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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]

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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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]

The composition of worldwide energy consumption is undergoing tremendous changes due to the consumption of non-renewable fossil energy and emerging global warming issues. Renewable energy is now the focus of energy development to replace traditional fossil energy. Energy storage system (ESS) is playing a vital role in power system operations for smoothing the intermittency of renewable energy generation and enhancing the system stability. We divide ESS technologies into five categories, mainly covering their development history, performance characteristics, and advanced materials. Biomass storage and gas storage are also discussed, which are not considered in most reviews. After detailed research, the rapid development of each technology in recent years is introduced, and some representative research works are surveyed. We comprehensively summarized the advantages and disadvantages of various ESS technologies and presented several evaluation indicators for quantitative analysis. Hybrid ESS is also considered based on the complex market demand. Then, we investigate the applications of various ESS technologies as short-term, medium-term, and long-term storages in power systems, covering the power generation, transmission and distribution, and end-user. Finally, this paper reviews global developing trends, and identifies critical challenges and promising opportunities. • Comprehensively review five types of energy storage technologies. • Introduce the performance features and advanced materials of diverse energy storages. • Investigate the applications of various energy storage technologies. [ABSTRACT FROM AUTHOR]

Energy storage system of extended-range electric vehicle faces great challenges in working efficiency and energy utilization to meet the requirement of various working conditions of vehicle, efficient ultra-capacitor/battery hybrid power source is an effective way to tackle these challenges. This paper takes an ultra-capacitor/battery hybrid power source based on series-parallel switchover technology of ultra-capacitors as the research object, launches a fundamental study on its operation principle, control method and simulation/experimental verification. A significative series-parallel switchover technology of ultra-capacitors is adopted to achieve variable-voltage output of the hybrid power source, which overcomes the technical limitation of the existing hybrid power source with only a fixed working voltage output, enables the voltage-conversion ratio of the power converter to be controlled in a highly efficient range. The bi-directional four working modes of the hybrid power source that can fit the various working conditions of vehicle are analyzed. Following this, an incremental digital PID controller suitable for this energy storage system is presented. After that, a comprehensive comparison and analysis of the simulation and small-power experiment based on the simulated working conditions of vehicle are performed. The results have verified the feasibility and effectiveness of the proposed hybrid power source and its control method. • An advanced hybrid power source for extended-range electric vehicle is presented. • Proposed scheme effectively breaks the technical limitations of existing topologies. • Response characteristics of the hybrid power source are verified by simulation/test. • The designed scheme has good versatility for other types of new energy vehicles. [ABSTRACT FROM AUTHOR]

Recent works on self-charging power technologies mainly focused on the low energy harvesting component, while its integration with the energy storage system was usually not further evaluated or discussed. This was addressed in the present work by providing a comprehensive state-of-the-art review on different types of energy storage used for self-sufficient or self-sustainable power units to meet the power demands of low power devices such as wearable devices, wireless sensor networks, portable electronics, and LED lights within the range of 4.8 mW–13 W. The paper presents the relevant scientific studies and recent developments on incorporating low energy harvesting with energy storage and power management systems. Recent advances on seven types of low energy harvesting technologies or transducers and eight types of micro/small-scale energy storage systems from farads to amps were examined to assess the integrated design's overall efficiency. The study focused on the design, distribution management networks, efficiency, compatibility with other components, costs, and environmental impact of self-sustainable power unit. To effectively assess the most suitable energy storage for the self-charging power unit, assessing its technical characteristics, economical, and environmental impact is discussed. Finally, the review identified the challenges and further research that must be carried out to achieve a more sustainable and stable integrated technology, moving from the proof of concept or laboratory to actual applications. • There is a lack of literature evaluating both/combined low energy harvesting and storage. • Recent advances on seven types of low energy harvesting technologies were examined. • Eight types of micro/small-scale energy storage systems for energy harvesting were examined. • Assessment of integrated design of low power energy harvesting, energy storage, and power management. • Techno-economic analysis, environmental impacts of low energy storage were discussed. [ABSTRACT FROM AUTHOR]

The development of electricity retailers with energy storage systems expands the energy use ways of users, promotes the consumption of clean energy power generation, and facilitates the development of electricity market. However, due to the imperfect trading mechanism and uncertainties of power supply and demand, the business risk continues to be large, which leads to limited sustainable development of electricity retailers. Therefore, based on the design of a trading mechanism of electricity retailers with energy storage systems in the electricity market, this paper constructs a multi-objective stochastic optimization model of the retailers' flexible purchase of electricity, aiming at minimizing the cost of electricity retailers and maximizing the consumption of clean energy power generation. In the model, the uncertainty of supply and demand and the demand response are taken into consideration. The results show that: (1) Compared with the conventional optimization model, considering the uncertainty in the medium-and-long-term electricity trading, although the demand for clean energy is reduced, the retail cost of temporary electricity in the day-ahead trading is also reduced. (2) The retailers make full use of flexible power charging and discharging, so the extra cost of purchasing electricity in the day-ahead trading caused by the uncertainty of clean energy is reduced via the energy storage demand response. (3) A price-based demand response can change the electricity purchase demand of retailers, improve the transaction volume between retailers and clean power enterprises in the medium-and-long-term electricity trading, and reduce the energy purchase cost while improving the consumption of clean energy power generation. (4) Due to the impact of initial investment cost and other factors, there is no obvious linear relationship between the capacity of energy storage systems and the reduction of retail energy purchase cost; therefore, it is necessary to apply energy storage systems reasonably to achieve the optimal economic benefits. • The trading strategy for ER-ESS participating in electricity market is formulated. • The energy storage and price-based demand response models are constructed. • The respective solving algorithms for the regular and uncertainty model are built. [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]

• A multi-objective renewable energy management scheme is proposed. • Cost saving, green consumption and power quality are the main motivations. • A novel multi-agent system with three electricity use mode is developed. • Key implications and recommendations for policy makers are given. This paper proposes a multi-objective renewable energy management scheme to satisfy the needs of diversified community power consumers, wherein the multi-agent system is employed for coordinating and controlling the power generation and consumption units. Firstly, a multi-agent based microgrid and home energy management system is constructed. Subsequently, system models for renewable energy sources, electrical vehicles, residential loads and the cost function are constructed to form the microgrid operation constraints. With these constraints, three optimization models are proposed to minimize the electricity bills, the power purchased from the main grid, and optimize the power quality. The three objectives are proposed to reflect the power consumer's needs for cost saving, green consumption, and power reliability, respectively. Meanwhile, a coordination strategy which balances the three objectives is proposed. After that, a novel multi agent system is proposed to realize the proposed objectives. Four case studies and a sensitivity analysis are conducted to verify the effectiveness of the proposed method. The case study results show that: in electricity minimization, 2–6.5% of total electricity bills can be saved; in main grid power consumption minimization, the peaks of the power consumption profiles are shaved while the valleys of the profiles are filled; in power quality enhancement, the steady state frequency drop is reduced for 0.35 Hz to 0.38 Hz. The sensitivity analysis shows that communities equipped with energy storage systems accounting for 30% of the total load can achieve best optimization outcomes; the increase in renewable energy usage will lead to higher electricity bills and poorer power quality if the renewable energy sources are limited, while the availability of more renewable energy sources will compensate for the negative effects of using renewable energy sources. [ABSTRACT FROM AUTHOR]

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]

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]

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]