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Second-Life Battery Energy Storage System Capacity Planning and Power Dispatch via Model-Free Adaptive Control-Embedded Heuristic Optimization
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作者 Chuan Yuan Chang Liu +5 位作者 Shijun Chen Weiting Xu Jing Gou Ke Xu Zhengbo Li Youbo Liu 《Energy Engineering》 2025年第9期3573-3593,共21页
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
关键词 Second-life battery energy storage systems model-free adaptive voltage control bilevel optimization framework heterogeneous battery degradation model heuristic capacity configuration optimization
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Optimization Configuration Analysis of Wind-Solar-Storage System Based on HOMER
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作者 Daixuan Zhou Zhichao Wang +2 位作者 Kaile Xi Chong Zuo Yan Jia 《Energy Engineering》 2025年第5期2119-2153,共35页
HOMER(Hybrid OptimizationModel for Electric Renewables)is an effective simulation and optimization platform for hybrid renewable energy.By inputting specific users’energy resource data(such as wind speed,solar radiat... HOMER(Hybrid OptimizationModel for Electric Renewables)is an effective simulation and optimization platform for hybrid renewable energy.By inputting specific users’energy resource data(such as wind speed,solar radiation,etc.)and load data,and by determining the types and models of components selected by the user,HOMER calculates and simulates the operational status of each component at every time step.Ultimately,it computes the energy balance of the system within specified constraints to simulate the overall system operation.This approach enables the reasonable determination of system component capacities,the evaluation of system feasibility,and the calculation of costs over the entire lifecycle of the system.In response to the challenges of matching capacities and high construction costs in wind-solar-storage multi-energy complementary power generation systems,This paper addresses issues such as difficulty in matching component capacities,high construction costs,and low system reliability in multi-energy complementary power generation systems.Using the HOMER hybrid renewable energy simulation and optimization platform,we constructed various hybrid energy systems for a specific region and considered multiple power supply modes.Thesoftware was used to solve for the optimal capacities and costs of each system.Four scenarios were analyzed:grid-only,grid-connected(purchase-sale)wind-solar-storage system,grid-connected(sale)wind-solar-storage system,and off-grid wind-solar-storage system.The results were compared and analyzed.HOMER can assess systemfeasibility and calculate the cost over its entire lifecycle.By inputting 8760 h of wind and solar resource data and load data for a specific region,and considering multiple system structures and power supply modes,the configuration results were evaluated using indicators such as cost and renewable energy utilization ratio.The simulation results indicate that the Net Present Cost(NPC)values across four different scenarios range from 1,877,292 CNY to 3,222,724 CNY,demonstrating significant cost differences.Among these scenarios,the grid-connected(purchase-sell)wind-solarstorage system exhibited the lowest NPC and the highest renewable energy utilization rate.Compared to a system relying solely on the grid,the NPC was reduced by 305,695 CNY,and the renewable energy utilization rate reached 74.7%. 展开更多
关键词 Wind-solar-storage system HOMER software capacity optimization configuration
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Capacity Optimization Configuration of Hydrogen Production System for Offshore Surplus Wind Power 被引量:1
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作者 Yanshan Lu Binbin He +6 位作者 Jun Jiang Ruixiao Lin Xinzhen Zhang Zaimin Yang Zhi Rao Wenchuan Meng Siyang Sun 《Energy Engineering》 EI 2023年第12期2803-2818,共16页
To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of re... To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power.By studying the mathematical model of wind power output and calculating surplus wind power,as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank,an innovative capacity optimization allocation model was established.The objective of the model was to achieve the lowest total net present value over the entire life cycle.The model took into account the cost-benefit breakdown of equipment end-of-life cost,replacement cost,residual value gain,wind abandonment penalty,hydrogen transportation,and environmental value.The MATLAB-based platform invoked the CPLEX commercial solver to solve the model.Combined with the analysis of the annual average wind speed data from an offshore wind farm in Guangdong Province,the optimal capacity configuration results and the actual operation of the hydrogen production system were obtained.Under the calculation scenario,this hydrogen production system could consume 3,800 MWh of residual electricity from offshore wind power each year.It could achieve complete consumption of residual electricity from wind power without incurring the penalty cost of wind power.Additionally,it could produce 66,500 kg of green hydrogen from wind power,resulting in hydrogen sales revenue of 3.63 million RMB.It would also reduce pollutant emissions from coal-based hydrogen production by 1.5 tons and realize an environmental value of 4.83 million RMB.The annual net operating income exceeded 6 million RMB and the whole life cycle NPV income exceeded 50 million RMB.These results verified the feasibility and rationality of the established capacity optimization allocation model.The model could help advance power system planning and operation research and assist offshore wind farm operators in improving economic and environmental benefits. 展开更多
关键词 Surplus wind power offshore wind power hydrogen generation capacity optimization configuration total net present cost
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Multi-objective capacity allocation optimization method of photovoltaic EV charging station considering V2G 被引量:10
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作者 ZHENG Xue-qin YAO Yi-ping 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第2期481-493,共13页
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed... Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency. 展开更多
关键词 vehicle to grid (V2G) capacity configuration optimization time-to-use (TOU) price multi-objective optimization NSGA-Ⅱ algorithm NSGA-SA algorithm
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Optimal Configuration Method for the Installed Capacity of the Solar-Thermal Power Stations 被引量:1
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作者 Yan Wang Zhicheng Ma +3 位作者 Jinping Zhang Qiang Zhou Ruiping Zhang Haiying Dong 《Energy Engineering》 EI 2023年第4期949-963,共15页
Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we p... Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise. 展开更多
关键词 Solar-thermal power station optimal configuration of installed capacity new energy base multi-objective optimization chance constrained planning theory
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