A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about com...A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about commercializing HESS and improving it further.However,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS design.With that,this review aims to collect and analyse a wide range of HESS studies to summarise recent studies.Two different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via VOSViewer.The findings from the Web of Science platform were also examined for amore comprehensive understanding.Major findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this country.HESS has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of analysis.MATLAB is a common tool used for HESS design,modelling,and optimization as it can handle complex calculations.Artificial neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future work.From a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and development.From this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are needed.Overall,this review summarized various takeaways that future research works on HESS can use.展开更多
To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy...To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.展开更多
An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential...An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.展开更多
The development of sustainable electrode materials for energy storage systems has become very important and porous carbons derived from biomass have become an important candidate because of their tunable pore structur...The development of sustainable electrode materials for energy storage systems has become very important and porous carbons derived from biomass have become an important candidate because of their tunable pore structure,environmental friendliness,and cost-effectiveness.Recent advances in controlling the pore structure of these carbons and its relationship between to is energy storage performance are discussed,emphasizing the critical role of a balanced distribution of micropores,mesopores and macropores in determining electrochemical behavior.Particular attention is given to how the intrinsic components of biomass precursors(lignin,cellulose,and hemicellulose)influence pore formation during carbonization.Carbonization and activation strategies to precisely control the pore structure are introduced.Finally,key challenges in the industrial production of these carbons are outlined,and future research directions are proposed.These include the establishment of a database of biomass intrinsic structures and machine learning-assisted pore structure engineering,aimed at providing guidance for the design of high-performance carbon materials for next-generation energy storage devices.展开更多
Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper...Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon.First,existing methods employed in urban rail transit are comprehensively reviewed.Then,a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced.This integration effectively utilizes and manages diverse renewable energy sources and the available space resources.The viability is demonstrated through a case study by combining Nanjing metro.Finally,suggestions for research in pivotal areas are summarized.展开更多
Using electric motors instead of diesel engines as the driving system for mining excavators can reduce the energy consumption and operating costs.However,pure electric-driven mining excavators are prone to unexpected ...Using electric motors instead of diesel engines as the driving system for mining excavators can reduce the energy consumption and operating costs.However,pure electric-driven mining excavators are prone to unexpected power outages in mines because of drastic changes in load power,leading to significant fluctuations in the power demand of the grid,which in turn affects production.To solve the above problem,a pure electric-driven mining hydraulic excavator based on electric-motor-driven swing platform and hydraulic pumps was used as the research object.Moreover,supercapacitors and DC/DC converter,as the energy storage system(ESS)adjust the output power of the grid and recover the braking kinetic energy of the swing platform.Subsequently,a novel integrated energy management strategy for a DC bus voltage predictive controller based on the power feedforward of fuzzy rules is proposed to run mining excavators efficiently and reliably.Specifically,the working modes of the ESS are determined by the DC bus voltage and state of charge(SOC)of the supercapacitor.Next,the output power of the supercapacitor and the DC bus voltage were controlled by adjusting the charging and discharging currents of the DC/DC converter using a predictive controller and fuzzy rules.In addition,a digital prototype of the excavator was verified using an original machine test.The performance of the different strategies and driven systems were analyzed using digital prototypes.The results showed that,compared with traditional excavators with diesel engines,the operational cost of the developed excavators was reduced by 54.02%.Compared to pure electric-driven excavators without an ESS,the peak power of the grid for the developed excavators was reduced by 10%.This study designed an integrated energy management strategy for a pure electric mining excavator that can regulate the power output of the grid and maintain the stability of the bus voltage and SOC of the ESS.展开更多
The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-...The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.展开更多
To enhance energy interaction among low-voltage stations(LVSs)and reduce the line loss of the distribution network,a novel operation mode of the micro-pumped storage system(mPSS)has been proposed based on the common r...To enhance energy interaction among low-voltage stations(LVSs)and reduce the line loss of the distribution network,a novel operation mode of the micro-pumped storage system(mPSS)has been proposed based on the common reservoir.First,some operation modes of mPSS are analyzed,which include the separated reservoir mode(SRM)and common reservoir mode(CRM).Then,based on the SRM,and CRM,an energy mutual assistance control model between LVSs has been built to optimize energy loss.Finally,in the simulation,compared to the model without pumped storage in the LVS,the SRMand CLRMcan decrease the total energy loss by 294.377 and 432.578 kWh,respectively.The configuration of mPSS can improve the utilization rate of the new energy source generation system,and relieve the pressure of transformer capacity in the LVS.Compared with the SRM,the proposed CRM has reduced the total energy loss by 138.201 kWh,increased the new energy consumption by 161.642 kWh,and decreased the line loss by 7.271 kWh.With the efficiency of the mPSS improving,the total energy loss reduction of CRM will be 3.5 times that of SRM.Further,the CRMcan significantly reduce the reservoir capacity construction of mPSS and ismore suitable for scenarios where the capacity configuration of mPSS is limited.展开更多
To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved...To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.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
Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways Hi...In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.展开更多
The bicarbonate-formate(HCO_(3)−–HCO_(2)−)interconversion provides a promising cycle for a conveniently accessible hydrogen storage system via reversible dehydrogenation and hydrogenation processes.Existing catalytic...The bicarbonate-formate(HCO_(3)−–HCO_(2)−)interconversion provides a promising cycle for a conveniently accessible hydrogen storage system via reversible dehydrogenation and hydrogenation processes.Existing catalytic systems often use organic solvents,tedious optimization as well as manipulation of pH values,solvent,pressure and various additives.Herein,we present an operational,robust,safe and cost-effective catalytic system for hydrogen storage and liberation.We have established a unique catalytic system with two different solid organometallic assemblies(NHC-Ru and NHC-Ir)that facilitate the reversible transformation between sodium formate and bicarbonate in aqueous solutions collaboratively and efficiently.Notably,the NHC-Ru catalyst is privileged for the hydrogenation of sodium bicarbonate,whereas the NHC-Ir component enables the dehydrogenation of sodium formate,all in a single reaction vessel.What sets this system apart is its simplicity.The H_(2)discharging and recharging is simply regulated by heating the mixture with or without H_(2).Remarkably,this process requires no extra additives or supplementary treatments.Moreover,the reversible hydrogen storage system is durable and can be reused for over 30 cycles without a discernible decline in activity and selectivity.The strategic paradigm in this study shows significant practical potential in hydrogen fuel cell applications.展开更多
The ability to control the electrode interfaces in an electrochemical energy storage system is essential for achieving the desired electrochemical performance.However,achieving this ability requires an in-depth unders...The ability to control the electrode interfaces in an electrochemical energy storage system is essential for achieving the desired electrochemical performance.However,achieving this ability requires an in-depth understanding of the detailed interfacial nanostructures of the electrode under electrochemical operating conditions.In-situ transmission electron microscopy(TEM)is one of the most powerful techniques for revealing electrochemical energy storage mechanisms with high spatiotemporal resolution and high sensitivity in complex electrochemical environments.These attributes play a unique role in understanding how ion transport inside electrode nanomaterials and across interfaces under the dynamic conditions within working batteries.This review aims to gain an in-depth insight into the latest developments of in-situ TEM imaging techniques for probing the interfacial nanostructures of electrochemical energy storage systems,including atomic-scale structural imaging,strain field imaging,electron holography,and integrated differential phase contrast imaging.Significant examples will be described to highlight the fundamental understanding of atomic-scale and nanoscale mechanisms from employing state-of-the-art imaging techniques to visualize structural evolution,ionic valence state changes,and strain mapping,ion transport dynamics.The review concludes by providing a perspective discussion of future directions of the development and application of in-situ TEM techniques in the field of electrochemical energy storage systems.展开更多
The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.Wh...The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.展开更多
High-temperature phase change materials(PCMs)have attracted significant attention in the field of thermal energy storage due to their ability to store and release large amounts of heat within a small temperature fluct...High-temperature phase change materials(PCMs)have attracted significant attention in the field of thermal energy storage due to their ability to store and release large amounts of heat within a small temperature fluctuation range.However,their practical application is limited due to problems such as leakage,corrosion,and volume changes at high temperatures.Recent research has shown that macroencapsulation technology holds promise in addressing these issues.This paper focuses on the macroencapsulation technology of high-temperature PCMs,starting with a review of the classification and development history of high-temperature macroencapsulatd PCMs.Four major encapsulation strategies,including electroplating method,solid/liquid filling method,sacrificial material method,and powder compaction into sphere method,are then summarized.The methods for effectively addressing issues such as corrosion,leakage,supercooling,and phase separation in PCMs are analyzed,along with approaches for improving the heat transfer performance,mechanical strength,and thermal cycling stability of macrocapsules.Subsequently,the structure and packing arrangement optimization of macrocapsules in thermal storage systems is discussed in detail.Finally,after comparing the performance of various encapsulation strategies and summarizing existing issues,the current technical challenges,improvement methods,and future development directions are proposed.More attention should be given to utilizing AI technology and reinforcement learning to reveal the multiphysics-coupled heat and mass transfer mechanisms in macrocapsule applications,as well as to optimize material selection and encapsulation parameters,thereby enhancing the overall efficiency of thermal storage systems.展开更多
Based on the distribution of cooling load at a subway station and the peak-valley electricity price in Guangzhou,a chilled water storage system is reserved in the ample space above the station's distribution area....Based on the distribution of cooling load at a subway station and the peak-valley electricity price in Guangzhou,a chilled water storage system is reserved in the ample space above the station's distribution area.This study proposes a design scheme and operational strategy for a chilled water storage system suitable for subway engineering,based on calculating the cooling load and designing a chilled water storage system in a subway station.Additionally,it proposes calculation coefficients of hourly cooling load suitable for subway engineering and convenient for estimation of hourly cooling load.Furthermore,an economic analysis is conducted by combining hourly cooling load with time-of-use electricity prices.This study provides a reference for the design and application of chilled water storage systems in subsequent subway projects.展开更多
With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as...With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.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
文摘A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various purposes.With that,there have been many discussions about commercializing HESS and improving it further.However,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS design.With that,this review aims to collect and analyse a wide range of HESS studies to summarise recent studies.Two different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via VOSViewer.The findings from the Web of Science platform were also examined for amore comprehensive understanding.Major findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this country.HESS has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of analysis.MATLAB is a common tool used for HESS design,modelling,and optimization as it can handle complex calculations.Artificial neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future work.From a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and development.From this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are needed.Overall,this review summarized various takeaways that future research works on HESS can use.
基金Supported by State Grid Zhejiang Electric Power Co.,Ltd.Science and Technology Project Funding(No.B311DS230005).
文摘To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.
基金supported by the Fundamental Research Funds for the Central Universities(WK2150110022)Anhui Provincial Natural Science Foundation(2208085QF189)National Natural Science Foundation of China(62202440).
文摘An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.
文摘The development of sustainable electrode materials for energy storage systems has become very important and porous carbons derived from biomass have become an important candidate because of their tunable pore structure,environmental friendliness,and cost-effectiveness.Recent advances in controlling the pore structure of these carbons and its relationship between to is energy storage performance are discussed,emphasizing the critical role of a balanced distribution of micropores,mesopores and macropores in determining electrochemical behavior.Particular attention is given to how the intrinsic components of biomass precursors(lignin,cellulose,and hemicellulose)influence pore formation during carbonization.Carbonization and activation strategies to precisely control the pore structure are introduced.Finally,key challenges in the industrial production of these carbons are outlined,and future research directions are proposed.These include the establishment of a database of biomass intrinsic structures and machine learning-assisted pore structure engineering,aimed at providing guidance for the design of high-performance carbon materials for next-generation energy storage devices.
基金supported by the National Natural Science Foundation of China(Grant numbers 52177112 and 52278419)the Chinese Academy of Engineering(Grant number 2022--XY-75).
文摘Within the transition process of urban rail transit systems,the challenges of high energy consumption,increasing carbon emissions,limited economic viability,and intricate risks emerge as significant hurdles.This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon.First,existing methods employed in urban rail transit are comprehensively reviewed.Then,a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced.This integration effectively utilizes and manages diverse renewable energy sources and the available space resources.The viability is demonstrated through a case study by combining Nanjing metro.Finally,suggestions for research in pivotal areas are summarized.
基金Supported by National Natural Science Foundation of ChinaShanxi Coalbased Low-Carbon Joint Fund(Grant No.U1910211)。
文摘Using electric motors instead of diesel engines as the driving system for mining excavators can reduce the energy consumption and operating costs.However,pure electric-driven mining excavators are prone to unexpected power outages in mines because of drastic changes in load power,leading to significant fluctuations in the power demand of the grid,which in turn affects production.To solve the above problem,a pure electric-driven mining hydraulic excavator based on electric-motor-driven swing platform and hydraulic pumps was used as the research object.Moreover,supercapacitors and DC/DC converter,as the energy storage system(ESS)adjust the output power of the grid and recover the braking kinetic energy of the swing platform.Subsequently,a novel integrated energy management strategy for a DC bus voltage predictive controller based on the power feedforward of fuzzy rules is proposed to run mining excavators efficiently and reliably.Specifically,the working modes of the ESS are determined by the DC bus voltage and state of charge(SOC)of the supercapacitor.Next,the output power of the supercapacitor and the DC bus voltage were controlled by adjusting the charging and discharging currents of the DC/DC converter using a predictive controller and fuzzy rules.In addition,a digital prototype of the excavator was verified using an original machine test.The performance of the different strategies and driven systems were analyzed using digital prototypes.The results showed that,compared with traditional excavators with diesel engines,the operational cost of the developed excavators was reduced by 54.02%.Compared to pure electric-driven excavators without an ESS,the peak power of the grid for the developed excavators was reduced by 10%.This study designed an integrated energy management strategy for a pure electric mining excavator that can regulate the power output of the grid and maintain the stability of the bus voltage and SOC of the ESS.
文摘The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.
基金sponsored by the State Grid Corporation of China Technology Project(Research on Key Technologies and Equipment Development of Micro Pumped Storage for Distributed New Energy Consumption in Distribution Networks,5400-202324196A-1-1-ZN).
文摘To enhance energy interaction among low-voltage stations(LVSs)and reduce the line loss of the distribution network,a novel operation mode of the micro-pumped storage system(mPSS)has been proposed based on the common reservoir.First,some operation modes of mPSS are analyzed,which include the separated reservoir mode(SRM)and common reservoir mode(CRM).Then,based on the SRM,and CRM,an energy mutual assistance control model between LVSs has been built to optimize energy loss.Finally,in the simulation,compared to the model without pumped storage in the LVS,the SRMand CLRMcan decrease the total energy loss by 294.377 and 432.578 kWh,respectively.The configuration of mPSS can improve the utilization rate of the new energy source generation system,and relieve the pressure of transformer capacity in the LVS.Compared with the SRM,the proposed CRM has reduced the total energy loss by 138.201 kWh,increased the new energy consumption by 161.642 kWh,and decreased the line loss by 7.271 kWh.With the efficiency of the mPSS improving,the total energy loss reduction of CRM will be 3.5 times that of SRM.Further,the CRMcan significantly reduce the reservoir capacity construction of mPSS and ismore suitable for scenarios where the capacity configuration of mPSS is limited.
基金by National Natural Science Foundation of China(62373142,62033014)Natural Science Foundation of Hunan Province(2025JJ70017,2022JJ50074).
文摘To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains.
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supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.
基金Financial support from the National Natural Science Foundation of China(No.22271060)。
文摘The bicarbonate-formate(HCO_(3)−–HCO_(2)−)interconversion provides a promising cycle for a conveniently accessible hydrogen storage system via reversible dehydrogenation and hydrogenation processes.Existing catalytic systems often use organic solvents,tedious optimization as well as manipulation of pH values,solvent,pressure and various additives.Herein,we present an operational,robust,safe and cost-effective catalytic system for hydrogen storage and liberation.We have established a unique catalytic system with two different solid organometallic assemblies(NHC-Ru and NHC-Ir)that facilitate the reversible transformation between sodium formate and bicarbonate in aqueous solutions collaboratively and efficiently.Notably,the NHC-Ru catalyst is privileged for the hydrogenation of sodium bicarbonate,whereas the NHC-Ir component enables the dehydrogenation of sodium formate,all in a single reaction vessel.What sets this system apart is its simplicity.The H_(2)discharging and recharging is simply regulated by heating the mixture with or without H_(2).Remarkably,this process requires no extra additives or supplementary treatments.Moreover,the reversible hydrogen storage system is durable and can be reused for over 30 cycles without a discernible decline in activity and selectivity.The strategic paradigm in this study shows significant practical potential in hydrogen fuel cell applications.
基金supported by the National Key Research Program of China under Grant No.2024YFA1408000the National Natural Science Foundation of China(52231007,12327804,T2321003,22088101)+1 种基金in part by the National Key Research Program of China under Grant 2021YFA1200600the support from the U.S.National Science Foundation(CHE 2102482)。
文摘The ability to control the electrode interfaces in an electrochemical energy storage system is essential for achieving the desired electrochemical performance.However,achieving this ability requires an in-depth understanding of the detailed interfacial nanostructures of the electrode under electrochemical operating conditions.In-situ transmission electron microscopy(TEM)is one of the most powerful techniques for revealing electrochemical energy storage mechanisms with high spatiotemporal resolution and high sensitivity in complex electrochemical environments.These attributes play a unique role in understanding how ion transport inside electrode nanomaterials and across interfaces under the dynamic conditions within working batteries.This review aims to gain an in-depth insight into the latest developments of in-situ TEM imaging techniques for probing the interfacial nanostructures of electrochemical energy storage systems,including atomic-scale structural imaging,strain field imaging,electron holography,and integrated differential phase contrast imaging.Significant examples will be described to highlight the fundamental understanding of atomic-scale and nanoscale mechanisms from employing state-of-the-art imaging techniques to visualize structural evolution,ionic valence state changes,and strain mapping,ion transport dynamics.The review concludes by providing a perspective discussion of future directions of the development and application of in-situ TEM techniques in the field of electrochemical energy storage systems.
基金supported by National Natural Science Foundation of China(52407126).
文摘The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.
基金supported by the National Natural Science Foundation of China(Grant No.51976092)。
文摘High-temperature phase change materials(PCMs)have attracted significant attention in the field of thermal energy storage due to their ability to store and release large amounts of heat within a small temperature fluctuation range.However,their practical application is limited due to problems such as leakage,corrosion,and volume changes at high temperatures.Recent research has shown that macroencapsulation technology holds promise in addressing these issues.This paper focuses on the macroencapsulation technology of high-temperature PCMs,starting with a review of the classification and development history of high-temperature macroencapsulatd PCMs.Four major encapsulation strategies,including electroplating method,solid/liquid filling method,sacrificial material method,and powder compaction into sphere method,are then summarized.The methods for effectively addressing issues such as corrosion,leakage,supercooling,and phase separation in PCMs are analyzed,along with approaches for improving the heat transfer performance,mechanical strength,and thermal cycling stability of macrocapsules.Subsequently,the structure and packing arrangement optimization of macrocapsules in thermal storage systems is discussed in detail.Finally,after comparing the performance of various encapsulation strategies and summarizing existing issues,the current technical challenges,improvement methods,and future development directions are proposed.More attention should be given to utilizing AI technology and reinforcement learning to reveal the multiphysics-coupled heat and mass transfer mechanisms in macrocapsule applications,as well as to optimize material selection and encapsulation parameters,thereby enhancing the overall efficiency of thermal storage systems.
基金supported by the Science and Technology Development Project of China Railway Design Corporation(Project No.2024CJ0401).
文摘Based on the distribution of cooling load at a subway station and the peak-valley electricity price in Guangzhou,a chilled water storage system is reserved in the ample space above the station's distribution area.This study proposes a design scheme and operational strategy for a chilled water storage system suitable for subway engineering,based on calculating the cooling load and designing a chilled water storage system in a subway station.Additionally,it proposes calculation coefficients of hourly cooling load suitable for subway engineering and convenient for estimation of hourly cooling load.Furthermore,an economic analysis is conducted by combining hourly cooling load with time-of-use electricity prices.This study provides a reference for the design and application of chilled water storage systems in subsequent subway projects.
文摘With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.
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.
