摘要
我国风能、太阳能资源富集地与负荷存在时空错配问题,利用同一区域内风能和太阳能之间的相关性与互补性,采用电-氢协同储能模式,是缓解可再生能源出力对电网不良影响的有效技术路径。使用非参数核密度估计法拟合风、光出力数据的概率分布规律,结合Copula理论生成计及风光时空相关性的时序场景;考虑风、光发电的相关性,进一步建立了电-氢协同储能综合能源系统的经济性日前优化调度模型,并使用自适应模拟退火粒子群优化(ASA-PSO)算法求解。仿真结果表明:相比于基本PSO算法,ASA-PSO算法具有更高的求解速度与精度;电-氢协同储能系统的日前经济优化调度方案节省了约19%的日运行成本,可以避免系统在电价高峰时段大量购入电力并实现了波动性新能源的就地消纳,可为友好型规模化电网的构建提供电-氢柔性匹配方法。
In China,there is a spatiotemporal mismatch between the areas rich in wind and solar energy resources and the load centers.By leveraging the correlation and complementarity between wind and solar energy within the same region,an electricity-hydrogen coordinated energy storage model was proposed,which was an effective technical approach to mitigate the adverse impact of renewable energy output on the power grid.The probability distribution patterns of wind and photovoltaic power output data were fitted using the nonparametric kernel density estimation method,and time-series scenarios considering the spatiotemporal correlation of wind and photovoltaic power were generated using Copula theory.By considering the correlation between wind and photovoltaic power generation,an economic day-ahead optimal scheduling model for the integrated electricity-hydrogen coordinated energy system was further established,and solved using the adaptive simulated annealing particle swarm optimization(ASA-PSO)algorithm.The simulation results showed that compared to the basic PSO algorithm,the ASA-PSO algorithm demonstrated superior solving speed and accuracy.The economic day-ahead optimal scheduling scheme for the electricity-hydrogen coordinated energy storage system reduced daily operating costs by approximately 19%,avoided large-scale electricity purchases during peak price periods,and enabled local consumption of fluctuating renewable energy.It provides a flexible electricity-hydrogen matching approach for constructing a grid-friendly and large-scale power system.
作者
王芊瑞
阮景昕
王跃社
WANG Qianrui;RUAN Jingxin;WANG Yueshe(State Key Laboratory of Multiphase Flow in Power Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Nari Technology Company Limited,Nanjing 211106,China)
出处
《综合智慧能源》
2025年第12期34-45,共12页
Integrated Intelligent Energy
基金
国家重点研发计划项目(2024YFF0505802)。
关键词
电-氢耦合
储能
可再生能源
COPULA理论
核密度估计
经济性
优化调度
ASA-PSO算法
electricity-hydrogen coupling
energy storage
renewable energy
Copula theory
kernel density estimation
economic efficiency
optimal scheduling
ASA-PSO algorithm
