This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking(MPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comp...This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking(MPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comparative study in terms of the dynamic response,battery state of charge(SOC),and oscillations around the Maximum Power Point(MPP)of the PV-BSS to variations in climate conditions,these techniques are simulated in Matlab/Simulink.The introduced methodologies are classified into two types;the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb&Observe and Incremental Conductance techniques.The second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre-build Adaptive Neuro-Fuzzy Inference System(ANFIS)model to predict DC–DC converter optimum duty cycle to track MPP.Then evaluation study is introduced for conventional and proposed On-Line MPPT techniques.This comparative study can be useful in specifying the appropriateness of the MPPT techniques for PV-BSS.Also the introduced model can be used as a valued reference model for future research related to Soft Computing(SC)MPPT techniques.A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.展开更多
This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater pene...This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.展开更多
This study introduces a novel deep reinforcement learning(DRL)framework for the joint dispatch of Gas Turbines(GTs)and Battery Energy Storage Systems(BESs)in microgrids that face the variability of renewable energy so...This study introduces a novel deep reinforcement learning(DRL)framework for the joint dispatch of Gas Turbines(GTs)and Battery Energy Storage Systems(BESs)in microgrids that face the variability of renewable energy sources and demands.BESs can store surplus renewable energy for nearly instantaneous use,while GTs offer sustained energy output over longer periods,offering complementary benefits.Previous studies often oversimplified GT operations,neglecting critical factors such as ramp-up times and increased degradation from frequent starts.This research addresses these gaps by proposing an advanced modeling framework that accurately captures the dynamic interaction between GTs and BESs,including GT ramp-up times and maintenance costs associated with operational cycles.Through extensive case studies involving diverse microgrid configurations,we demonstrate that DRL effectively learns dispatch policies directly from historical data,outperforming traditional optimization techniques.Deploying DRL to our framework yields more realistic dispatch policies,reducing GT maintenance costs by avoiding frequent starts.The proposed framework has significant potential to improve energy management strategies and to streamline the planning of hybrid energy systems.To encourage further research,we have released our codebase to the public,enabling the scientific community to build upon our findings.展开更多
Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequ...Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequate heat dissipation during their discharge process can significantly degrade battery performance.The improvement of BESS efficiency depends on the optimization of thermal management structures.In this work,we integrate the pseudo-two-dimensional(P2D)electrochemical model with a three-dimensional thermal model to analyze the heat generation and transfer processes within the BESS.The simulation results are closely aligned with the experimental results in terms of voltage and temperature rise curves.Under air cooling conditions of 293.15 K and 3 m·s^(-1),the BESS has a maximum temperature of 308.60 K and a temperature difference of 9.22 K,ensuring safe operation.At 1 C,we suggest that enlarging the inlet and outlet areas improves the air-cooling efficiency,and transitioning environmental air-cooling temperatures after 2400 s of discharge effectively reduces the temperature difference and the energy consumption of the cooling equipment.This work provides valuable theoretical insights for optimizing the thermal design of BESS.展开更多
The development of microgrid systems forces to integration of various distributed generators(DG)and battery energy storage(BES)systems.The integration of a BES system in MG provides several benefits such as fast respo...The development of microgrid systems forces to integration of various distributed generators(DG)and battery energy storage(BES)systems.The integration of a BES system in MG provides several benefits such as fast response,short-term power supply,improved power quality,ancillary service,and arbitrage.The system constraints as power balance and the assets constraints as power limit of different DGs,energy,and charge/discharge power limit of BES increase the complexity of the original problem.Therefore,to tackle such a problem an efficient,robust,and strong optimization algorithm is required.In this paper,a recently developed optimization method known as the wild geese algorithm(WGA)has been applied to solve the problem.The WGA is a population-based metaheuristic approach inspired by the different aspects of the living behavior of wild geese.This algorithm has developed with the inspiration of different phases of wild geese's lives,such as their evolution,well-organized and coordinated long-distance group migration,and fatality.The WGA has tested on the MG problem and the obtained simulation results are validated by comparison of results obtained from the other methods.The result shows the WGA is efficiently able to handle the MG operational problem with numerous constraints and shows the potential to produce a high-quality solution in terms of cost reduction.The incorporation of BES reduces operating costs for MG's off-grid and on-grid operational modes by 5.91%and 8.62%,respectively.Further,the analysis for off-grid mode under different seasonality,reduction in the operational cost by 4.47%,9.28%,6.37%,and 7.22%was measured in the summer,autumn,winter,and spring seasons,respectively,with the integration of BES.Additionally,the integration of BES in on-grid mode results in a decrease in operating costs by 7.15%,12.54%,7.56%,and 11.07%in the summer,autumn,winter,and spring,respectively.展开更多
The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
With the continuous emergence of new energy storage technology innovation in the field of electrochemical energy storage in China,different megawatt-grade lithium-ion battery energy storage projects have been implemen...With the continuous emergence of new energy storage technology innovation in the field of electrochemical energy storage in China,different megawatt-grade lithium-ion battery energy storage projects have been implemented,promoting the high-quality development of the energy storage industry.In the context of vigorously promoting the energy consumption revolution and enhancing the green transformation and development momentum,strengthening the safety construction of lithium-ion battery energy storage is of great importance to realize the transformation of energy structure and improve the utilization efficiency of renewable energy.However,in recent years,frequent safety accidents of lithium-ion battery energy storage power stations,such as fires,have aroused the public’s high attention to the construction of lithium-ion battery energy storage power stations,affecting the large-scale development of energy storage power stations.Based on this,this paper analyzes the safety risks of lithium-ion battery energy storage power stations and focuses on how to improve their safety performance.展开更多
At present,the power system is more inclined towards disturbances,such as voltage variations and unbalanced load conditions,due to the grid's complexity and load growth.These challenges emphasize the integration o...At present,the power system is more inclined towards disturbances,such as voltage variations and unbalanced load conditions,due to the grid's complexity and load growth.These challenges emphasize the integration of the compensating devices,such as battery storage(BS)and D-STATCOMs.In this regard,this current paper exhibits a novel energy management system(EMS)of a combined BS and D-STATCOM to compensate the power system during disturbances.The EMS is based on a fractional order sliding mode control(FOSMC)to drive the voltage source converters(VSCs)such that the active power is independently absorbed/injected by the BS,whereas the reactive power is independently absorbed/injected by the D-STATCOM depending upon the disturbance situation.FOSMC is a robust non-linear controller in which the Riemann-Liouville(RL)function is employed to design the sliding surface and the exponential reaching law is used to minimize the chattering phenomenon.The stability of the FOSMC in the proposed EMS is proved using the Lyapunov candidate function.In order to validate the performance of the proposed EMS,a model of a 400 V,180 kVA radial distributor along with a BS and D-STATCOM is simulated in MATLAB/Simulink environment in two test cases.The results prove that the proposed EMS with FOMSC effectively compensates the power system under voltage variations and unbalanced load conditions with rapid tracking,fast convergence and upright damping.Furthermore,the results have been compared with the classical proportional integral(PI)control and fixed frequency SMC(FFSMC),and they demonstrate the superiority of the proposed EMS with FOSMC in power system applications.展开更多
Distributed generation(DG)are critical components for active distribution system(ADS).However,this may be a serious impact on power system due to their volatility.To this problem,interactive load and battery storage m...Distributed generation(DG)are critical components for active distribution system(ADS).However,this may be a serious impact on power system due to their volatility.To this problem,interactive load and battery storage may be a best solution.This paper firstly investigates operation characteristics of interactive load and battery storage,including operation flexibility,inter-temporal operation relations and active-reactive power relations.Then,a multi-period coordinated activereactive scheduling model considering interactive load and battery storage is proposed in order to minimize overall operation costs over a specific duration of time.The model takes into accounts operation characteristics of interactive load and battery storage and focuses on coordination between DGs and them.Finally,validity and effectiveness of the proposed model are demonstrated based on case study of a medium-voltage 135-bus distribution system.展开更多
To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertai...To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertainty of daily cycling load prompts the need to design a new cost function which is able to quantify the associated uncertainty.By modelling a probabilistic dependence among flow,load,and electricity tariffs,the expected cost function is obtained and used in the constrained optimization.The proposed control strategy explicitly incorporates the cycling nature of customer load.Furthermore,for daily cycling load,a fixed-end time and a fixed-end output problem are addressed.It is demonstrated that the proposed control strategy is a convex optimization problem.While stochastic and robust model predictive controllers evaluate the cost concerning model constraints and parameter variations.Also,the expected cost across the flow variations is considered.The density function of load probability improves load prediction over a progressive prediction horizon,and a nonlinear battery model is utilized.展开更多
This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emerg...This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.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 upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged...The upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged stable and efficient operation of the power system.Battery energy storage systems(BESSs)have been identified as critical to mitigate random fluctuations,unnecessary green energy curtailment and load shedding with rapid response and flexible connection.On the other hand,an AC/DC hybrid distribution system can offer merged benefits in both AC and DC subsystems without additional losses during AC/DC power conversion.Therefore,configuring BESSs on an AC/DC distribution system is wellpositioned to meet challenges brought by carbon reductions in an efficient way.A bi-level optimization model of BESS capacity allocation for AC/DC hybrid distribution systems,considering the flexibility of voltage source converters(VSCs)and power conversion systems(PCSs),has been established in this paper to address the techno-economic issues that hindered wide implementation.The large-scale nonlinear programming problem has been solved utilizing a genetic algorithm combined with second-order cone programming.Rationality and effectiveness of the model have been verified by setting different scenarios through case studies.Simulation results have demonstrated the coordinated operation of BESS and AC/DC hybrid systems can effectively suppress voltage fluctuations and improve the cost-benefit of BESSs from a life cycle angle.展开更多
Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery ener...Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery energy storage system(BESS)has a promising future in applying regulation and load management in the power grid.For regulation services,normally,the regulation power prediction is estimated based on the required maximum regulation capacity;the power needed for the specific regulation service is unknown to the BESS owner.However,this information is needed in the regulation model when formulating the linearised BESS model with a constraint on the state of charge(SoC).This compromises the accuracy of the model greatly when it is applied for regulation service.Moreover,different control strategies can be employed by BESS.However,the current depth of discharge(DoD)based models have difficulties in being used in a linearization problem.Due to the consideration of the control strategy,the model becomes highly nonlinear and cannot be solved.In this paper,a charging rate(C-rate)based model is introduced,which can consider different control strategies of a BESS for cooperation with wind farms to participate in wind farm estimation error compensation,load management,energy bid,and regulation bid.First,the limitation of conventional BESS models are listed,and a new C-rate-based model is introduced.Then the C-rate-based BESS model is adopted in a wind farm and BESS cooperation scheme.Finally,experimental studies are carried out,and the DoD model and C-rate model optimization results are compared to prove the rationality of the C-rate model.展开更多
Battery energy storage stations(BESSs)pose sever-al challenges for both phasor-based differential protection and the newly-proposed time-domain differential protection.These challenges include low sensitivity and even...Battery energy storage stations(BESSs)pose sever-al challenges for both phasor-based differential protection and the newly-proposed time-domain differential protection.These challenges include low sensitivity and even rejection.Besides,the negative impact of various nonideal conditions,including current transformer(CT)saturation,errors,and outliers,on the security of differential protection remains an important problem.Motivated by the aforementioned issues,this study accounts for the trajectory distribution discrepancy on Cartesian plane under various conditions and proposes a time-domain differential protection method.In this paper,the trajectory formed by operating and restraining current samples is devel-oped.Subsequently,after considering different operating states,the fault severity levels,and nonideal conditions,the variances in trajectory distribution between internal and external faults are extensively analyzed.On this basis,the Cartesian plane is divided into operating,uncertainty,and restraining zones.Further,the operating and restraining trajectory indices are meticu-lously designed and a protection criterion based on these indices is formed to accurately separate internal faults from other events,unaffected by CT saturation,errors,and outliers.The exceptional performance of the proposed protection method is extensively validated through PSCAD simulations and a hard-ware-in-the-loop testing platform.Regarding the dependability,sensitivity,and security,the proposed protection method outper-forms three state-of-the-art differential protection methods.展开更多
Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy s...Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system(BESS).However,the current modeling of grid-connected BESS is overly simplistic,typically only considering state of charge(SOC)and power constraints.Detailed lithium(Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions.Additionally,there is a lack of real-time batteries risk assessment frameworks.To address these issues,in this study,we establish a thermal-electric-performance(TEP)coupling model based on a multitime scale BESS model,incorporating the electrical and thermal characteristics of Li-ion batteries along with their performance degradation to achieve detailed simulation of grid-connected BESS.Additionally,considering the operating characteristics of energy storage batteries and electrical and thermal abuse factors,we developed a battery pack operational riskmodel,which takes into account SOCand charge-discharge rate(Cr),using amodified failure rate to represent the BESS risk.By integrating detailed simulation of energy storage with predictive failure risk analysis,we obtained a detailed model for BESS risk analysis.This model offers a multi-time scale integrated simulation that spans month-level energy storage simulation times,day-level performance degradation,minutescale failure rate,and second-level BESS characteristics.It offers a critical tool for the study of BESS.Finally,the performance and risk of energy storage batteries under three scenarios—microgrid energy storage,wind power smoothing,and power grid failure response—are simulated,achieving a real-time state-dependent operational risk analysis of the BESS.展开更多
This paper studies the feasibility of a supply-side wind-coal integrated energy system.Based on grid-side data,the load regulation model of coal-fired power and the wind-coal integrated energy system model are establi...This paper studies the feasibility of a supply-side wind-coal integrated energy system.Based on grid-side data,the load regulation model of coal-fired power and the wind-coal integrated energy system model are established.According to the simulation results,the reasons why the wind-coal combined power supply is difficult to meet the grid-side demand are revealedthrough scenario analysis.Basedon thewind-coal combinedoperation,a wind-coalstorage integrated energy system was proposed by adding lithium-iron phosphate battery energy storage system(LIPBESS)to adjust the load of the system.According to the four load adjustment scenarios of grid-side instructions of the wind-coal system,the difficulty of load adjustment in each scenario is analyzed.Based on the priority degree of LIPBESS charge/discharge in four scenarios at different time periods,the operation mode of two charges and two discharges per day was developed.Based on the independent operation level of coal-fired power,after the addition of LIPBESS(5.5 MWh),the average qualified rate of multi-power operation in March and June reached the level of independent operation of coal-fired power,while the average qualified rate of the remaining months was only 5.4%different from that of independent operation of coal-fired power.Compared with the wind storage mode,the energy storage capacity and investment cost of wind-coal-storage integrated energy system are reduced by 54.2%and 53.7%,respectively.展开更多
The wind energy generation,utilization and its grid penetration in electrical grid are increasing world-wide.The wind generated power is always fluctuating due to its time varying nature and causing stability problem....The wind energy generation,utilization and its grid penetration in electrical grid are increasing world-wide.The wind generated power is always fluctuating due to its time varying nature and causing stability problem.This weak interconnection of wind generating source in the electrical network affects the power quality and reliability.The localized energy storages shall compensate the fluctuating power and support to strengthen the wind generator in the power system.In this paper,it is proposed to control the voltage source inverter （VSI） in current control mode with energy storage,that is,batteries across the dc bus.The generated wind power can be extracted under varying wind speed and stored in the batteries.This energy storage maintains the stiff voltage across the dc bus of the voltage source inverter.The proposed scheme enhances the stability and reliability of the power system and maintains unity power factor.It can also be operated in stand-alone mode in the power system.The power exchange across the wind generation and the load under dynamic situation is feasible while maintaining the power quality norms at the common point of coupling.It strengthens the weak grid in the power system.This control strategy is evaluated on the test system under dynamic condition by using simulation.The results are verified by comparing the performance of controllers.展开更多
For the impact of intermittent resources＇ high penetration on the economic dispatch of islanded microgrid, a new economic dispatch method is presented to minimize the overall generating cost for islanded microgrid, c...For the impact of intermittent resources＇ high penetration on the economic dispatch of islanded microgrid, a new economic dispatch method is presented to minimize the overall generating cost for islanded microgrid, considering a cooperative strategy between diesel generator （hereinafter referred to as DE） and battery energy storage system （BESS）. The optimum economic operation range of DE and the optimal set-point between DE and BESS are presented in the cooperative dispatch strategy, in which BESS is used fully to enable DE in a lower cost and higher efficient way. The results are analyzed under various operation conditions and also prove the validity of the DrODosed method.展开更多
Battery energy storage system(BESS)has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies.However,the BESS have not been properly studied under unbala...Battery energy storage system(BESS)has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies.However,the BESS have not been properly studied under unbalanced operation of power grids.This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids.The proposed model manages the BESS to optimize energy cost,deal with load uncertainties,and settle the unbalanced loading at the same time.The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition.The IEEE 69-bus grid is considered as case study.The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties.The model is formulated as mixed-integer linear programming and solved by GAMS/CPLEX.The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time.The model also minimizes the operation cost and satisfies all security constraints of power grid.展开更多
基金The Deanship of Scientific Research at Najran University has supported this work,under the General Research Funding program grant code(NU/-/SERC/10/650).
文摘This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking(MPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comparative study in terms of the dynamic response,battery state of charge(SOC),and oscillations around the Maximum Power Point(MPP)of the PV-BSS to variations in climate conditions,these techniques are simulated in Matlab/Simulink.The introduced methodologies are classified into two types;the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb&Observe and Incremental Conductance techniques.The second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre-build Adaptive Neuro-Fuzzy Inference System(ANFIS)model to predict DC–DC converter optimum duty cycle to track MPP.Then evaluation study is introduced for conventional and proposed On-Line MPPT techniques.This comparative study can be useful in specifying the appropriateness of the MPPT techniques for PV-BSS.Also the introduced model can be used as a valued reference model for future research related to Soft Computing(SC)MPPT techniques.A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.
基金supported by the Natural Science Foundation of China No.62303126the project Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.
文摘This study introduces a novel deep reinforcement learning(DRL)framework for the joint dispatch of Gas Turbines(GTs)and Battery Energy Storage Systems(BESs)in microgrids that face the variability of renewable energy sources and demands.BESs can store surplus renewable energy for nearly instantaneous use,while GTs offer sustained energy output over longer periods,offering complementary benefits.Previous studies often oversimplified GT operations,neglecting critical factors such as ramp-up times and increased degradation from frequent starts.This research addresses these gaps by proposing an advanced modeling framework that accurately captures the dynamic interaction between GTs and BESs,including GT ramp-up times and maintenance costs associated with operational cycles.Through extensive case studies involving diverse microgrid configurations,we demonstrate that DRL effectively learns dispatch policies directly from historical data,outperforming traditional optimization techniques.Deploying DRL to our framework yields more realistic dispatch policies,reducing GT maintenance costs by avoiding frequent starts.The proposed framework has significant potential to improve energy management strategies and to streamline the planning of hybrid energy systems.To encourage further research,we have released our codebase to the public,enabling the scientific community to build upon our findings.
基金sponsored by the National Key Research and Development Program of China(2022YFA1503501)the National Natural Science Foundation of China(22278127,22378112)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)21C Innovation Laboratory,Contemporary Amperex Technology Ltd by project No.21C-368 OP-202312,Shanghai Pilot Proaram for Basic Research(22T01400100-18)。
文摘Lithium-ion batteries(LIBs)are widely used in electrochemical battery energy storage systems(BESS)because of their high energy density,lack of memory effects,low self-discharge rate,and long cycle life.However,inadequate heat dissipation during their discharge process can significantly degrade battery performance.The improvement of BESS efficiency depends on the optimization of thermal management structures.In this work,we integrate the pseudo-two-dimensional(P2D)electrochemical model with a three-dimensional thermal model to analyze the heat generation and transfer processes within the BESS.The simulation results are closely aligned with the experimental results in terms of voltage and temperature rise curves.Under air cooling conditions of 293.15 K and 3 m·s^(-1),the BESS has a maximum temperature of 308.60 K and a temperature difference of 9.22 K,ensuring safe operation.At 1 C,we suggest that enlarging the inlet and outlet areas improves the air-cooling efficiency,and transitioning environmental air-cooling temperatures after 2400 s of discharge effectively reduces the temperature difference and the energy consumption of the cooling equipment.This work provides valuable theoretical insights for optimizing the thermal design of BESS.
文摘The development of microgrid systems forces to integration of various distributed generators(DG)and battery energy storage(BES)systems.The integration of a BES system in MG provides several benefits such as fast response,short-term power supply,improved power quality,ancillary service,and arbitrage.The system constraints as power balance and the assets constraints as power limit of different DGs,energy,and charge/discharge power limit of BES increase the complexity of the original problem.Therefore,to tackle such a problem an efficient,robust,and strong optimization algorithm is required.In this paper,a recently developed optimization method known as the wild geese algorithm(WGA)has been applied to solve the problem.The WGA is a population-based metaheuristic approach inspired by the different aspects of the living behavior of wild geese.This algorithm has developed with the inspiration of different phases of wild geese's lives,such as their evolution,well-organized and coordinated long-distance group migration,and fatality.The WGA has tested on the MG problem and the obtained simulation results are validated by comparison of results obtained from the other methods.The result shows the WGA is efficiently able to handle the MG operational problem with numerous constraints and shows the potential to produce a high-quality solution in terms of cost reduction.The incorporation of BES reduces operating costs for MG's off-grid and on-grid operational modes by 5.91%and 8.62%,respectively.Further,the analysis for off-grid mode under different seasonality,reduction in the operational cost by 4.47%,9.28%,6.37%,and 7.22%was measured in the summer,autumn,winter,and spring seasons,respectively,with the integration of BES.Additionally,the integration of BES in on-grid mode results in a decrease in operating costs by 7.15%,12.54%,7.56%,and 11.07%in the summer,autumn,winter,and spring,respectively.
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
基金This research was supported by the Science Foundation of Yantai Vocational College(No.2023XBYB008).
文摘With the continuous emergence of new energy storage technology innovation in the field of electrochemical energy storage in China,different megawatt-grade lithium-ion battery energy storage projects have been implemented,promoting the high-quality development of the energy storage industry.In the context of vigorously promoting the energy consumption revolution and enhancing the green transformation and development momentum,strengthening the safety construction of lithium-ion battery energy storage is of great importance to realize the transformation of energy structure and improve the utilization efficiency of renewable energy.However,in recent years,frequent safety accidents of lithium-ion battery energy storage power stations,such as fires,have aroused the public’s high attention to the construction of lithium-ion battery energy storage power stations,affecting the large-scale development of energy storage power stations.Based on this,this paper analyzes the safety risks of lithium-ion battery energy storage power stations and focuses on how to improve their safety performance.
基金supported by the research grant(20AUDP-B099686-06)from architecture&urban development research program funded by ministry of land,infrastructure and transport of Korean government.
文摘At present,the power system is more inclined towards disturbances,such as voltage variations and unbalanced load conditions,due to the grid's complexity and load growth.These challenges emphasize the integration of the compensating devices,such as battery storage(BS)and D-STATCOMs.In this regard,this current paper exhibits a novel energy management system(EMS)of a combined BS and D-STATCOM to compensate the power system during disturbances.The EMS is based on a fractional order sliding mode control(FOSMC)to drive the voltage source converters(VSCs)such that the active power is independently absorbed/injected by the BS,whereas the reactive power is independently absorbed/injected by the D-STATCOM depending upon the disturbance situation.FOSMC is a robust non-linear controller in which the Riemann-Liouville(RL)function is employed to design the sliding surface and the exponential reaching law is used to minimize the chattering phenomenon.The stability of the FOSMC in the proposed EMS is proved using the Lyapunov candidate function.In order to validate the performance of the proposed EMS,a model of a 400 V,180 kVA radial distributor along with a BS and D-STATCOM is simulated in MATLAB/Simulink environment in two test cases.The results prove that the proposed EMS with FOMSC effectively compensates the power system under voltage variations and unbalanced load conditions with rapid tracking,fast convergence and upright damping.Furthermore,the results have been compared with the classical proportional integral(PI)control and fixed frequency SMC(FFSMC),and they demonstrate the superiority of the proposed EMS with FOSMC in power system applications.
文摘Distributed generation(DG)are critical components for active distribution system(ADS).However,this may be a serious impact on power system due to their volatility.To this problem,interactive load and battery storage may be a best solution.This paper firstly investigates operation characteristics of interactive load and battery storage,including operation flexibility,inter-temporal operation relations and active-reactive power relations.Then,a multi-period coordinated activereactive scheduling model considering interactive load and battery storage is proposed in order to minimize overall operation costs over a specific duration of time.The model takes into accounts operation characteristics of interactive load and battery storage and focuses on coordination between DGs and them.Finally,validity and effectiveness of the proposed model are demonstrated based on case study of a medium-voltage 135-bus distribution system.
基金This work was supported by Australian Research Council(ARC)Discovery Project(No.160102571).
文摘To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertainty of daily cycling load prompts the need to design a new cost function which is able to quantify the associated uncertainty.By modelling a probabilistic dependence among flow,load,and electricity tariffs,the expected cost function is obtained and used in the constrained optimization.The proposed control strategy explicitly incorporates the cycling nature of customer load.Furthermore,for daily cycling load,a fixed-end time and a fixed-end output problem are addressed.It is demonstrated that the proposed control strategy is a convex optimization problem.While stochastic and robust model predictive controllers evaluate the cost concerning model constraints and parameter variations.Also,the expected cost across the flow variations is considered.The density function of load probability improves load prediction over a progressive prediction horizon,and a nonlinear battery model is utilized.
文摘This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.
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.
基金supported in part by the National Natural Science Foundation of China(No.51777134)in part by a joint project of NSFC of China and EPSRC of UK(No.52061635103 and EP/T021969/1).
文摘The upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged stable and efficient operation of the power system.Battery energy storage systems(BESSs)have been identified as critical to mitigate random fluctuations,unnecessary green energy curtailment and load shedding with rapid response and flexible connection.On the other hand,an AC/DC hybrid distribution system can offer merged benefits in both AC and DC subsystems without additional losses during AC/DC power conversion.Therefore,configuring BESSs on an AC/DC distribution system is wellpositioned to meet challenges brought by carbon reductions in an efficient way.A bi-level optimization model of BESS capacity allocation for AC/DC hybrid distribution systems,considering the flexibility of voltage source converters(VSCs)and power conversion systems(PCSs),has been established in this paper to address the techno-economic issues that hindered wide implementation.The large-scale nonlinear programming problem has been solved utilizing a genetic algorithm combined with second-order cone programming.Rationality and effectiveness of the model have been verified by setting different scenarios through case studies.Simulation results have demonstrated the coordinated operation of BESS and AC/DC hybrid systems can effectively suppress voltage fluctuations and improve the cost-benefit of BESSs from a life cycle angle.
文摘Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery energy storage system(BESS)has a promising future in applying regulation and load management in the power grid.For regulation services,normally,the regulation power prediction is estimated based on the required maximum regulation capacity;the power needed for the specific regulation service is unknown to the BESS owner.However,this information is needed in the regulation model when formulating the linearised BESS model with a constraint on the state of charge(SoC).This compromises the accuracy of the model greatly when it is applied for regulation service.Moreover,different control strategies can be employed by BESS.However,the current depth of discharge(DoD)based models have difficulties in being used in a linearization problem.Due to the consideration of the control strategy,the model becomes highly nonlinear and cannot be solved.In this paper,a charging rate(C-rate)based model is introduced,which can consider different control strategies of a BESS for cooperation with wind farms to participate in wind farm estimation error compensation,load management,energy bid,and regulation bid.First,the limitation of conventional BESS models are listed,and a new C-rate-based model is introduced.Then the C-rate-based BESS model is adopted in a wind farm and BESS cooperation scheme.Finally,experimental studies are carried out,and the DoD model and C-rate model optimization results are compared to prove the rationality of the C-rate model.
基金supported in part by the National Natural Science Foundation of China (No.52277132)in part by the Fundamental Research Funds for the Central Universities (No.2024JCCXJD01)
文摘Battery energy storage stations(BESSs)pose sever-al challenges for both phasor-based differential protection and the newly-proposed time-domain differential protection.These challenges include low sensitivity and even rejection.Besides,the negative impact of various nonideal conditions,including current transformer(CT)saturation,errors,and outliers,on the security of differential protection remains an important problem.Motivated by the aforementioned issues,this study accounts for the trajectory distribution discrepancy on Cartesian plane under various conditions and proposes a time-domain differential protection method.In this paper,the trajectory formed by operating and restraining current samples is devel-oped.Subsequently,after considering different operating states,the fault severity levels,and nonideal conditions,the variances in trajectory distribution between internal and external faults are extensively analyzed.On this basis,the Cartesian plane is divided into operating,uncertainty,and restraining zones.Further,the operating and restraining trajectory indices are meticu-lously designed and a protection criterion based on these indices is formed to accurately separate internal faults from other events,unaffected by CT saturation,errors,and outliers.The exceptional performance of the proposed protection method is extensively validated through PSCAD simulations and a hard-ware-in-the-loop testing platform.Regarding the dependability,sensitivity,and security,the proposed protection method outper-forms three state-of-the-art differential protection methods.
基金Supported by Open Fund of National Key Laboratory of Power Grid Safety(No.XTB51202301386).
文摘Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system(BESS).However,the current modeling of grid-connected BESS is overly simplistic,typically only considering state of charge(SOC)and power constraints.Detailed lithium(Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions.Additionally,there is a lack of real-time batteries risk assessment frameworks.To address these issues,in this study,we establish a thermal-electric-performance(TEP)coupling model based on a multitime scale BESS model,incorporating the electrical and thermal characteristics of Li-ion batteries along with their performance degradation to achieve detailed simulation of grid-connected BESS.Additionally,considering the operating characteristics of energy storage batteries and electrical and thermal abuse factors,we developed a battery pack operational riskmodel,which takes into account SOCand charge-discharge rate(Cr),using amodified failure rate to represent the BESS risk.By integrating detailed simulation of energy storage with predictive failure risk analysis,we obtained a detailed model for BESS risk analysis.This model offers a multi-time scale integrated simulation that spans month-level energy storage simulation times,day-level performance degradation,minutescale failure rate,and second-level BESS characteristics.It offers a critical tool for the study of BESS.Finally,the performance and risk of energy storage batteries under three scenarios—microgrid energy storage,wind power smoothing,and power grid failure response—are simulated,achieving a real-time state-dependent operational risk analysis of the BESS.
基金supported by the Natural Science Foundation of China(Grant No.52076079)Natural Science Foundation of Hebei Province,China(Grant No.E2020502013)the Fundamental Research Funds for the Central Universities(2021MS076,2021MS079).
文摘This paper studies the feasibility of a supply-side wind-coal integrated energy system.Based on grid-side data,the load regulation model of coal-fired power and the wind-coal integrated energy system model are established.According to the simulation results,the reasons why the wind-coal combined power supply is difficult to meet the grid-side demand are revealedthrough scenario analysis.Basedon thewind-coal combinedoperation,a wind-coalstorage integrated energy system was proposed by adding lithium-iron phosphate battery energy storage system(LIPBESS)to adjust the load of the system.According to the four load adjustment scenarios of grid-side instructions of the wind-coal system,the difficulty of load adjustment in each scenario is analyzed.Based on the priority degree of LIPBESS charge/discharge in four scenarios at different time periods,the operation mode of two charges and two discharges per day was developed.Based on the independent operation level of coal-fired power,after the addition of LIPBESS(5.5 MWh),the average qualified rate of multi-power operation in March and June reached the level of independent operation of coal-fired power,while the average qualified rate of the remaining months was only 5.4%different from that of independent operation of coal-fired power.Compared with the wind storage mode,the energy storage capacity and investment cost of wind-coal-storage integrated energy system are reduced by 54.2%and 53.7%,respectively.
文摘The wind energy generation,utilization and its grid penetration in electrical grid are increasing world-wide.The wind generated power is always fluctuating due to its time varying nature and causing stability problem.This weak interconnection of wind generating source in the electrical network affects the power quality and reliability.The localized energy storages shall compensate the fluctuating power and support to strengthen the wind generator in the power system.In this paper,it is proposed to control the voltage source inverter （VSI） in current control mode with energy storage,that is,batteries across the dc bus.The generated wind power can be extracted under varying wind speed and stored in the batteries.This energy storage maintains the stiff voltage across the dc bus of the voltage source inverter.The proposed scheme enhances the stability and reliability of the power system and maintains unity power factor.It can also be operated in stand-alone mode in the power system.The power exchange across the wind generation and the load under dynamic situation is feasible while maintaining the power quality norms at the common point of coupling.It strengthens the weak grid in the power system.This control strategy is evaluated on the test system under dynamic condition by using simulation.The results are verified by comparing the performance of controllers.
基金the National Natural Science Foundation of China(No.61703068)the Scientific and Technological Research Program of Chongqing Municipal Education Commission(No.KJ1704097)+1 种基金the Chongqing Basic Science and Advanced Technology Research Project(No.cstc2016jcyjA1919)the Doctor Start-up Funding of Chongqing University of Posts and Telecommunications(No.A2016-05)
文摘For the impact of intermittent resources＇ high penetration on the economic dispatch of islanded microgrid, a new economic dispatch method is presented to minimize the overall generating cost for islanded microgrid, considering a cooperative strategy between diesel generator （hereinafter referred to as DE） and battery energy storage system （BESS）. The optimum economic operation range of DE and the optimal set-point between DE and BESS are presented in the cooperative dispatch strategy, in which BESS is used fully to enable DE in a lower cost and higher efficient way. The results are analyzed under various operation conditions and also prove the validity of the DrODosed method.
文摘Battery energy storage system(BESS)has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies.However,the BESS have not been properly studied under unbalanced operation of power grids.This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids.The proposed model manages the BESS to optimize energy cost,deal with load uncertainties,and settle the unbalanced loading at the same time.The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition.The IEEE 69-bus grid is considered as case study.The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties.The model is formulated as mixed-integer linear programming and solved by GAMS/CPLEX.The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time.The model also minimizes the operation cost and satisfies all security constraints of power grid.
