To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust optimization.This approach aims to regulate the energy storage system by using a ...To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust optimization.This approach aims to regulate the energy storage system by using a multi-stage robust optimal control method,which helps overcome the limitations of traditional methods in terms of time scale.The goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the day.To achieve this,a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind power.The generalized Benders Decomposition method is then employed to solve the multi-stage objective optimization problem.By decomposing the problem into a series of sub-objectives,the system scale is effectively reduced,and the algorithm’s convergence ability is improved.Compared with other algorithms,the multi-stage robust optimization model has better economy and convergence ability and can be used to guide the power dispatching of uncertain energy and energy storage systems.展开更多
Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink...Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.展开更多
The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and v...The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.展开更多
In this paper, a reinforcement learning-based multibattery energy storage system(MBESS) scheduling policy is proposed to minimize the consumers ’ electricity cost. The MBESS scheduling problem is modeled as a Markov ...In this paper, a reinforcement learning-based multibattery energy storage system(MBESS) scheduling policy is proposed to minimize the consumers ’ electricity cost. The MBESS scheduling problem is modeled as a Markov decision process(MDP) with unknown transition probability. However, the optimal value function is time-dependent and difficult to obtain because of the periodicity of the electricity price and residential load. Therefore, a series of time-independent action-value functions are proposed to describe every period of a day. To approximate every action-value function, a corresponding critic network is established, which is cascaded with other critic networks according to the time sequence. Then, the continuous management strategy is obtained from the related action network. Moreover, a two-stage learning protocol including offline and online learning stages is provided for detailed implementation in real-time battery management. Numerical experimental examples are given to demonstrate the effectiveness of the developed algorithm.展开更多
Improving the capacitance and energy density is a significant challenge while developing practical and flexible energy storage system(ESS).Redox mediators(RMs),as redox-active electrolyte additives,can provide additio...Improving the capacitance and energy density is a significant challenge while developing practical and flexible energy storage system(ESS).Redox mediators(RMs),as redox-active electrolyte additives,can provide additional energy storing capability via electrochemical faradaic contribution on electrodes for high-performance flexible ESSs.Particularly,determining effective material combinations between electrodes and RMs is essential for maximizing surface faradaic redox reactions for energy-storage performance.In this study,an electrode-RM system comprising heterostructured hybrid(carbon fiber(CF)/MnO_(2)) faradaic electrodes and iodine RMs(I-RMs) in a redox-active electrolyte is investigated.The CF/MnO_(2)with the 1-RMs(CF/MnO_(2)-I) induces dominant catalytic faradaic interaction with the I-RMs,significantly enhancing the surface faradaic kinetics and increasing the overall energy-storage performance.The CF/MnO_(2)-I ESSs show a 12.6-fold(or higher) increased volumetric energy density of 793.81 mWh L^(-1)at a current of 10 μA relative to ESSs using CF/MnO_(2)without I-RMs(CF/MnO_(2)).Moreover,the CF/MnO_(2)-I retains 93.1% of its initial capacitance after 10,000 cycles,validating the excellent cyclability.Finally,the flexibility of the ESSs is tested at different bending angles(180° to 0°),demonstrating its feasibility for flexible and high-wear environments.Therefore,CF/MnO_(2)electrodes present a practical material combination for high-performance flexible energy-storage devices owing to the catalytic faradaic interaction with I-RMs.展开更多
Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of ...Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of the power systems.In order to achieve effective forecasting outcomes with minimumcomputation time,this study develops an improved whale optimization with deep learning enabled load prediction(IWO-DLELP)scheme for energy storage systems(ESS)in smart grid platform.The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS.The proposed IWO-DLELP model initially undergoes pre-processing in two stages namely min-max normalization and feature selection.Besides,partition clustering approach is applied for the decomposition of data into distinct clusters with respect to distance and objective functions.Moreover,IWO with bidirectional gated recurrent unit(BiGRU)model is applied for the prediction of load and the hyperparameters are tuned by the use of IWO algorithm.The experiment analysis reported the enhanced results of the IWO-DLELP model over the recent methods interms of distinct evaluation measures.展开更多
This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure o...This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.展开更多
Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the...Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.展开更多
In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the ...In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the energy storage is taken into consideration,then,the charge-discharge strategy for this equipment is determined.Here,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)are used to calculate the minimum and maximum load in the network with the presence of energy storage systems.The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach.Ultimately,the battery charge-discharge is managed at any time during the day,considering the load consumption at each hour.The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes.This shows the significance of such matters in terms of economy and technicality.展开更多
The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manag...The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).展开更多
The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while ...The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while meeting the total charging/discharging power requirement is formulated and solved as a distributed control problem.Conditions on the communication topology among the battery units are established under which a control law is designed for each battery unit to solve the control problem based on distributed average reference power estimators and distributed average unit state estimators.Two types of estimators are proposed.One achieves asymptotic estimation and the other achieves finite time estimation.We show that,under the proposed control laws,SoC balancing of all battery units is achieved and the total charging/discharging power of the BESS tracks the desired power.A simulation example is shown to verify the theoretical results.展开更多
With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role ...With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role in renewable energy integration.In this paper,a distributed virtual synchronous generator(VSG)control method for a battery energy storage system(BESS)with a cascaded H-bridge converter in a grid-connected mode is proposed.The VSG is developed without communication dependence,and state-of-charge(SOC)balancing control is achieved using the distributed average algorithm.Owing to the low varying speed of SOC,the bandwidth of the distributed communication networks is extremely slow,which decreases the cost.Therefore,the proposed method can simultaneously provide inertial support and accurate SOC balancing.The stability is also proved using root locus analysis.Finally,simulations under different conditions are carried out to verify the effectiveness of the proposed method.展开更多
The current energy trend indicates a strong thrust toward transforming renewable energy as a major power source.To achieve this mission,battery energy storage systems(BESSs)are indispensable.Although BESSs are expensi...The current energy trend indicates a strong thrust toward transforming renewable energy as a major power source.To achieve this mission,battery energy storage systems(BESSs)are indispensable.Although BESSs are expensive,cost reduction can be achieved by using BESSs for multiple purposes,such as load leveling,business continuity planning,frequency control,capacity market,arbitrage,and emergency power.In this paper,various applications of BESSs are classified.The possibility of achieving conflict-free combination of different applications is demonstrated.The total required energy storage capacity in Japan is estimated to be 150–200 GWh by 2030.The present status of NaS batteries for multipurpose use and new trends in battery-based businesses are introduced.展开更多
Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based en...Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.展开更多
Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribu...Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.展开更多
Energy storage system is an important means to improve the flexibility and safety of traditional power system,but it has the problem of high cost and unclear value recovery path.In this paper,the typical application s...Energy storage system is an important means to improve the flexibility and safety of traditional power system,but it has the problem of high cost and unclear value recovery path.In this paper,the typical application scenarios of energy storage system are summarized and analyzed from the perspectives of user side,power grid side and power generation side.Based on the typical application scenarios,the economic benefit assessment framework of energy storage system including value,time and efficiency indicators is proposed.Typical battery energy storage projects are selected for economic benefit calculation according to different scenarios,and key factors are selected for sensitivity analysis.Finally,the key factors affecting economic benefit of the energy storage system are analyzed.展开更多
Permanent magnet homopolar inductor machine(PMHIM) has attracted much attention in the field of flywheel energy storage system(FESS) due to its merits of simple structure,brushless excitation, and rotor flywheel integ...Permanent magnet homopolar inductor machine(PMHIM) has attracted much attention in the field of flywheel energy storage system(FESS) due to its merits of simple structure,brushless excitation, and rotor flywheel integration. However, the air-gap flux generated by the PM cannot be adjusted, which would cause large electromagnetic losses in the standby operation state of FESS. To solve this problem, a novel mechanically adjusted variable flux permanent magnet homopolar inductor machine with rotating magnetic poles(RMP-PMHIM) is proposed in this paper. The permanent magnet poles are rotated by an auxiliary rotating device and the purpose of changing the air-gap flux is achieved. First, the structure and operation principle of the proposed RMP-PMHIM are explained. Second,the flux weakening principle of the RMP-PMHIM is analyzed and the equivalent magnetic circuit models under different flux weakening states are built. Third, the parameters of the PM and its fixed structure are optimized to obtain the good electromagnetic performance. Fourth, the electromagnetic performance, including the air-gap flux density, back-EMF, flux weakening ability, loss, etc. of the proposed RMP-PMHIM are investigated and compared. Compared with the non-rotating state of the PM of RPM-PMHIM, the air-gap flux density amplitude can be weakened by 99.95% when the PM rotation angle is 90 degrees, and the no-load core loss can be suppressed by 99.98%,which shows that the proposed RPM-PMHIM is a good candidate for the application of FESS.展开更多
In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configurat...In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configuration and optimization. Based on the most promising battery energy storage technology, this paper introduces the current status of the grid technology, the application of large-scale energy storage technology and the supporting role of battery energy storage for GEI. Based on several key technologies of large-scale battery energy storage system, preliminary analysis of the standard system construction of energy storage system is made, and the future prospect is put forward.展开更多
Battery energy storage systems(ESS) have been widely used in mobile base stations(BS) as the main backup power source. Due to the large number of base stations, massive distributed ESSs have largely stayed in idle and...Battery energy storage systems(ESS) have been widely used in mobile base stations(BS) as the main backup power source. Due to the large number of base stations, massive distributed ESSs have largely stayed in idle and very difficult to achieve high asset utilization. In recent years, the fast-paced development of digital energy storage(DES) technology has revolutionized the traditional operation and maintenance of ESSs by transforming them into digital assets, further enabling battery energy storage services, raising up a new way to achieve a much higher utilization of such kind of largely idle ESS resources. In this paper, the disruptive DES technology will be introduced and its application under the context of mobile BSs will be studied, and then a cloud-based energy storage(CES) platform is proposed based on a large scale distributed DESs to provide a new cyber-enabled energy storage service to the local utility company. A real-world case study shows the effectiveness and efficiency of the CES platform.展开更多
文摘To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust optimization.This approach aims to regulate the energy storage system by using a multi-stage robust optimal control method,which helps overcome the limitations of traditional methods in terms of time scale.The goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the day.To achieve this,a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind power.The generalized Benders Decomposition method is then employed to solve the multi-stage objective optimization problem.By decomposing the problem into a series of sub-objectives,the system scale is effectively reduced,and the algorithm’s convergence ability is improved.Compared with other algorithms,the multi-stage robust optimization model has better economy and convergence ability and can be used to guide the power dispatching of uncertain energy and energy storage systems.
文摘Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.
基金supported by the Science and Technology Support Program of Guizhou Province([2022]General 012)the Key Science and Technology Project of China Southern Power Grid Corporation(GZKJXM20220043)。
文摘The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.
基金supported by the National Key R&D Program of China (2018AAA0101400)the National Natural Science Foundation of China (61921004,62173251,U1713209,62236002)+1 种基金the Fundamental Research Funds for the Central UniversitiesGuangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control。
文摘In this paper, a reinforcement learning-based multibattery energy storage system(MBESS) scheduling policy is proposed to minimize the consumers ’ electricity cost. The MBESS scheduling problem is modeled as a Markov decision process(MDP) with unknown transition probability. However, the optimal value function is time-dependent and difficult to obtain because of the periodicity of the electricity price and residential load. Therefore, a series of time-independent action-value functions are proposed to describe every period of a day. To approximate every action-value function, a corresponding critic network is established, which is cascaded with other critic networks according to the time sequence. Then, the continuous management strategy is obtained from the related action network. Moreover, a two-stage learning protocol including offline and online learning stages is provided for detailed implementation in real-time battery management. Numerical experimental examples are given to demonstrate the effectiveness of the developed algorithm.
基金supported by the National Research Foundation of Korea grant funded by the Korean government (MSIT)(2020R1A2C1101039)the Commercializations Promotion Agency for R&D Outcomes (COMPA) grant funded by the Korea government(MSIT)(2021E200)+1 种基金supported by“Regional Innovation Strategy (RIS)” through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(MOE)(2021RIS-004)supported by the Soonchunhyang University Research Fund。
文摘Improving the capacitance and energy density is a significant challenge while developing practical and flexible energy storage system(ESS).Redox mediators(RMs),as redox-active electrolyte additives,can provide additional energy storing capability via electrochemical faradaic contribution on electrodes for high-performance flexible ESSs.Particularly,determining effective material combinations between electrodes and RMs is essential for maximizing surface faradaic redox reactions for energy-storage performance.In this study,an electrode-RM system comprising heterostructured hybrid(carbon fiber(CF)/MnO_(2)) faradaic electrodes and iodine RMs(I-RMs) in a redox-active electrolyte is investigated.The CF/MnO_(2)with the 1-RMs(CF/MnO_(2)-I) induces dominant catalytic faradaic interaction with the I-RMs,significantly enhancing the surface faradaic kinetics and increasing the overall energy-storage performance.The CF/MnO_(2)-I ESSs show a 12.6-fold(or higher) increased volumetric energy density of 793.81 mWh L^(-1)at a current of 10 μA relative to ESSs using CF/MnO_(2)without I-RMs(CF/MnO_(2)).Moreover,the CF/MnO_(2)-I retains 93.1% of its initial capacitance after 10,000 cycles,validating the excellent cyclability.Finally,the flexibility of the ESSs is tested at different bending angles(180° to 0°),demonstrating its feasibility for flexible and high-wear environments.Therefore,CF/MnO_(2)electrodes present a practical material combination for high-performance flexible energy-storage devices owing to the catalytic faradaic interaction with I-RMs.
文摘Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of the power systems.In order to achieve effective forecasting outcomes with minimumcomputation time,this study develops an improved whale optimization with deep learning enabled load prediction(IWO-DLELP)scheme for energy storage systems(ESS)in smart grid platform.The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS.The proposed IWO-DLELP model initially undergoes pre-processing in two stages namely min-max normalization and feature selection.Besides,partition clustering approach is applied for the decomposition of data into distinct clusters with respect to distance and objective functions.Moreover,IWO with bidirectional gated recurrent unit(BiGRU)model is applied for the prediction of load and the hyperparameters are tuned by the use of IWO algorithm.The experiment analysis reported the enhanced results of the IWO-DLELP model over the recent methods interms of distinct evaluation measures.
基金supported by the State Grid Science and Technology Project (No.52999821N004)。
文摘This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.
基金support by Ministry of Housing and Urban-Rural Development’s Science and Technology Plan Project 2022(Hubei Province).
文摘Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.
基金supported in part by an International Research Partnership“Electrical Engineering-Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universitéd’Excellence(LUE)in cooperation between Universitéde Lorraine and King Mongkut’s University of Technology North Bangkok and in part by the National Research Council of Thailand(NRCT)under Senior Research Scholar Program under Grant No.N42A640328.
文摘In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the energy storage is taken into consideration,then,the charge-discharge strategy for this equipment is determined.Here,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)are used to calculate the minimum and maximum load in the network with the presence of energy storage systems.The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach.Ultimately,the battery charge-discharge is managed at any time during the day,considering the load consumption at each hour.The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes.This shows the significance of such matters in terms of economy and technicality.
文摘The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).
基金relates to Department of Navy award(N00014-20-1-2858)。
文摘The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while meeting the total charging/discharging power requirement is formulated and solved as a distributed control problem.Conditions on the communication topology among the battery units are established under which a control law is designed for each battery unit to solve the control problem based on distributed average reference power estimators and distributed average unit state estimators.Two types of estimators are proposed.One achieves asymptotic estimation and the other achieves finite time estimation.We show that,under the proposed control laws,SoC balancing of all battery units is achieved and the total charging/discharging power of the BESS tracks the desired power.A simulation example is shown to verify the theoretical results.
基金This work was supported by National Natural Science Foundation of China under Grant U1909201,Distributed active learning theory and method for operational situation awareness of active distribution network.
文摘With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role in renewable energy integration.In this paper,a distributed virtual synchronous generator(VSG)control method for a battery energy storage system(BESS)with a cascaded H-bridge converter in a grid-connected mode is proposed.The VSG is developed without communication dependence,and state-of-charge(SOC)balancing control is achieved using the distributed average algorithm.Owing to the low varying speed of SOC,the bandwidth of the distributed communication networks is extremely slow,which decreases the cost.Therefore,the proposed method can simultaneously provide inertial support and accurate SOC balancing.The stability is also proved using root locus analysis.Finally,simulations under different conditions are carried out to verify the effectiveness of the proposed method.
文摘The current energy trend indicates a strong thrust toward transforming renewable energy as a major power source.To achieve this mission,battery energy storage systems(BESSs)are indispensable.Although BESSs are expensive,cost reduction can be achieved by using BESSs for multiple purposes,such as load leveling,business continuity planning,frequency control,capacity market,arbitrage,and emergency power.In this paper,various applications of BESSs are classified.The possibility of achieving conflict-free combination of different applications is demonstrated.The total required energy storage capacity in Japan is estimated to be 150–200 GWh by 2030.The present status of NaS batteries for multipurpose use and new trends in battery-based businesses are introduced.
基金supported by the National Natural Science Foundation of China(61673164)the Natural Science Foundation of Hunan Province(2020JJ6024)the Scientific Research Fund of Hunan Provincal Education Department(19K025).
文摘Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.
文摘Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.
基金supported by State Grid Zhejiang Electric Power Co.,Ltd.(Project of Research on interactive operation control technology and business model of 5G base station energy storage and power grid(B311JX210006)).
文摘Energy storage system is an important means to improve the flexibility and safety of traditional power system,but it has the problem of high cost and unclear value recovery path.In this paper,the typical application scenarios of energy storage system are summarized and analyzed from the perspectives of user side,power grid side and power generation side.Based on the typical application scenarios,the economic benefit assessment framework of energy storage system including value,time and efficiency indicators is proposed.Typical battery energy storage projects are selected for economic benefit calculation according to different scenarios,and key factors are selected for sensitivity analysis.Finally,the key factors affecting economic benefit of the energy storage system are analyzed.
基金supported in part by the National Natural Science Foundation of China under Grant 52007055in part by the Natural Science Foundation of Hunan Province of China under Grant 2021JJ40099。
文摘Permanent magnet homopolar inductor machine(PMHIM) has attracted much attention in the field of flywheel energy storage system(FESS) due to its merits of simple structure,brushless excitation, and rotor flywheel integration. However, the air-gap flux generated by the PM cannot be adjusted, which would cause large electromagnetic losses in the standby operation state of FESS. To solve this problem, a novel mechanically adjusted variable flux permanent magnet homopolar inductor machine with rotating magnetic poles(RMP-PMHIM) is proposed in this paper. The permanent magnet poles are rotated by an auxiliary rotating device and the purpose of changing the air-gap flux is achieved. First, the structure and operation principle of the proposed RMP-PMHIM are explained. Second,the flux weakening principle of the RMP-PMHIM is analyzed and the equivalent magnetic circuit models under different flux weakening states are built. Third, the parameters of the PM and its fixed structure are optimized to obtain the good electromagnetic performance. Fourth, the electromagnetic performance, including the air-gap flux density, back-EMF, flux weakening ability, loss, etc. of the proposed RMP-PMHIM are investigated and compared. Compared with the non-rotating state of the PM of RPM-PMHIM, the air-gap flux density amplitude can be weakened by 99.95% when the PM rotation angle is 90 degrees, and the no-load core loss can be suppressed by 99.98%,which shows that the proposed RPM-PMHIM is a good candidate for the application of FESS.
基金supported by National Key R&D Program of China(2017YFB0903504)
文摘In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configuration and optimization. Based on the most promising battery energy storage technology, this paper introduces the current status of the grid technology, the application of large-scale energy storage technology and the supporting role of battery energy storage for GEI. Based on several key technologies of large-scale battery energy storage system, preliminary analysis of the standard system construction of energy storage system is made, and the future prospect is put forward.
基金partly supported by the National Key R&D Program of China under the granted No. 2018YFC1902202.
文摘Battery energy storage systems(ESS) have been widely used in mobile base stations(BS) as the main backup power source. Due to the large number of base stations, massive distributed ESSs have largely stayed in idle and very difficult to achieve high asset utilization. In recent years, the fast-paced development of digital energy storage(DES) technology has revolutionized the traditional operation and maintenance of ESSs by transforming them into digital assets, further enabling battery energy storage services, raising up a new way to achieve a much higher utilization of such kind of largely idle ESS resources. In this paper, the disruptive DES technology will be introduced and its application under the context of mobile BSs will be studied, and then a cloud-based energy storage(CES) platform is proposed based on a large scale distributed DESs to provide a new cyber-enabled energy storage service to the local utility company. A real-world case study shows the effectiveness and efficiency of the CES platform.
