中国电机工程学报2023，Vol.43Issue(24)：9411-9422,中插3,13.DOI:10.13334/j.0258-8013.pcsee.230820
基于C藤Copula及条件风险价值的综合能源系统灵活爬坡优化调度
Flexible Ramping Optimal Scheduling of Integrated Energy System Based on C-vine Copula and Conditional Value at Risk
摘要
Abstract
With the increase of renewable energy penetration,the net load fluctuation becomes larger.Therefore,a flexible ramping optimal scheduling method of integrated energy systems is proposed in this paper for the uncertain change of net load,combining the correlation of prediction error and conditional value at risk(CVaR).First,the initial power of scenic load is predicted by a neural network model,and the joint probability distribution of prediction errors of multivariate random variables is constructed by using the method of the C-vine Copula function for the prediction errors,and a flexible ramping product design method is proposed accordingly.Then,considering the conditional value at risk of scenic abandonment and load cutting brought by net load uncertainty,a flexible ramping product risk value is constructed.Later,an optimal scheduling model of integrated energy system considering the value at risk of flexible ramp climbing product is constructed considering the net load uncertainty.Simulation results show that optimization considering the correlation of load forecasting errors has improved the overall economic efficiency of the system by 1.22%.Both load shedding and curtailed wind power have decreased by 17.01%,validating the effectiveness of the proposed method.The CVaR values at different confidence levels can provide a certain risk reference for the scheduling of integrated energy systems.关键词
Copula 理论/灵活爬坡产品/净负荷不确定性/综合能源系统调度/条件风险价值Key words
Copula theory/flexible ramping product/net load uncertainty/integrated energy system scheduling/conditional value at risk分类
信息技术与安全科学引用本文复制引用
黄悦华,刘兴韬,张磊,陈庆,张子豪,涂金童,章轩瑞..基于C藤Copula及条件风险价值的综合能源系统灵活爬坡优化调度[J].中国电机工程学报,2023,43(24):9411-9422,中插3,13.基金项目
国家自然科学基金项目(52007103,62233006).Project Supported by National Natural Science Foundation of China(52007103,62233006). （52007103,62233006）
