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Multi-Objective Sizing of Solar-Wind-Hydro Hybrid Power System with Doubled Energy Storages Under Optimal Coordinated Operational Strategy

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摘要 More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.
出处 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2023年第6期2144-2155,共12页 中国电机工程学会电力与能源系统学报(英文)
基金 the National Key Research and Development Program of China 2018YFE0128500 the Fundamental Research Funds for the Central Universities of China under Grant B210202069.
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  • 1J.Charles Smith.中国电力市场在大规模可再生能源并网中面临的主要问题[J].中国电力,2012,45(12):1-3. 被引量:8
  • 2徐大明,康龙云,曹秉刚.基于NSGA-Ⅱ的风光互补独立供电系统多目标优化[J].太阳能学报,2006,27(6):593-598. 被引量:37
  • 3C A Coello Coello.A Comprehensive survey of evolutionary-based multiobjective optimization,techniques.Knowledge and Information Systems,1999,1(3):269~308
  • 4J D Schaffer.Multiple objective optimization with vector evaluated genetic algorithms.The First Int'l Conf on Genetic Algorithms,Lawrence Erlbaum,1985
  • 5D A V Veldhuizen,G B Lamont.Multiobjective evolutionary algorithm research:A history and analysis.Department of Electrical and Computer Engineering,Graduate School of Engineering,Air Force Institute of Technology,Tech Rep:TR-98-03,1998
  • 6R Eberhart,J Kennedy.A new optimizer using particle swarm theory.In:Proc of the 6th Int'l Symposium on Micro Machine and Human Science.Piscataway,NJ:IEEE Service Center,1995.39~43
  • 7J Kennedy,R Eberhart.Particle swarm optimization.IEEE Int'l Conf on Neural Networks,Perth,Australia,1995
  • 8K E Parsopoulos,M N Vrahatis.Particle swarm optimizer in noisy and continuously changing environments.In:M H Hamza ed.Artificial Intelligence and Soft Computing.Iasted:ACTA Press,2001.289~294
  • 9K E Parsopoulos,M N Vrahatis.Particle swarm optimization method for constrained optimization problems.Euro-Int'l Symp on Computational Intelligence 2002,Slovakia,2002
  • 10R C Eberhart,X Hu.Human tremor analyis using particle swarm optimization.IEEE Congress on evolutionary computation (CEC 1999),Washington,D C,1999

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