the methods for the evaluation of the necessary geometric quantities: analytic, numerical and Computer-Aided Design (CAD)-based. The more recent studies taking into account the influence on leakages of the interactions between the fluid and the mechanical parts are explained. Finally the models for the simulation of the fluid aeration are described. The review brings to evidence the increasing effort for improving the simulation models used for the design and the…

The search for new energy resources is a crucial task nowadays. Research on the use of solar energy is growing every year. The aim is the design of devices that can produce a considerable amount of energy using the Sun’s radiation. The modeling of solar cells (SCs) is based on the estimation of the intrinsic parameters of electrical circuits that simulate their behavior based on the current vs. voltage characteristics. The problem of SC design is defined by highly nonlinear and multimodal objective functions. Most of the algorithms proposed to find the best solutions become trapped into local solutions. This paper introduces the Chaotic Improved Artificial Bee Colony (CIABC) algorithm for the estimation of SC parameters. It combines the use of chaotic maps instead random variables with the search capabilities of the Artificial Bee Colony approach. CIABC has also been modified to avoid the generation of new random solutions, preserving the information of previous iterations. In comparison with similar optimization methods, CIABC is able to find the global solution of complex and…

Tip clearance between blade end and shroud is inevitable in pump operation and of great importance on pump energy performance and pressure fluctuation. As the tip clearance size increases, the head and efficiency of the mixed flow pump drop accordingly. The simulation results show that the development of a leakage vortex is observed as the tip clearance increases, and the trajectory of this leakage vortex remains in the same direction along the blade suction side for different tip clearances. With the increase in tip clearance size, the intensity of the leakage vortex is enhanced, and the separation between the main leakage vortex and the secondary leakage vortex is also strengthened. The leakage separation angle near the blade tip remains at the same value of 10° for different tip clearance sizes. As for the spectrum analysis, the maximum amplitudes of pressure fluctuations dramatically increase in the impeller when the tip clearance increases from 0.0 mm to 1.0 mm, and the dominant frequencies go from 145 Hz to 184 Hz due to the considerable leakage flow.

Reliable energy forecasting helps managers to prepare future budgets for their buildings. Therefore, a simple, easier, less time consuming and reliable forecasting model which could be used for different types of buildings is desired. In this paper, we have presented a forecasting model based on five years of real data sets for one dependent variable (the daily electricity consumption) and six explanatory variables (ambient temperature, solar radiation, relative humidity, wind speed, weekday index and building type). A single mathematical equation for forecasting daily electricity usage of university buildings has been developed using the Multiple Regression (MR) technique. Data of two such buildings, located at the Southwark Campus of London South Bank University in London, have been used for this study. The predicted test results of MR model are examined and judged against real electricity consumption data of both buildings for year 2011. The results demonstrate that out of six explanatory variables, three variables; surrounding temperature, weekday index and building type have…

150 years ago, Stanley Jevons introduced the concept of energy rebound: that anticipated energy efficiency savings may be “taken back” by behavioural responses. This is an important issue today because, if energy rebound is significant, this would hamper the effectiveness of energy efficiency policies aimed at reducing energy use and associated carbon emissions. However, empirical studies which estimate national energy rebound are rare and, perhaps as a result, rebound is largely ignored in energy-economy models and associated policy. A significant difficulty lies in the components of energy rebound assessed in empirical studies: most examine direct and indirect rebound in the static economy, excluding potentially significant rebound of the longer term structural response of the national economy. In response, we develop a novel exergy-based approach to estimate national energy rebound for the UK and US (1980–2010) and China (1981–2010). Exergy—as “available energy”—allows a consistent, thermodynamic-based metric for national-level energy efficiency. We find large energy rebound in…

This review article is mainly oriented to the control and applications of modular multilevel converters (MMC). The main topologies of the switching modules are presented, for normal operation and for the elimination of DC faults. Methods to keep the capacitor voltage balanced are included. The voltage and current modulators, that are the most internal loops of control, are detailed. Voltage control and current control schemes are included which regulate DC link voltage and reactive power. The cases of unbalanced and distorted networks are analyzed, and schemes are proposed so that MMC contribute to improve the quality of the grid in these situations. The main applications in high voltage direct current (HVDC) transmission along with other medium voltage (MV) and low voltage (LV) applications are included. Finally, the application to offshore wind farms is specifically analyzed.

Delamination in Wind Turbine Blades (WTB) is a common structural problem that can generate large costs. Delamination is the separation of layers of a composite material, which produces points of stress concentration. These points suffer greater traction and compression forces in working conditions, and they can trigger cracks, and partial or total breakage of the blade. Early detection of delamination is crucial for the prevention of breakages and downtime. The main novelty presented in this paper has been to apply an approach for detecting and diagnosing the delamination WTB. The approach is based on signal processing of guided waves, and multiclass pattern recognition using machine learning. Delamination was induced in the WTB to check the accuracy of the approach. The signal is denoised by wavelet transform. The autoregressive Yule–Walker model is employed for feature extraction, and Akaike’s information criterion method for feature selection. The classifiers are quadratic discriminant analysis, k-nearest neighbors, decision trees, and neural network multilayer perceptron. The…

In this work, we assess the performance of three probabilistic models for intra-day solar forecasting. More precisely, a linear quantile regression method is used to build three models for generating 1 h–6 h-ahead probabilistic forecasts. Our approach is applied to forecasting solar irradiance at a site experiencing highly variable sky conditions using the historical ground observations of solar irradiance as endogenous inputs and day-ahead forecasts as exogenous inputs. Day-ahead irradiance forecasts are obtained from the Integrated Forecast System (IFS), a Numerical Weather Prediction (NWP) model maintained by the European Center for Medium-Range Weather Forecast (ECMWF). Several metrics, mainly originated from the weather forecasting community, are used to evaluate the performance of the probabilistic forecasts. The results demonstrated that the NWP exogenous inputs improve the quality of the intra-day probabilistic forecasts. The analysis considered two locations with very dissimilar solar variability. Comparison between the two locations highlighted that the statistical…

SrTiO3/epoxy nanocomposites are prepared using the facile solution-processing technique by incorporating SrTiO3 nanoparticles with different weight fractions into the epoxy resin host. The morphology of the nanoparticles and composites, as well as the thermal conduction characteristics and electrical properties of the composites were investigated via conventional testing methods. The thermal conductivity increased along with the SrTiO3 weight fractions, and the thermal conductivity of the SrTiO3/epoxy composite with 40 wt % weight fraction increased to 0.52 W/mK. The dielectric constant increased along with the weight fractions and decreased along with frequency, thereby suggesting that the interfacial and dipole polarization do not follow the changes in the electrical field direction at high frequency. The dielectric constants at 1 kHz frequency increased along with temperature. Surface breakdown tests illustrated further improvements in the thermal and electrical properties of the composites. In the same time span of 40 s, the 40 wt % nanocomposite demonstrated a rapid temperature…

Li-ion batteries experience mechanical stress evolution due in part to Li intercalation into and de-intercalation out of the electrodes, ultimately resulting in performance degradation. In situ measurements of electrode stress can be used to analyze stress generation factors, verify mechanical deformation models, and validate degradation mechanisms. They can also be embedded in Li-ion battery management systems when stress sensors are either implanted in electrodes or attached on battery surfaces. This paper reviews in situ measurement methods of electrode stress based on optical principles, including digital image correlation, curvature measurement, and fiber optical sensors. Their experimental setups, principles, and applications are described and contrasted. This literature review summarizes the current status of these stress measurement methods for battery electrodes and discusses recent developments and trends.

Increasing use of the ground as a thermal reservoir is expected in the near future. Shallow geothermal energy (SGE) systems have proved to be sustainable alternative solutions for buildings and infrastructure conditioning in many areas across the globe in the past decades. Recently novel solutions, including energy geostructures, where SGE systems are coupled with foundation heat exchangers, have also been developed. The performance of these systems is dependent on a series of factors, among which the thermal properties of the soil play a major role. The purpose of this paper is to present, in an integrated manner, the main methods and procedures to assess ground thermal properties for SGE systems and to carry out a critical review of the methods. In particular, laboratory testing through either steady-state or transient methods are discussed and a new synthesis comparing results for different techniques is presented. In situ testing including all variations of the thermal response test is presented in detail, including a first comparison between new and traditional approaches. The…

Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. This paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power…

This paper endeavors to apply a novel intelligent damping controller (NIDC) for the static synchronous compensator (STATCOM) to reduce the power fluctuations, voltage support and damping in a hybrid power multi-system. In this paper, we discuss the integration of an offshore wind farm (OWF) and a seashore wave power farm (SWPF) via a high-voltage, alternating current (HVAC) electric power transmission line that connects the STATCOM and the 12-bus hybrid power multi-system. The hybrid multi-system consists of a battery energy storage system (BESS) and a micro-turbine generation (MTG). The proposed NIDC consists of a designed proportional–integral–derivative (PID) linear controller, an adaptive critic network and a proposed functional link-based novel recurrent fuzzy neural network (FLNRFNN). Test results show that the proposed controller can achieve better damping characteristics and effectively stabilize the network under unstable conditions.

Energy management systems are essential and indispensable for the secure and optimal operation of autonomous polygeneration microgrids which include distributed energy technologies and multiple electrical loads. In this paper, a multi-agent decentralized energy management system was designed. In particular, the devices of the microgrid under study were controlled as interactive agents. The energy management problem was formulated here through the application of game theory, in order to model the set of strategies between two players/agents, as a non-cooperative power control game or a cooperative one, according to the level of the energy produced by the renewable energy sources and the energy stored in the battery bank, for the purpose of accomplishing optimal energy management and control of the microgrid operation. The Nash equilibrium was used to compromise the possible diverging goals of the agents by maximizing their preferences. The proposed energy management system was then compared with a multi-agent decentralized energy management system where all the agents were assumed to…

Li-ion batteries have become a dominant power source in consumer electronics and vehicular applications. The mobile use of batteries subjects them to various mechanical loads. The mechanisms that follow a mechanical deformation and lead to damage and failure in Li-ion batteries have only been studied in recent years. This paper is a comprehensive review of advancements in experimental and computational techniques for characterization of Li-ion batteries under mechanical abuse loading scenarios. A number of recent studies have used experimental methods to characterize deformation and failure of batteries and their components under various tensile and compressive loading conditions. Several authors have used the test data to propose material laws and develop finite element (FE) models. Then the models have been validated against tests at different levels from comparison of shapes to predicting failure and onset of short circuit. In the current review main aspects of each study have been discussed and their approach in mechanical testing, material characterization, FE modeling, and…

In this study power generation and demand are matched through a least-cost mix of renewable energy (RE) resources and storage technologies for North America by 2030. The study is performed using an hourly resolved model based on a linear optimization algorithm. The geographical, technical and economic potentials of different forms of RE resources enable the option of building a super grid between different North American regions. North America (including the U.S., Canada and Mexico in this paper), is divided into 20 sub-regions based on their population, demand, area and electricity grid structure. Four scenarios have been evaluated: region-wide, country-wide, area-wide and an integrated scenario. The levelised cost of electricity is found to be quite attractive in such a system, with the range from 63 €/MWhel in a decentralized case and 42 €/MWhel in a more centralized and integrated scenario. Electrical grid interconnections significantly reduce the storage requirement and overall cost of the energy system. Among all RE resources, wind and solar PV are found to be the least-cost…

Energy planning and policy development require an in-depth assessment of energy resources and long-term demand forecast estimates. Pakistan, unfortunately, lacks reliable data on its energy resources as well do not have dependable long-term energy demand forecasts. As a result, the policy makers could not come up with an effective energy policy in the history of the country. Energy demand forecast has attained greatest ever attention in the perspective of growing population and diminishing fossil fuel resources. In this study, Pakistan’s energy demand forecast for electricity, natural gas, oil, coal and LPG across all the sectors of the economy have been undertaken. Three different energy demand forecasting methodologies, i.e., Autoregressive Integrated Moving Average (ARIMA), Holt-Winter and Long-range Energy Alternate Planning (LEAP) model were used. The demand forecast estimates of each of these methods were compared using annual energy demand data. The results of this study suggest that ARIMA is more appropriate for energy demand forecasting for Pakistan compared to Holt-Winter…

The economic and environmental benefits brought by electric vehicles (EVs) cannot be fully delivered unless these vehicles are fully or partially charged by renewable energy sources (RES) such as photovoltaic system (PVS). Nevertheless, the EV charging management problem of a parking station integrated with RES is challenging due to the uncertain nature of local RES generation. This paper aims to address these difficulties by deploying an energy storage system (ESS) in parking stations and exploiting the charging and discharging scheduling of EVs to achieve better utilization of intermittent PVS for EV charging. A real-time charging optimization scheme is also formulated, using mixed-integer linear programming (MILP) to coordinate the charging or discharging power of EVs along with the power dispatches of power grid and ESS based on the vehicles’ charging or discharging priorities and electricity price preferences. Extensive simulations show that the proposed approach not only maximizes the satisfaction of EV owners in terms of fulfilling all charging and discharging requests, but…

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs,…