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
Latent heat storage plays an important role in the utilization of solar energy.However,the low thermal conductivity of phase change materials(PCM)significantly reduces the heat transfer efficiency of latent heat stora...Latent heat storage plays an important role in the utilization of solar energy.However,the low thermal conductivity of phase change materials(PCM)significantly reduces the heat transfer efficiency of latent heat storage systems.To enhance its storage/release efficiency,optimizing the fin geometry is essential.This paper establishes a validated three-dimensional numerical model that considers PCM natural convection to study the effects of fin height and number on the heat transfer process.The fin volume of all models is kept constant,and the fin height is determined by the annular space.The impact of fin heights(0.3ΔR,0.5ΔR,0.7ΔR,0.9ΔR)and numbers(4,8,10,16)on heat transfer efficiency was investigated by analyzing the PCM temperature distribution on the shell section,the liquid fraction within the shell over time,and the average heat transfer rate and heat flux.The results show that increasing the fin height from 0.3ΔR to 0.9ΔR reduces the heat storage and release completion times by 61.16%and 45.43%,respectively.Similarly,increasing the number of fins from 4 to 16 reduces the heat storage and release completion times by 33.35%and 31.13%,respectively.The study concludes that increasing both the fin number and height dilutes the heat flux between the fin and PCM during both the heat storage and release processes,with the fin number having a more significant effect on reducing heat flux than fin height.Therefore,when the fin volume remains constant,increasing fin height is more conducive to improving the heat transfer performance of the PCM.These findings will provide a foundation for the application of finned tube energy storage systems in building energy conservation and other fields.展开更多
The energy transition increasingly requires holistic approaches that integrate electricity,heating and cooling,water management,industrial processes,transport,and environmental considerations within coherent system fr...The energy transition increasingly requires holistic approaches that integrate electricity,heating and cooling,water management,industrial processes,transport,and environmental considerations within coherent system frameworks.Such integration is essential for achieving deep decarbonisation while maintaining reliability,affordability,and resource efficiency across diverse regional and sectoral contexts.This Special Issue of Energy Engineering presents selected contributions from the 2024 Conferences on Sustainable Development of Energy,Water and Environment Systems(SDEWES),reflecting recent advances in modelling,system integration,and technology deployment.The included papers address a broad spectrum of challenges relevant to integrated energy–water–environment systems.These include building-sector decarbonisation through hybrid heat pump configurations,geothermal revitalisation of existing oil and gas wells via deep borehole heat exchangers,and techno-economic comparisons of electrochemical batteries and supercapacitors for island energy systems.Further contributions investigate decentralised micro-hydropower solutions tailored to Amazonian conditions,advanced modelling of seepage characteristics in deep tight reservoirs accounting for creep effects,and multi-physical thermal modelling of lithium iron phosphate batteries for residential applications.In addition,hydrogen storage-supported energy system planning using detailed regional housing datasets and retrofit solutions for load balancing in legacy drilling-rig mud pump drives are explored.Collectively,the papers demonstrate how component-level innovation,data-driven planning,and system-level integration can jointly support flexible,resilient,and sustainable energy transitions.By covering diverse applications and geographical contexts,this Special Issue highlights the breadth of the SDEWES research community and provides insights that are relevant for researchers,system planners,and decision-makers working toward integrated energy–water–environment systems.展开更多
The utilisation of waste in green sustainable technology can provide a clean environment and support energy demand.This work aims to design and analyse the performance of a developed indirect flat-plate Solar Air Heat...The utilisation of waste in green sustainable technology can provide a clean environment and support energy demand.This work aims to design and analyse the performance of a developed indirect flat-plate Solar Air Heater(SAH)integrated with an internal thermal storage unit using Waste Automotive Oil(WAO).The SAH was designed based on the circulation of confined air around the internal thermal storage unit due to the updraft effects of hot air.Two SAHs were tested to compare the performance of WAO and water,with the results being compared to previous work that utilised phase change material.Results showed that WAO responds faster in the early stage,while water has slightly higher daytime efficiency,with a maximum temperature of 60℃,while WAO reached a maximum temperature of 76℃.During the discharge cycle,WAO achieved an efficiency of 65.7%,while the water’s efficiency 73.2% within the same period.The highest outlet air temperatures recorded were 43℃ for WAO and 33.8℃ for water.These findings support that water is suitable for applications requiring rapid thermal charging,while WAO offers extended thermal stability.The study highlights the feasibility of using low-cost materials,such as WAO and water,to enhance the performance of solar energy systems,thereby making them more viable for industrial applications like drying and heating.展开更多
The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling tec...The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling technologies into TPUs has the potential to improve their operational flexibility and regulation capability.However,existing research seldom investigates the combined effects of MSTS retrofitting and thermal-electric output coupling on short-term dispatchability,especially under rapid load variation conditions.This study proposes a comprehensive modeling and multi-timescale optimization framework for MSTS-retrofitted TPUs with rapid load variation capability,enabling coordinated thermal and electrical dispatch in both day-ahead and real-time stages.The TPU model incorporates steam heating,electric heating,MSTS charge and discharge characteristics,and ladder typer ramping constraints,enabling detailed representation of thermal-electric coupling interactions.The proposed scheduling framework consists of a day-ahead economic dispatch model and a minute-level intraday rolling optimization.In the day-ahead stage,the model maximizes operational revenue while considering flexibility reserve requirements,multi-period peak shaving,reserve allocation,and thermal-electric coupling strategies that coordinate steam and electric heating with MSTS charging and discharging.In the intraday rolling stage,real-time RES fluctuations and load variations are incorporated to update dispatch decisions,ensuring continuous power–heat balance and efficient use of stored thermal energy.Simulation results verify that thermal-electric coupling enhances the system’s capability to maintain real-time power balance,while MSTS operation effectively mitigates output fluctuations and supports stable,economical operation for addressing RES variation.展开更多
The rapid development of portable electronics,wearable technologies,and healthcare monitoring systems necessitates the innovation of flexible energy storage systems.Considering environmental pollution and the depletio...The rapid development of portable electronics,wearable technologies,and healthcare monitoring systems necessitates the innovation of flexible energy storage systems.Considering environmental pollution and the depletion of fossil resources,the utilization of renewable resources to engineer advanced flexible materials has become especially crucial.Cellulose,the most abundant natural polymer,has emerged as a promising precursor for advanced functional materials due to its unique structure and properties.Typically,the easy processability,tunable chemical structure,self-assembly behavior,mechanical strength,and reinforcing capability enable its utilization as binder,substrate,hybrid electrode,separator,and electrolyte reservoir for flexible energy storage devices.This review comprehensively summarizes the design,fabrication,and mechanical and electrochemical performances of cellulose-based materials.The structure and unique properties of cellulose are first briefly introduced.Then,the construction of cellulose-based materials in the forms of 1D fibers/filaments,2D films/membranes,3D hydrogels and aerogels is discussed,and the merits of cellulose in these materials are emphasized.After that,the various advanced applications in supercapacitors,lithium-ion batteries,lithium-sulfur batteries,sodium-ion batteries,metal-air batteries,and Zn-ion batteries are presented in detail.Finally,an outlook of the potential challenges and future perspectives in advanced cellulose-based materials for flexible energy storage systems is discussed.展开更多
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
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
A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and n...A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and non-storage components in BESS are ana-lyzed.Based on this analysis,steady-state and transient methods for evaluating battery loss are proposed.Second,considering the distinct time-varying characteristics of various BESS components,the load-rate vs.equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools.These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy compo-nents of BESS.Building on this foundation,a time-varying optimization strategy for battery cluster power allocation is developed,aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS.Compared to real-time optimization,this strategy prioritizes global optimality in the time domain,mitigates the risk of dimensionality curse,and enhances BESS efficiency.Finally,a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS.The effectiveness of the proposed strategy is validated under a peak shaving scenario.Results indicate that,after optimization,the annual operational loss of BESS is reduced by 2.40%,while the energy round-trip efficiency is improved by 0.59%.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
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
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
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
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 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
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
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
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.
基金Natural Scientific Research Project of Hunan Province(No's.2022JJ31046 and 2023JJ50027).
文摘Latent heat storage plays an important role in the utilization of solar energy.However,the low thermal conductivity of phase change materials(PCM)significantly reduces the heat transfer efficiency of latent heat storage systems.To enhance its storage/release efficiency,optimizing the fin geometry is essential.This paper establishes a validated three-dimensional numerical model that considers PCM natural convection to study the effects of fin height and number on the heat transfer process.The fin volume of all models is kept constant,and the fin height is determined by the annular space.The impact of fin heights(0.3ΔR,0.5ΔR,0.7ΔR,0.9ΔR)and numbers(4,8,10,16)on heat transfer efficiency was investigated by analyzing the PCM temperature distribution on the shell section,the liquid fraction within the shell over time,and the average heat transfer rate and heat flux.The results show that increasing the fin height from 0.3ΔR to 0.9ΔR reduces the heat storage and release completion times by 61.16%and 45.43%,respectively.Similarly,increasing the number of fins from 4 to 16 reduces the heat storage and release completion times by 33.35%and 31.13%,respectively.The study concludes that increasing both the fin number and height dilutes the heat flux between the fin and PCM during both the heat storage and release processes,with the fin number having a more significant effect on reducing heat flux than fin height.Therefore,when the fin volume remains constant,increasing fin height is more conducive to improving the heat transfer performance of the PCM.These findings will provide a foundation for the application of finned tube energy storage systems in building energy conservation and other fields.
文摘The energy transition increasingly requires holistic approaches that integrate electricity,heating and cooling,water management,industrial processes,transport,and environmental considerations within coherent system frameworks.Such integration is essential for achieving deep decarbonisation while maintaining reliability,affordability,and resource efficiency across diverse regional and sectoral contexts.This Special Issue of Energy Engineering presents selected contributions from the 2024 Conferences on Sustainable Development of Energy,Water and Environment Systems(SDEWES),reflecting recent advances in modelling,system integration,and technology deployment.The included papers address a broad spectrum of challenges relevant to integrated energy–water–environment systems.These include building-sector decarbonisation through hybrid heat pump configurations,geothermal revitalisation of existing oil and gas wells via deep borehole heat exchangers,and techno-economic comparisons of electrochemical batteries and supercapacitors for island energy systems.Further contributions investigate decentralised micro-hydropower solutions tailored to Amazonian conditions,advanced modelling of seepage characteristics in deep tight reservoirs accounting for creep effects,and multi-physical thermal modelling of lithium iron phosphate batteries for residential applications.In addition,hydrogen storage-supported energy system planning using detailed regional housing datasets and retrofit solutions for load balancing in legacy drilling-rig mud pump drives are explored.Collectively,the papers demonstrate how component-level innovation,data-driven planning,and system-level integration can jointly support flexible,resilient,and sustainable energy transitions.By covering diverse applications and geographical contexts,this Special Issue highlights the breadth of the SDEWES research community and provides insights that are relevant for researchers,system planners,and decision-makers working toward integrated energy–water–environment systems.
文摘The utilisation of waste in green sustainable technology can provide a clean environment and support energy demand.This work aims to design and analyse the performance of a developed indirect flat-plate Solar Air Heater(SAH)integrated with an internal thermal storage unit using Waste Automotive Oil(WAO).The SAH was designed based on the circulation of confined air around the internal thermal storage unit due to the updraft effects of hot air.Two SAHs were tested to compare the performance of WAO and water,with the results being compared to previous work that utilised phase change material.Results showed that WAO responds faster in the early stage,while water has slightly higher daytime efficiency,with a maximum temperature of 60℃,while WAO reached a maximum temperature of 76℃.During the discharge cycle,WAO achieved an efficiency of 65.7%,while the water’s efficiency 73.2% within the same period.The highest outlet air temperatures recorded were 43℃ for WAO and 33.8℃ for water.These findings support that water is suitable for applications requiring rapid thermal charging,while WAO offers extended thermal stability.The study highlights the feasibility of using low-cost materials,such as WAO and water,to enhance the performance of solar energy systems,thereby making them more viable for industrial applications like drying and heating.
基金funded by State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project,grant number J2023118.
文摘The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling technologies into TPUs has the potential to improve their operational flexibility and regulation capability.However,existing research seldom investigates the combined effects of MSTS retrofitting and thermal-electric output coupling on short-term dispatchability,especially under rapid load variation conditions.This study proposes a comprehensive modeling and multi-timescale optimization framework for MSTS-retrofitted TPUs with rapid load variation capability,enabling coordinated thermal and electrical dispatch in both day-ahead and real-time stages.The TPU model incorporates steam heating,electric heating,MSTS charge and discharge characteristics,and ladder typer ramping constraints,enabling detailed representation of thermal-electric coupling interactions.The proposed scheduling framework consists of a day-ahead economic dispatch model and a minute-level intraday rolling optimization.In the day-ahead stage,the model maximizes operational revenue while considering flexibility reserve requirements,multi-period peak shaving,reserve allocation,and thermal-electric coupling strategies that coordinate steam and electric heating with MSTS charging and discharging.In the intraday rolling stage,real-time RES fluctuations and load variations are incorporated to update dispatch decisions,ensuring continuous power–heat balance and efficient use of stored thermal energy.Simulation results verify that thermal-electric coupling enhances the system’s capability to maintain real-time power balance,while MSTS operation effectively mitigates output fluctuations and supports stable,economical operation for addressing RES variation.
基金supported by National Natural Science Foundation of China(Grant Nos.32201499,32222057,and 22478142)Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2023A1515012519,2023A0505050114,and 2024B1515040004)+1 种基金National Key Research and Development Project(Grant No 2023YFE0109600)State Key Laboratory of Advanced Papermaking and Paper-based Materials(2024C02).
文摘The rapid development of portable electronics,wearable technologies,and healthcare monitoring systems necessitates the innovation of flexible energy storage systems.Considering environmental pollution and the depletion of fossil resources,the utilization of renewable resources to engineer advanced flexible materials has become especially crucial.Cellulose,the most abundant natural polymer,has emerged as a promising precursor for advanced functional materials due to its unique structure and properties.Typically,the easy processability,tunable chemical structure,self-assembly behavior,mechanical strength,and reinforcing capability enable its utilization as binder,substrate,hybrid electrode,separator,and electrolyte reservoir for flexible energy storage devices.This review comprehensively summarizes the design,fabrication,and mechanical and electrochemical performances of cellulose-based materials.The structure and unique properties of cellulose are first briefly introduced.Then,the construction of cellulose-based materials in the forms of 1D fibers/filaments,2D films/membranes,3D hydrogels and aerogels is discussed,and the merits of cellulose in these materials are emphasized.After that,the various advanced applications in supercapacitors,lithium-ion batteries,lithium-sulfur batteries,sodium-ion batteries,metal-air batteries,and Zn-ion batteries are presented in detail.Finally,an outlook of the potential challenges and future perspectives in advanced cellulose-based materials for flexible energy storage systems is discussed.
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.
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 Key Program of the Na-tional Natural Science Foundation of China(No.52337004).
文摘A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and non-storage components in BESS are ana-lyzed.Based on this analysis,steady-state and transient methods for evaluating battery loss are proposed.Second,considering the distinct time-varying characteristics of various BESS components,the load-rate vs.equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools.These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy compo-nents of BESS.Building on this foundation,a time-varying optimization strategy for battery cluster power allocation is developed,aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS.Compared to real-time optimization,this strategy prioritizes global optimality in the time domain,mitigates the risk of dimensionality curse,and enhances BESS efficiency.Finally,a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS.The effectiveness of the proposed strategy is validated under a peak shaving scenario.Results indicate that,after optimization,the annual operational loss of BESS is reduced by 2.40%,while the energy round-trip efficiency is improved by 0.59%.
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.
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.
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.
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.
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.
