摘要
针对风电出力预测误差对区域间可用输电能力(ATC)评估的影响,提出一种计及风电出力相关性和条件风险价值(CVaR)的电力系统区域间ATC概率评估方法。首先,通过基于历史风电出力数据的相关系数矩阵和Copula函数,构建计及风电场出力空间相关性的风电出力预测误差概率模型;接着,基于获得的计及风电出力空间相关性的风电出力预测误差修正风电场出力预测值;然后,提出一种计及风电出力相关性和CVaR的ATC概率评估双层优化模型,下层模型以基态下发电成本和风险费用最小为目标,上层模型以极大化区域间ATC为目标,通过基态下和极限状态下机组的出力作为上下层模型间的交互信息;在此基础上,利用Karush-Kuhn-Tucker(KKT)最优条件,对下层模型进行转换,将双层优化模型转换为均衡约束的数学规划(MPEC)模型;进一步,将MPEC模型转换为混合整数二阶锥规划问题,进而实现概率ATC的求解;最后,通过PJM-5节点测试系统和吉林西部电网进行算例分析,结果验证了所提方法的可行性和有效性。
To consider the impact of wind power output forecasting errors on the assessment of available transfer capability(ATC),this paper proposes a probabilistic ATC assessment method of power system considering wind power correlation and conditional value-at-risk(CVaR).First of all,the correlation coefficient between wind farms is calculated through the historical wind power output data,and the correlation coefficient matrix among wind farms is obtained.Then,the probability distribution and Copula function of wind farm output prediction are used to construct a probability model of wind power output prediction error considering spatial correlation.According to the wind power output forecast error data and wind farm output prediction value that meet the correlation of actual wind farm output,the output prediction of wind farm is corrected,and then the revised wind power output forecast is used as the input for calculating interregional ATC.After that,this paper proposes a bi-level optimal model considering the correlation of wind power output and CVaR for probabilistic ATC assessment.The lower level model aims to minimize the generation cost and risk under the base state.The upper level model aims at maximizing inter-regional ATC by taking power output under base state and extreme state as the interaction information between the upper and lower level models.On this basis,the Karush-Kuhn-Tucker(KKT)optimal conditions are used and the bi-level model is converted into a mathematical program with equilibrium constraints(MPEC)model.The MPEC model is further transformed into a mixed integer second-order cone programming form,and then the probabilistic ATC can be solved.Finally,the PJM-5 bus test system and Jilin Western Power Grid are used to analyze the example.In the PJM-5 bus test system,when the confidence level is taken by 90%,as the correlation coefficient increases from 0.5 to 0.9,the correlation of wind farm output gradually increases,and the inter-regional probability ATC expectation first increases and then decreases
作者
李雪
李佳奇
张儒峰
李筱婧
王茗萱
Li Xue;Li Jiaqi;Zhang Rufeng;Li Xiaojing;Wang Mingxuan(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education Northeast Electric Power University,Jilin 132012,China;State Grid Jilin Electric Power Company,Changchun 130021,China)
出处
《电工技术学报》
EI
CSCD
北大核心
2023年第15期4162-4177,共16页
Transactions of China Electrotechnical Society
基金
吉林省自然科学基金资助项目(YDZJ202101ZYTS194)。
关键词
可用输电能力
风电出力相关性
条件风险价值
双层优化模型
Available transfer capability
wind power output correlation
conditional value-at-risk
bi-level optimal model
