电力需求侧管理2025，Vol.27Issue(4)：57-63,7.DOI:10.3969/j.issn.1009-1831.2025.04.009
考虑新能源随机场景的省间电力现货日前鲁棒调度策略
Day-ahead robust scheduling strategy for inter-provincial electricity spot market considering stochastic scenarios of renewable energy
摘要
Abstract
To address the impact of the uncertainty of renewable energy output on scheduling plans,a robust scheduling method consider-ing stochastic scenarios of renewable energy is proposed.Firstly,for the generation of stochastic scenarios of renewable energy output,the interval and temporal characteristics of errors are taken into account.Kernel density estimation and Markov chain modeling are employed,followed by an improved K-means algorithm for scenario reduction,to generate day-ahead stochastic scenarios of renewable energy output for computation.Secondly,to tackle the issue of intraday deviations of renewable energy output from predicted values,a robust scheduling model incorporating stochastic scenario constraints is constructed,which considers both stochastic scenario constraints and scenario transi-tion constraints.Furthermore,due to the large number of stochastic scenarios leading to an oversized robust scheduling model,a solution method based on stochastic scenario feasibility verification is proposed.Finally,the economic efficiency,safety,and effectiveness of the proposed robust scheduling model and solution method are validated through case studies based on a provincial and regional power grid framework.The results demonstrate that the proposed robust scheduling model can effectively solve the unit commitment problem in power markets with high penetration of renewable energy,and the running time and solution efficiency of the proposed model's solution method are acceptable in practical market applications.关键词
新能源出力/随机场景/鲁棒调度/场景缩减/电力市场机组组合Key words
renewable energy output/stochastic scenarios/robust scheduling/scenario reduction/power market unit commitment分类
信息技术与安全科学引用本文复制引用
王德林,谢文锦,于希娟,王方雨,王海云..考虑新能源随机场景的省间电力现货日前鲁棒调度策略[J].电力需求侧管理,2025,27(4):57-63,7.基金项目
国家电网有限公司总部科技项目(5108-202355047A-1-1-ZN) （5108-202355047A-1-1-ZN）
