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This paper considers a single-machine scheduling problem with sequence-dependent setup times and energy-generation and storage systems. Each job requires a sequence-dependent setup to be processed on the machine, and both setup and processing of the job require job-dependent amounts of energy. The energy consumed by the machine can be bought from an Electric Power Company (EPC) or generated by own Distributed Energy Resource (DER), such as solar photovoltaic or wind, and the energy can be stored in an Energy Storage System (ESS). The objective is to minimise the total cost, the sum of production cost depending on makespan and energy cost by considering energy usage from the EPC, DER and ESS. For the problem, a mathematical programming model is first derived by using period-based indexes. Then, a hybrid genetic algorithm, which adds appropriate idle times between jobs and determines an efficient energy schedule by storing some energy during less expensive periods into the ESS for later use in high-price periods, is developed. Finally, computational experiments show that the proposed algorithm provides effective solutions, and which component of the total cost affects the performance the most, how effective adding idle times between jobs is, and how much cost can be saved by having a DER and ESS. [ABSTRACT FROM AUTHOR]

Forecasts and their corresponding optimized operation plans for energy plants never match perfectly, especially if they have a horizon of several days. In this paper, we suggest a concept to cope with uncertain load forecasts by reserving a share of the energy storage system for short-term balancing. Depending on the amount of uncertainty in the load forecasts, we schedule the energy system with a specific reduced storage capacity at the day-ahead market. For the day of delivery, we examine the optimal thresholds when the remaining capacity should be used to balance differences between forecast and reality at the intraday market. With the help of a case study for a simple sector-coupled energy system with a demand for cooling, it is shown that the energy costs could be reduced by up to 10% using the optimal reserve share. The optimal reserve share depends on the forecast quality and the time series of loads and prices. Generally, the trends and qualitative results can be transferred to other systems. However, of course, an individual evaluation before the realization is recommended. [ABSTRACT FROM AUTHOR]

The widespread installation of 5G base stations has caused a notable surge in energy consumption, and a situation that conflicts with the aim of attaining carbon neutrality. Numerous studies have affirmed that the incorporation of distributed photovoltaic (PV) and energy storage systems (ESS) is an effective measure to reduce energy consumption from the utility grid. The optimization of PV and ESS setup according to local conditions has a direct impact on the economic and ecological benefits of the base station power system. An improved base station power system model is proposed in this paper, which takes into consideration the behavior of converters. And through this, a multi-faceted assessment criterion that considers both economic and ecological factors is established. Then, the PV and ESS capacity optimization for base stations under multiple scenarios is realized. The case study indicates that the optimization process of PV and ESS is significantly influenced by the behavior of the converter. [ABSTRACT FROM AUTHOR]

Due to the uncertainty of user's behaviour and other conditions, the design of energy efficiency improvement methods in buildings is challenging. In this paper, a building energy management method based on deep reinforcement learning is proposed, which solves the energy scheduling problem of buildings with renewable sources and energy storage system and minimises electricity costs while maintaining the user's comfort. Different from model-based methods, the proposed DRL agent makes decisions only by observing the measurable information without considering the dynamic of the building environment. Simulations based on real data verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Electric microgrids based mainly on renewable energies have seen a big expansion in recent years due to the great advantages they present against fossil fuels. Nowadays different governments are becoming aware of the use of environmentally friendly energies, so progressive investment has been granted to the consumers in Spain. Many microgrids have been installed in both connected and isolated circumstances, and this fact brings new challenges regarding the technical and economic points of view. This study aims to delve into electrical microgrids based on renewable energies applied in industrial facilities through a review of the literature associated with the study of general microgrids. It later focuses on the relationships between renewable energies and industrial environments. A brief reference is made to the use of energy storage systems in industrial installations depicting the most used systems. This paper presents a review of the state of the art of microgrids from distributed energy resources technologies to industrial microgrids optimization, with the primary objective of providing insight on current trends and directions in research and further identifying areas in need of further development. [ABSTRACT FROM AUTHOR]

Renewable energy systems are mostly used in the world due to their inexhaustible and nonpolluting production. As a result of a large utilization of these energy sources in different areas, the electricity production rate is increasing every day. Previous studies clarified uses, modeling, configuration, energy management operation, and optimization objectives based on different energy sources. For this reason, this paper focuses on an overview of multi energy systems as renewable and conventional power sources with the integration of an energy storage system coupled to the on-off electrical network. Furthermore, a survey is done regarding global energy production, configuration energy systems, energy storage systems, power management strategies, and optimization methods based on different hybrid energy systems. Multiple optimization approaches have been implemented to reach the global best solution for the hybrid power systems. To ensure the best optimization result, it is preferable to take hybrid optimization methods into consideration. These methods have been invented recently and have proved their efficacy and performance mainly in power systems. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the two‐stage hierarchical control of microgrids (MG) that can operate in both grid‐connected and off‐grid modes. The procedure consists in the segmentation of the control scheme in the primary and secondary levels, thus enabling the application of faster and slower dynamics according to the process. A decentralized droop control‐based method is used in the primary level, while a distributed multi‐agent coordination scheme is applied in the secondary one. The multi‐agent system is run on Python Agent DEvelopment (PADE) environment, a FIPA‐compliant agent framework. The key contributions this paper provides are the control strategies of reactive power output of non‐dispatchable sources, dynamic sharing of energy storage systems, and the management of loads of microgrids, all of them based on multi‐agent system. Co‐simulations using PSCADTM and PADE are performed considering several operating scenarios of the MG resources under different load conditions. Simulation results validate the accurate performance of the proposed control strategies. [ABSTRACT FROM AUTHOR]

The stationary supercapacitor energy storage system (SCESS) is one of effective approaches for the utilization of train's regenerative braking energy in urban rail systems. In this paper, the capacity configuration of SCESSs, the no-load voltage of substation, the control of onboard braking resistors and train operation diagrams are considered comprehensively. Based on the equivalent circuit model, the effects of traction power system parameters on the energy transmission between powering trains, braking trains and SCESSs are analyzed, and the relationships between the train operating parameters and system energy consumptions are revealed. A multi-variable synthetic optimization method is proposed to optimize the SCESS capacity, train operation diagrams and traction power system parameters collaboratively. In order to reduce the search space and improve the efficiency of the optimization algorithm, a hierarchical multi-objective optimization model is established, based on which the design variables and the control variables are optimized iteratively. And as the traffic density has a great impact on the regenerative braking energy distribution of the system, the optimization objective function fully considers the frequency distribution of headways throughout the day. Combined the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with the traction power flow simulator, the flowchart of the two-stage optimization algorithm is designed, and the pareto set of the multi-objective problem is obtained. The advantages of reducing system energy consumptions and configuration cost under the proposed algorithm are verified based on case studies of Beijing Batong Line. [ABSTRACT FROM AUTHOR]

Different from low-temperature electrolysis systems, the large power consumption for the balance of plant (BOP) of the reversible solid oxide cell (RSOC) system for a high-temperature operating condition needs to be considered in the determination of the capacity configuration of the hybrid renewable energy (HRE) system. To address this issue, a power-based model of the RSOC system is developed and the corresponding capacity configuration strategy especially for the HRE system is also proposed in this paper. An optimization program of a hybrid energy system model composed of the wind turbines (WT), photovoltaic panels (PV), reversible solid oxide cell (RSOC) system, hydrogen storage tank (HST), and battery are presented to urge the minimization of the total system cost, power redundancy, and power shortage. Particle swarm optimization (PSO) algorithm is utilized to determine the optimum size and operational energy management within the system. The results show that after the regulation of the energy storage system, the power redundancy and shortage of the hybrid energy system are greatly reduced with the decreases by 85.08% and 64.42%, respectively. Moreover, the power mismatch is still significantly affected by seasons. It is also found that the energy storage efficiency of the RSOC system is within 20% due to the fact that part of the electric energy is consumed by the BOP to maintain the operation of the RSOC system. Thus, more improvements should focus on simplifying the BOP system of the RSOC system and reducing the excess power consumption in the future. [ABSTRACT FROM AUTHOR]

The All-electric ship (AES) concept has revolutionized the maritime sector. Indeed, AES is a promising solution for modern vessels where decreasing emission pollution, suppressing fossil fuel consumption, and making economical operation are its brilliant merits. Fuel cell (FC) technology based on clean hydrogen energy sources can play a significant role in meeting these requirements in the AES platform. Because of the slow transient response of the FC, an energy storage system (ESS) is required to improve AES performance in different operation scenarios. Therefore, optimal sizing of the FC and the ESS and proper design of energy management strategy is a challenging problem. This paper proposes a systematic approach for the optimal design of hybrid FC-ESS of AES power systems. The proposed method is based on an optimization technique to determine the optimal sizing of the FCs and the ESS. Capital investment, fuel consumption, personnel electrical safety, and occupied volume of the AES power system are the main objectives. The FC size, the battery size, the scheduled output power of the FC, and the battery are the decision variables. Genetic Algorithm (GA) is used to solve the optimization problem. To validate the numerical results, the optimization problem is also solved by Mayfly Algorithm (MA) separately. To assess the feasibility of the proposed strategy, the optimal design of hybrid FC-ESS for a vessel is implemented based on the proposed method. The simulation results validate the proposed approach's sufficiency to investigate and optimize the economic, safety, and dimensional aspects of designing the FC ship's IPS. Numerical results are reported for each design aspect. Considering the minor differences of the numerical results obtained by GA and MA, the optimum points are validated by the two techniques. Using the obtained results, various perceptions can be derived from the FC ship's IPS design. For example, the IPS cost in the cases with optimum volume, weight, and safety, has 2.3%, 2.6%, and 7.3% penalties, respectively compared to the case with the minimum cost. • Fuel cell-based electrification of a fishing ship based on practical information. • Systematic approach for optimal power system design of hydrogen-powered ship. • Proposing safety objective function for integrated power system of fuel cell ship. • Fuel cell hybrid IPS optimization based on volume, mass, cost and safety. • Estimation of propulsion power demand based on ship's resistance and speed profile. [ABSTRACT FROM AUTHOR]

In the energy system, various sources are used to fulfill the energy demand of large buildings. The energy management of large-scale buildings is very important. The proposed system comprises solar PVs, energy storage systems, and electric vehicles. Demand response (DR) schemes are considered in various studies, but the analysis of the impact of dynamic DR on operational cost has been ignored. So, in this paper, renewable energy resources and storages are integrated considering the demand response strategies such as real-time pricing (RTP), critical peak pricing (CPP), and time of use (ToU). The proposed system is mapped in a linear model and simulated in MATLAB using linear programming (LP). Different case studies are investigated considering the dynamic demand response schemes. Among different schemes, results based on real-time pricing (58% saving) show more saving as compared to the CPP and ToU. The obtained results reduced the operational cost and greenhouse gas (GHG) emissions, which shows the efficacy of the model. [ABSTRACT FROM AUTHOR]

Hybrid energy storage systems (HESS) for electric vehicles, which consist of lithium-ion batteries and supercapacitors, have become an increasing focus of research and development in recent years. The combination of the two combines the advantages of each storage technology (high energy density in batteries and high power density in supercapacitors) in one system. To effectively manage the energy flow between these two different storage technologies, an intelligent energy management system (EMS) is required. In the development of the EMS, it is usual to run preliminary checks in a simulation environment that is as close to reality as feasible already during the development process. For this purpose, this paper presents a concept for the creation of a simulation environment consisting of realistic routes and a holistic vehicle model. The realistic route data are generated by a route-generating algorithm, which accesses different map services via application programming interfaces (API) and retrieves real route data to generate a simulated route. By integrating further online services (e.g., OpenWeather API), the routes are further specified with, for example, real weather data, traffic data, speed limits and altitude data. For the complete vehicle model, components including the suspension, chassis and auxiliary consumers are simulated as blackbox models. The components that can be accessed during the simulation are simulated as white box models. These are the battery, the supercapacitor, the DC/DC converter and the electric motor. This allows the EMS to control and regulate the HESS in real time during the simulation. To validate the simulation environment presented here, a real BMW i3 was driven on a real route, and its energy demand was measured. The same route was simulated in the simulation environment with environmental conditions that were as realistic as feasible (traffic volume, traffic facilities, weather) and the vehicle model of the BMW i3. The resulting energy demand from the simulation was recorded. The results show that the simulated energy consumption value differs by only 1.92% from the real measured value. This demonstrates the accuracy of the simulation environment presented here. [ABSTRACT FROM AUTHOR]

With the increasing adoption of solar photovoltaics (PVs) in the power grid, the grid authorities are faced with significant challenges in managing PV intermittency, variability and uncertainty. The inherent ramping behaviour of the PVs results in short-term PV power fluctuations which in-turn affects the grid voltage regulation. This has resulted in implementation of new grid codes to limit the ramp-rate (RR) behaviour of PVs allowing the grid resources to curb the power fluctuations. Energy storage system (ESS) is one such fast acting resource that helps in limiting and smoothing PV power fluctuations when coordinated by RR control algorithms. This paper proposes an ESS-based RR control strategy to smoothen and limit PV power fluctuations in the power grid. The proposed RR control strategy has been implemented for two types of smoothing namely, aggregated smoothing that considers the overall PV output, and individual node-level smoothing that considers the individual PV output. The technical feasibility of this RR control strategy to limit the PV power fluctuations is analysed using a standard IEEE test network with both centralized and distributed ESS placements at various PV penetration levels. The effectiveness of the proposed RR control strategy in reducing voltage fluctuations in the power network is also studied. Moreover, cost optimization is carried out with various PV penetration levels to ensure optimal ESS operation at the lowest possible cost while adhering to the optimization and network constraints. The paper further provides detailed techno-economic analysis for various case scenarios. • Ramp-rate control of solar PV is implemented using energy storage system. • Different types of smoothing techniques are used in ramp-rate control strategy. • Impacts of both centralized and distributed energy storage systems are analysed. • Techno-economic analysis is conducted for optimal operation of energy storage. [ABSTRACT FROM AUTHOR]

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element. [ABSTRACT FROM AUTHOR]

In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

Emergency generators are important facilities that supply emergency power to fire-fighting facilities in the event of a power outage. Accordingly, a load test of the emergency generator should be performed by cutting off the power source of the fire-fighting target in order to accurately confirm the performance and condition of the emergency generator in normal circumstances. However, the test has usually been carried out without loads due to serious problems, which are caused by a shutdown of the power source for the load test of emergency generators, such as the shutdown of emergency load, etc. In order to overcome these problems, this paper proposes an operation method and algorithm of a load test device using ESS, which can conform to characteristics of emergency loads installed in fire-fighting targets by interconnecting it with the emergency generator. In addition, this paper performs a modeling of an emergency power system using PSCAD/EMTDC, and then this paper confirms the usefulness of the proposed method and operation algorithm of the load test device using ESS. [ABSTRACT FROM AUTHOR]

Energy storage technology is recognized as an underpinning technology to have great potential in coping with a high proportion of renewable power integration and decarbonizing power system. However, the costs of energy storage facilities remain high-level and it makes energy storage a luxury in many application fields. To address this issue, a new type of energy storage business model named cloud energy storage was proposed, inspired by the sharing economy in recent years. This paper presents a review and outlook on cloud energy storage technology. The paper starts with the introduction of the basic concept, fundamental structure, and superiorities of cloud energy storage. Facing the energy storage utilization demands of the users on the source side, grid side, and demand side, the typical application scenarios of cloud energy storage are analyzed, and the corresponding state-of-art pilot trials are introduced. After that, the theoretical research framework of the cloud energy storage technology is presented, and the research status of cloud energy storage technology is surveyed. Finally, considering the combination of cloud energy storage and other advanced energy and information technology such as multi-energy coordination and blockchain, the evolution path and development prospects of cloud energy storage are discussed. • Basic attributes including concept, framework and superiorities, as well as corresponding pilot trials of cloud energy storage for different application scenarios are concluded. • The achievements, shortcomings and key research directions of the three most concerning areas of cloud energy storage technology are summarized. • The development prospects of cloud energy storage technology considering the combination with multi-energy technology, virtual energy storage and distributed information technologies are analyzed. [ABSTRACT FROM AUTHOR]

Intermittency characteristic of renewable energy sources can be resolved using an energy storage technology. The function of the energy storage system is to store the excess energy that is produced from various renewable energy sources during the off‐peak hours and releases the same energy during the peak hours. The energy that is produced from the renewable energy sources can be stored in different forms such as Mechanical, Electrical, Electrochemical, Thermal, Chemical energy etc. Among all these forms of stored energy, a CAES technology under the Mechanical form of energy is the most cost effective for the bulk energy storage purpose. It involves a combined operation of various components such as Compressor/Expander, Gas turbine, combustion chambers, heat exchangers, generator unit, and underground compressed air storage. This article focuses to review the detail of various CAES systems such as D‐CAES, A‐CAES, I‐CAES etc. Additionally, it presents various technologies that are used to improve the energy efficiency and applicability of the CAES system. It is found that a maximum RTE of the C‐CAES, A‐CAES, and I‐CAES are 54%, 71%, and 80%, respectively. In addition, the RTE of the modified CAES systems such as LP‐CAES, PH‐CAES, and SC‐CAES are about 90%, 80%, and 60 to 80%, respectively. [ABSTRACT FROM AUTHOR]

This article presents a study of optimal control strategies for an energy storage system connected to a network of electrified Rubber Tyre Gantry (RTG) cranes. The study aims to design optimal control strategies for the power flows associated with the energy storage device, considering the highly volatile nature of RTG crane demand and difficulties in prediction. Deterministic optimal energy management controller and a Model Predictive Controller (MPC) are proposed as potentially suitable approaches to minimise the electric energy costs associated with the real-time electricity price and maximise the peak demand reduction, under given energy storage system parameters and network specifications. A specific case study is presented in to test the proposed optimal strategies and compares them to a set-point controller. The proposed models used in the study are validated using data collected from an instrumented RTG crane at the Port of Felixstowe, UK and are compared to a standard set-point controller. The results of the proposed control strategies show a significant reduction in the potential electricity costs and peak power demand from the RTG cranes. [ABSTRACT FROM AUTHOR]

The two most critical deciding factors for power consumption are energy efficiency and cost. Power electronic circuits are widely used and play an important role in achieving high efficiency in power distribution to customers and power transfer from source to load. Furthermore, solar energy is abundant, sustainable, and pollution-free in nature. Power electronic circuits are used in high-power applications with voltages ranging from a few millivolts to thousands of volts and wattages ranging from a few mW to megawatts. This paper examines a variety of inverter topologies and their modeling, as well as a comparison of single-stage and multi-stage/inverter topologies depending on the application. The main aim of control techniques is to keep Total Harmonic Distortion (THD) to a minimum and the switching frequency within the permissible range so that inverters for renewable energy sources, electric vehicles, uninterruptible power supply (UPS) systems, and hybrid energy storage systems can work efficiently. Plug-and-play, adaptability, self-awareness, and other features should all be included in a smart inverter. Based on the findings of this comparative analysis, selection criteria are established. This comparative analysis can be used to develop selection criteria for choosing inverter circuits for the various applications described in this paper. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy technology, marine current energy is treated as the most desirable form of ocean energies. Due to the nature of marine current energy, simple structure, high reliability, and good control performance are the primary consideration for the energy management strategy. This paper proposes an energy management control strategy based on rules to compensate for the fluctuating power caused by tidal motion. The hybrid energy storage system composed of vanadium redox flow battery (VRB) is applied to reallocate power. Supercapacitor banks (SCBs) are applied as the auxiliary power source to absorb or release the required power according to energy management strategy based on control rules in the marine current power system. SCB makes the grid-connected power track the grid command power and also improves the operational efficiency of the vanadium redox flow battery (VRB). VRB compensates for the low-frequency fluctuating power caused by tidal motion and plays an important role in compensating for the difference in power between the grid-connected power and the grid command power to ensure the reliability of the marine current power system. A simulation model of a 3 MW marine current power system is built to verify the effectiveness of the energy management strategy based on the real marine current velocity data. [ABSTRACT FROM AUTHOR]

The global population is rapidly increasing, and the urban population is on an even faster trend; therefore, the population density is expected to rise. As the number of people in cities grows, the demand for high-rise buildings is anticipated to increase to address the problem of limited land resources. Therefore, efficient energy management using distributed resources has become increasingly important. Elevators are a vital vertical means of transportation in high-rise buildings, and reducing the weight of their components can lead to favorable conditions for energy utilization and increased speed. Therefore, this study presents an elevator system that supplies power inside an elevator car by eliminating the traveling cable and applying a small-capacity energy storage system (ESS). Additionally, we propose a charging algorithm suitable for the proposed system. Generally, batteries have sensitive electrical properties among the distributed energy resources (DERs). Therefore, controlling the stable maintenance of the transient state of the charging current—even when the DC power is unstable or the load changes rapidly in a system requiring fast charging—is crucial. Owing to the nature of the elevator system to be applied, discontinuous charging is frequent, and the active and efficient management of the battery state of charge (SOC) may be challenging. In addition, since it is necessary to be able to charge as much as possible during a short discontinuous charging time, a current control algorithm with a stable and high-speed response is required. The proposed transient high-speed tracking controller (THSTC) is a method for tracking the time of applying an inductor's excitation voltage without pulse–width modulation (PWM) switching, which is less sensitive to the controller gain values and has fast responsiveness as well as stable transient response characteristics. The proposed method has good dynamic characteristics with a simple control structure without a complex design, which is useful for systems with repeated discontinuous charging. We validate the performance and effectiveness of the proposed controller through simulations and experiments. [ABSTRACT FROM AUTHOR]

Summary: At present with the massive induction of distributed renewable energy sources (RES), energy storage systems (ESS) have the potential to curb the intermittent nature of micro sources and provide a steady supply of power to the load. It gives an optimum solution and considers as a major part of intelligent grids. For making a green environment, Electric Vehicle (EV) is the best option that emits zero exhaust gases, cleaner, less noisy and eco‐friendly compared to engine‐based vehicles. It could embark power sanctuary by allowing open access to RES. Nonetheless, EVs presently face encounters in the deployment of ESSs, inroad to their reliability, capacity, price, and online management issues. This study comprehensive review about technical advancements of ESSs, its detailed taxonomy, features, implementation, possibilities with system differences, and additional features of particularly EV applications. Hence, in this current study, technical analysis of Energy storage systems, its leading technologies, core assets, global energy stakeholders, economic merits and techniques on energy conversion is provided. Besides, the way of deploying energy storage techniques, the barriers and assessments are also presented to give a wider scope in this particular area. [ABSTRACT FROM AUTHOR]

The application of a stationary ultra-capacitor energy storage system (ESS) in urban rail transit allows for the recuperation of vehicle braking energy for increasing energy savings as well as for a better vehicle voltage profile. This paper aims to obtain the best energy savings and voltage profile by optimizing the location and size of ultra-capacitors. This paper firstly raises the optimization objective functions from the perspectives of energy savings, regenerative braking cancellation and installation cost, respectively. Then, proper mathematical models of the DC (direct current) traction power supply system are established to simulate the electrical load-flow of the traction supply network, and the optimization objections are evaluated in the example of a Chinese metro line. Ultimately, a methodology for optimal ultra-capacitor energy storage system locating and sizing is put forward based on the improved genetic algorithm. The optimized result shows that certain preferable and compromised schemes of ESSs' location and size can be obtained, acting as a compromise between satisfying better energy savings, voltage profile and lower installation cost. [ABSTRACT FROM AUTHOR]

Multiple wave energy converter (WEC) buoys can be used to establish a WEC array-powered microgrid collectively forming a Marine Energy Grid (MEG). An oceanic domain with gravity waves will have significant spatial variability in phase, causing the power produced by a WEC array to have high peak-to-average ratios. Minimizing these power fluctuations reduces the demand for large energy storage by WEC array-powered DC microgrids while also reducing losses in the undersea cable to the shore. Designs that reduce energy storage requirements are desirable to reduce deployment and maintenance costs. This work demonstrates that polyphase power in conjunction with an energy storage system can be used to maintain constant power. This work shows that an N WEC array geometry can be designed to reduce the energy storage requirements needed to mitigate the power fluctuations if the WEC array produces constant, polyphase power. Additionally, the conditions that identify the wave frequencies and control the effort needed to produce polyphase power are developed. This paper also shows that increasing the number of WECs in an array reduces aggregate power fluctuations. Finally, WEC array power profiles are investigated using simulation results to verify the mathematical conditions developed for the three and six WEC cases. [ABSTRACT FROM AUTHOR]

Increasing the proportion of carbon-free power sources, such as renewable energy, is essential for transitioning to a zero-carbon power system. However, when the rate of grid expansion and flexibility cannot match the rate of renewable energy increase, surplus energy is the result. Surplus energy can be discarded through curtailment or stored and utilized when required. The optimal equipment configuration of the storage system should be determined based on the surplus energy characteristics. This study proposes an optimal energy storage mix configuration method by considering long-term forecasts of surplus energy in the South Korean renewable energy supply and power grid expansion plan. The surplus energy by time slot is comprehensively analyzed considering renewable energy power output, power demand, and power system operation constraints. We calculate the required power and energy of storage devices. Furthermore, we construct a long-term optimal energy storage mix using surplus energy generation patterns and technical and economical characteristics of storage technologies. The total cost minimization was considered as the objective function, comprising three elements: initial construction, equipment replacement, and loss costs for charging and discharging. We propose a time sequence analysis (TSA) method that enables chronological analysis from the starting year to the final target year. The TSA method provides an energy storage mix configuration roadmap that can utilize surplus energy for various years over the entire period, considering the annual increase in surplus energy and commercialization timing of each storage technology. We compare the difference between our proposed TSA method and the method that analyzes only the final target year to validate the superiority of this methodology. [ABSTRACT FROM AUTHOR]

Abstract: Wind Energy is a fast developing source of energy since 1996. Despite its advantages, this energy could never be a primary source of electric power to be integrated into the grid even in high wind areas, such as Great Plains, due to its intermittent behaviour. This intermittency will generate intermittent power to grid, which leads to instability, unreliability and power quality problem onto the grid system. One of the widely accepted methods to overcome this problem is by coupling the wind turbine with the energy storage system. This paper reviews the ability of four different types of the energy storage system to mitigate the power fluctuated into the grid, especially during low wind speed. This paper also explains the operating principles and the different methods of charging and discharging the energy storage. The ability of permanent magnet synchronous generator (PMSG) in dealing with variable wind speed also will be discussed. [Copyright &y& Elsevier]

The global consumerism trend and the increase in worldwide population is increasing the need to improve the efficiency of marine container transportation. The high operating costs, pollution and noise of the diesel yard equipment is leading sea ports to move towards replacing diesel RTG cranes with electric Rubber Tyre Gantry (RTG) cranes which offer reduced environmental impact and higher energy efficiency. However, ports will require smarter solutions to meet the increased demand on the electrical distribution network due to the electrification of RTGs. This paper aims to highlight the peak demand problem in the two electrical cranes network and attempts to increase the energy saving at ports by using two different technologies: Energy Storage System (ESS) and Active Front End (AFE). This article introduces one of the first extensive investigations into different networks of RTG crane models and compares the benefits of using either AFE or ESS. The proposed RTG crane models and network parameters are validated using data collected at the Port of Felixstowe, UK. The results of the proposed RTG cranes network show a significant peak demand reduction and energy cost saving. [ABSTRACT FROM AUTHOR]

The integration of more-electric technologies, such as energy storage systems (ESSs) and electric propulsion, has gained attention in recent years as a promising approach to reduce fuel consumption and emissions in the maritime industry. In this context, hybrid power systems (HPSs) with direct current (DC) distribution are currently gaining a commendable interest in research and industrial applications. This paper examines the impact of using HPS with DC distribution and a battery energy storage system (BESS) over a conventional AC power system for short haul roll-on/roll-off (RORO) ferries. An electric ferry with a HPS is modeled in this study and the power management system is simulated using the Matlab/Simulink software. The result is validated using measured load profile of a ferry. The performance of the DC HPS is compared with the conventional AC system based on fuel consumption and emission reductions. An approach to estimate the fuel consumption of the diesel engine through calculation of specific fuel oil consumption (SFOC) is also presented. This study uses two optimization techniques: a classical power management method namely Rule-Based control (RB) and a meta-heuristic power management method known as Grey Wolf Optimization (GWO) to optimally manage the power sharing of the proposed HPS. Fuel consumption and emission indicators are also used to assess the performance of the two power management methods. The simulation results show that the HPS provides a 2.91% and 7.48% fuel consumption reduction using RB method and GWO method respectively. It is apparent from the result that the HPS has more fuel savings while running the diesel generator sets (DGs) at higher operational efficiency. It is interesting that the proposed HPS using both power management methods provided a 100% emission reduction at berth. Finally, it was found that using a meta-heuristic optimization algorithm provides better fuel and emission reductions than a classical method. [ABSTRACT FROM AUTHOR]

This paper proposes an advanced shipboard energy management strategy (EMS) based on model predictive control (MPC). This EMS aims to reduce mission-scale fuel consumption of ship hybrid power plants, taking into account constraints introduced by the shipboard battery system. Such constraints are present due to the boundaries on the battery capacity and state of charge (SoC) values, aiming to ensure safe seagoing operation and long-lasting battery life. The proposed EMS can be used earlier in the propulsion design process and requires no tuning of parameters for a specific operating profile. The novelties of the study reside in (i) studying the impact of mission-scale effects and integral constraints on optimal fuel consumption and controller robustness, (ii) benchmarking the performance of the proposed MPC framework. A case study carried out on a naval vessel demonstrates near-optimal and robust behaviour of the controller for several loading sequences. The application of the proposed MPC framework can lead to up to 3.5% consumption reduction due to utilisation of long term information, considering specific loading sequences and charge depleting (CD) battery operation. [ABSTRACT FROM AUTHOR]

This paper describes the hybrid-electric vehicles (HEVs) and automotive propulsion technologies. The viability of the hybrid-electric concept and electric propulsion as major ways to improve energy efficiency and reduce the automobile's environmental effects and energy consumption has been demonstrated. The principal features are multiple power sources, an internal combustion engine, an electric motor, an energy storage system and an intelligent control system. This paper also discusses the design of the propulsion systems for automobiles and other transportation products, which is undergoing major changes. The development of EVs and HEVs provide a technology bridge to the electric propulsion technologies needed for the fuel cars (fuel cell hybrid vehicle) of the future. [ABSTRACT FROM PUBLISHER]

Despite their advantages, distributed energy resources (DERs) bring inherent uncertainty and variability into the landscape of modern power systems. As DER penetration grows, conventional generators like hydropower plants have to respond more often to arrest the imbalance in the net load. Hydropower turbines provide their best operational performance with minimal wear and tear when operating at regions of maximum efficiency. However, the current needs for hydropower plants require them to operate under varying load conditions and thus sub-optimal operating points leading to additional stress. To relieve the hydropower plants, this paper proposes a hybridization strategy where a hydropower unit is paired with an energy storage system (ESS) to increase operational flexibility and mitigate damage to the hydro plant. Models are developed to represent the operation of the hybrid system, quantify degradation, and assess economic benefits. Moreover, an innovative controller disaggregates the market dispatch signal into separate control setpoints for the ESS and hydropower unit. In case studies performed on a real-world hydropower facility, it was found that the ESS-based hybridization can extend the life of the hydropower plant by 5% on average. The economic benefits from reduced maintenance and deferred investment are estimated to be around $3.6 million. • A hybridization strategy is proposed to pair energy storage with a hydro plant. • Energy storage helps increase flexibility and mitigate damage to the hydro plant. • Methods are developed to model the hybrid system and quantify degradation effects. • An innovative controller is designed to optimize the set points by component. • Economic benefits from reduced maintenance and deferred investment are assessed. [ABSTRACT FROM AUTHOR]

Nowadays, sustainable navigation is becoming a trending topic not only for merchant ships but also for pleasure vessels such as motoryachts. Therefore, the adoption of a hybrid-electric propulsion system and the installation of on-board storage devices could increase the greenness of a megayacht. This paper analyses the performance of three commercial propulsive solutions, using a dynamic operative profile and considering the influences of the smart berthing infrastructures. Results compare the yearly fuel consumptions of the analysed configurations for a reference megayacht. [ABSTRACT FROM AUTHOR]

Battery equalization is a critical technology in energy storage systems, so that each storage cell has equal state. In the application of electric vehicle, equalization circuits and algorithms have been widely studied for the purpose of prolonging driving time, but optimization of equalization efficiency is a difficult task in the battery equalization of electric vehicle. In this paper, an optimization model with a linear form is proposed to incorporate both energy loss and equalization time for an energy-bus equalizer. In the consideration of different working status of electric vehicle, i.e., charging, discharging, and driving, dynamic equalization has been investigated, and a model predictive control approach is proposed to cope with frequent change of working status. According to simulation and experimental results, it can be concluded that energy and time efficiency can be significantly improved during dynamic battery equalization, and that the proposed equalization system is easily implemented with competitive simplicity due to the linearized system model. [ABSTRACT FROM AUTHOR]

At present, renewable energy installations are expanding to solve both environmental problems and expensive energy fuel import prices in isolated areas. However, in a small-scale power system, rapid output fluctuations of renewable energy may cause power quality problems such as voltage and frequency fluctuations in the power system. To solve this problem, the local government of Jeju Island in South Korea implemented a megawatt (MW)-class pilot project to stabilize the output power of wind turbines using an energy storage system (ESS). In this project, a 0.5 MWh lithium-ion battery was connected to a 3 MW wind turbine via 1 MW power conversion system (PCS). In this paper, the field test results were divided into four categories as follows. First, the performance of stabilizing the output of the wind turbine using ESS was confirmed. Second, the control performance of the ESS was confirmed when the wind turbine suddenly stopped due to an accident. Third, it was confirmed that the ESS discharged energy into the power system after the stabilization of the wind turbine output. Fourth, the reasons for the failure of the ESS to control output stabilization of the wind turbine were analyzed through MATLAB simulation. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal Energy Storage System (ESS) scheduling algorithm Building Energy Management System (BEMS). In particular, the focus is placed on how to reduce the peak load using ESS and load forecast. To this end, first, an existing deep learning-based load forecast method is applied to a real building energy prediction and it is shown that the deep learning-based method leads to an accuracy-enhanced load forecast. Second, an optimization problem is formulated in order to devise an ESS scheduling. In the optimization problem, the objective function and constraints are defined such that the peak load is reduced; the cost for electricity is minimized; and the ESS's lifetime is elongated considering the accuracy-enhanced load forecast, real-time electricity price, and the state-of-charge of the ESS. For the purpose of demonstrating the effectiveness of the proposed ESS scheduling method, it is implemented using a real building load power and temperature data. The simulation results show that the proposed method can reduce the peak load and results in smooth charging and discharging, which is important for the ESS lifetime. [ABSTRACT FROM AUTHOR]

The ever-increasing electricity price and energy consumption in high-speed railway industry push railway companies to seek a promising way to realize their sustainable developments. Making full use of the solar resource along with high-speed railways can be a potential solution to cut the electricity bill, bring more profit to railway companies and realize the decarbonization of high-speed railway industry. This paper studies the optimal planning of distributed photovoltaic generation (DPVG) and energy storage system (ESS) for the traction power supply system (TPSS) of high-speed railway. A quantitative method is proposed to study the time and space characteristics of photovoltaic generation and electricity demand of high-speed trains. An integrated cost-benefit analysis framework is developed to evaluate the effect of DPVG and ESS on the economy of TPSS. To derive the optimal planning scheme and energy management strategy of DPVG and ESS, a mathematical programming model with the objective of minimizing the total cost is proposed to seek the most economical solution. A hybrid global optimal solution approach is developed to solve the model. A real-world case of Beijing-Baoding high-speed railway in China is used to illustrate the capability and characteristics of the proposed model. The computational results show that DPVG is able to supply 32.5 % electricity demand of high-speed trains. The integration of DPVG and ESS can help railway company save 4.2 million CNY each year in Beijing-Baoding high-speed railway. This paper demonstrates the potential and applicability of DPVG and ESS in high-speed railway industry. • A novel distributed photovoltaic generation model is proposed for the traction power supply system of high-speed railway. • A global optimal algorithm is provided to derive the most economical planning scheme and energy-management strategy. • Photovoltaic generation can help Beijing-Baoding high-speed railway save 4.2 million China Yuan each year. • Solar energy is able to supply 32.5% electricity demand of Beijing-Baoding high-speed railway. [ABSTRACT FROM AUTHOR]

The increased usage of renewable energy sources (RESs) and the intermittent nature of the power they provide lead to several issues related to stability, reliability, and power quality. In such instances, energy storage systems (ESSs) offer a promising solution to such related RES issues. Hence, several ESS techniques were proposed in the literature to solve these issues; however, a single ESS does not fulfill all the requirements for certain operations and has different tradeoffs for overall system performance. This is mainly due to the limited capability of a single ESS and the potency concerning cost, lifespan, power and energy density, and dynamic response. In order to overcome the tradeoff issue resulting from using a single ESS system, a hybrid energy storage system (HESS) consisting of two or more ESSs appears as an effective solution. Many studies have been considered lately to develop and propose different HESSs for different applications showing the great advantages of using multiple ESSs in one combined system. Although these individual methods have been well documented, a comprehensive review of HESS-integrated RE has not been fully investigated in the literature before. Thus, as a novel contribution to the literature, this study aims to review and analyze the importance and impact of HESSs in the presence of renewable energy towards sustainable development that will facilitate this newly emerging topic to researchers in this field. In this regard, the present scenario and recent trend of HESSs in RESs at the global level, including a comparison with main ESS features, are discussed and analyzed along with the concept, design, classifications, and a detailed comparison of HESSs. The emerging role of HESSs in terms of their benefits and applications has been analyzed. Recent control and optimization methods of HESSs associated with RESs and their advantages and disadvantages have been reviewed. Finally, open issues and new challenges toward more efficient, sustainable, and green energy have also been highlighted herein. All the highlighted insights of this review will hopefully lead to increased efforts toward the development of an advanced HESS for future renewable energy optimal operation. [ABSTRACT FROM AUTHOR]

The article contains current information on the development of energy-efficient technologies of wind–diesel hybrid systems (WDHS) for decreasing organic fuel consumption. As a result of the review, three research directions are identified: WDHS design optimization, the main equipment and control system improvements. A comparison of their effectiveness is presented. The methods of selecting WDHS configuration, equipment capacities and location, the optimization algorithms and objective functions used are described and WDHS project feasibility calculation results are presented. The methods to improve energy efficiency of WDHS major units' (diesel generator (DG) and wind turbine (WT)) are considered. The methods to decrease diesel fuel consumption using special devices and energy storage system are presented. Special attention is paid to WDHS operating modes' control methods and strategies, as well as to algorithms providing the efficient system operation. As a result, recommendations for the design of both isolated and on-grid WDHS are formulated. [ABSTRACT FROM AUTHOR]

Past studies of microgrids have been based on measurements of fuel consumption by generators under static loads. There is little information on the fuel efficiency of generators under time-varying loads. To help analyze the impact of time-varying loads on optimal generator operation and fuel consumption, we formulate a mixed-integer linear optimization model to plan generator and energy storage system (ESS) operation to satisfy known demands. Our model includes fuel consumption penalty terms on time-varying loads. We exercise the model on various scenarios and compare the resulting optimal fuel consumption and generator operation profiles. Our results show that the change in fuel efficiency between scenarios with the integration of ESS is minimal regardless of the imposed penalty placed on the generator. However, without the assistance of the ESS, the fuel consumption increases dramatically with the penalty imposed on the generator. The integration of an ESS improves fuel consumption because the ESS allows the generator to minimize power output fluctuation. While the presence of a penalty term has a clear impact on generator operation and fuel consumption, the exact type and weight of the penalty appears insignificant; this may provide useful insight for future studies in developing a real-time controller. [ABSTRACT FROM AUTHOR]

Battery-based energy storage systems are forecasted to have a rapid diffusion in the next future, because they can support the diffusion of renewable energy sources and can offer interesting ancillary services for the distribution grid. Consequently, energy management strategies for batteries and inverters present in storage systems will play a fundamental role in order to guarantee effective energy transfer processes between storage systems and the grid. This paper proposes an efficient management strategy which allows maximizing the overall energy efficiency of grid-connected storage systems taking into account the actual relationship between the efficiency and the charging/discharging power of the storage system. The effectiveness of the strategy is as shown by analysis results, the proposed strategy can allow a remarkable efficiency increase compared with strategies which are not aimed at the efficiency optimization. [ABSTRACT FROM AUTHOR]

The use of electric vehicles (EVs) has recently increased in a smart city environment. With this, the optimal location of the charging station is a great challenge and, hence, the energy efficiency performance (EEP) of an electrical system is important. Ideally, the EEP is realized through passive energy boosters (PEBs) and active energy boosters (AEBs). PEBs require no external resources, and EEP is achieved through altering the network topology and loading patterns, whereas, in AEBs, integrating external energy resources is a must. The EEP has also become dynamic with the integration of an energy storage system (ESS) in a deregulated environment. Customer energy requirement varies daily, weekly, and seasonally. In this scenario, the frequent change in network topology requires modifying the size and location of AEBs. It alters the customers' voltage profile, loadability margin, and supply reliability when the EV works differently as a load or source. Therefore, a comprehensive EEP analysis with different probabilistic loading patterns, including ESS, must be performed at the planning stage. This work uses a harmony search algorithm to evaluate EEP for AEBs and PEBs, in coordination, when ESS works as a load or source, at four locations, for customers' and utilities' benefits. [ABSTRACT FROM AUTHOR]

Energy from the sun is weather-dependent. In modern electric grids that is a shortcoming; generation (and load) has to be regulated accordingly. This issue is a cornerstone for an effective transition to a renewable-based energy system. Weather forecast algorithms can predict photovoltaic production but, in real life conditions, their reliability is only partially effective with respect to the actual grid operation requirements. In the paper, Energy Storage Systems are adopted to compensate the mismatch between the injections of a photovoltaic power plant and the day-ahead market power schedule: the final goal is to achieve the full programmability of the photovoltaic resource by minimizing energy imbalances, as defined in the Italian regulatory framework, on an hourly basis. In particular, the optimal design of the storage apparatus (nominal power and capacity) is defined according to the regulating performances required. Moreover, three forecast models are tested to evaluate the impact of weather prediction accuracy on the ESS design. Finally, the benefit/cost ratio of the ESS application is assessed according to the main economic and technical parameters (ESS cost, round trip efficiency, lifespan). The analyses are performed on data measured on a real power plant, with hypotheses consistent with the actual Italian scenario. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal operational scheduling of a reconfigurable multi-microgrid (MG) distribution system complemented by demand response programs and Energy Storage Systems (ESSs) in an uncertain environment. Since there is a set of competing players with inherently conflicting objectives in the system under study such as the Distribution System Operator (DSO) and MG owners, a one-leader multi-follower-type bi-level optimization model is proposed. In this framework, the upper-level player as a leader minimizes the total cost from DSO's point of view, while the lower-level players as multi-followers maximize the profit of MG owners. Since the resulting model is a non-linear bi-level optimization problem, it is transformed into a single-level mixed-integer second-order cone programming problem through Karush–Kuhn–Tucker conditions. The satisfactory performance of the proposed model is investigated on a real-test system under different scenarios and working conditions. [ABSTRACT FROM AUTHOR]

Battery based energy storage system (ESS) has tremendous diversity of application with an intense focus on frequency regulation market. An ESS typically comprised of a battery and a power conversion system. A calculation of performance parameters is performed in this research. The aim is to formulate an in-depth analysis of the ESS in terms of power losses of the semiconductor and electrical devices, efficiency, reliability and cost which would foster various research groups and industries around the globe to improve their future product. In view of this, a relation between the operating conditions and power losses is established to evaluate the efficiency of the system. The power loss calculation presented in this paper has taken into account the conduction and switching losses of the semiconductor devices. Afterwards, the Arrhenius Life Stress relation is adopted to calculate the reliability of the system by considering temperature as a covariate. And finally, a cost calculation is executed and presented as a percentage of total cost of the ESS. It has been found that the power loss and efficiency of the ESS at rated power is 146 kW and 85% respectively. Furthermore, the mean time between failures of the ESS is 8 years and reliability remains at 73% after a year. The major cost impact observed is for battery and PCS as 58% and 16% respectively. Finally, it has been determined that further research is necessary for higher efficient and lower cost system for high penetration of energy storage system in the market. [ABSTRACT FROM AUTHOR]

Abstract: Energy storage systems (ESS) are becoming one of the most important components that noticeably change overall system performance in various applications, ranging from the power grid infrastructure to electric vehicles (EV) and portable electronics. However, a homogeneous ESS is subject to limited characteristics in terms of cost, efficiency, lifetime, etc., by the energy storage technology that comprises the ESS. On the other hand, hybrid ESS (HESS) are a viable solution for a practical ESS with currently available technologies as they have potential to overcome such limitations by exploiting only advantages of heterogeneous energy storage technologies while hiding their drawbacks. However, the HESS concept basically mandates sophisticated design and control to actually make the benefits happen. The HESS architecture should be able to provide controllability of many parts, which are often fixed in homogeneous ESS, and novel management policies should be able to utilize the control features. This paper introduces a complete design practice of a HESS prototype to demonstrate scalability, flexibility, and energy efficiency. It is composed of three heterogenous energy storage elements: lead-acid batteries, lithium-ion batteries, and supercapacitors. We demonstrate a novel system control methodology and enhanced energy efficiency through this design practice. [Copyright &y& Elsevier]

Energy storage systems (ESSs) are envisioned to be more popular during the next decades as part of Smart Grid expansion. Especially, as uncertainty with intermittent resource penetration increases the importance of frequency control reserves (FCRs), ESSs has considered as one of potential resources in FCR provision. ESSs can be very efficient resources for frequency control, which activation time is shorter and more flexible than traditional resources. In this work, we provide a valuation method for ESSs in tertiary reserve resources. We will also explain a brief overview of frequency control services and characteristics of ESSs. An indicative study is presented where the proposed method assesses the value of ESSs from provision in the competitive reserve market. [ABSTRACT FROM AUTHOR]

Energy storage plays a major role in solving the fluctuation and intermittence problem of wind and the effective use of wind power. The application of the hydraulic accumulator is the most efficient and convenient way to store wind energy in hydraulic wind turbines. A hydraulic energy storage generation system (HESGS) can transform hydraulic energy stored in the hydraulic accumulator into stable and constant electrical energy by controlling the variable motor, regardless of wind changes. The aim of the present study is to design a constant speed control method for the variable motor in the HESGS and investigate the influence of the controller's main parameters on the resistance of the HESGS to external load power disturbances. Mathematical equations of all components in this system are introduced and an entire system simulation model is built. A double closed-loop control method of the variable motor is presented within this paper, which keeps the motor speed constant for the fixed frequency of electrical power generated by the HESGS. Ultimately, a series of simulations with different proportional gains and integral gains under the environment of changeless load power step are conducted. At the same time, comparison analyses of the experiment and simulation under variable load power step are performed. The results verify the correctness and the usability of the simulation model, and also indicate that the proposed control method is robust to the disturbances of changing load power. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, along with the progress of modern wind energy technology, the trends of wind energy technology and potential challenges have been studied thoroughly. It is estimated that within the next 2–3 decades, the Vertical Axis Wind Turbine (VAWT) can dominate the wind-energy technology. The VAWT requires less land space and using the same space; it is capable of producing more wind energy than that of its counterpart. By implying the Fish Schooling Concept effectively and successfully, it is possible to advance the wind-energy technology more. In the last 3–4 decades, the wind turbine capacity has been increased around 30–40 times. With the increase of wind energy capacity, the demand of the energy storage system has been increased significantly. Along with the many energy storage systems, fuel cells and batteries are the two most promising devices to meet the demand in RE systems. The wind-energy technology is established itself but not yet fully mature and hence there are many areas where improvements are required to reduce the cost of wind energy. [Copyright &y& Elsevier]