基于鲁棒均值–方差优化的发电自调度算法及鲁棒代价分析  

Robust Mean-Variance Optimization for Self-scheduling of Thermal Producer and Its Price of Robustness

作　　者：丁涛[1] 柏瑞 孙宏斌[1] 黄灿[3] 李方兴[3] 

机构地区：[1]电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系),北京市海淀区100084 [2]美国中西部电网独立输电系统运行公司,明尼苏达州圣保罗55108 [3]美国田纳西大学电气工程与计算机科学系,田纳西州诺克斯维尔37996

出　　处：《中国电机工程学报》2015年第2期319-326,共8页Proceedings of the CSEE

基　　金：国家重点基础研究发展计划项目(973项目)(2013CB228203);国家杰出青年科学基金(51025725)~~

摘　　要：解除管制电力市场背景下,发电厂商作为价格的接受者,需向电力交易中心提供发电交易策略来最大化自身的收益,从而形成发电自调度的优化模型。然而,当考虑电价不确定性时,发电商一方面希望最大化收益,另一方面需要最小化不确定性带来的风险。为此,该文建立了一种鲁棒均值方差优化模型,以收益最大化和风险最小化为多目标,进而获得多目标优化的Pareto前沿。通过等价转化发现,鲁棒均值方差模型与非鲁棒均值方差模型具有相同的数学形式,均为一个二阶锥优化。进一步分析了鲁棒模型对收益、风险以及Pareto前沿的代价。最后采用30节点系统对鲁棒均值方差优化的发电厂自调度模型以及鲁棒代价进行详细的分析和对比,结果证明提出方法和分析的正确性。In deregulated electricity markets, generation companies with the aim of maximum revenue need to provide trading strategies to the electricity trading market, which contributed to a self-scheduling model. When considering the uncertainty of price, the trading strategies are required to maximize the revenue as well as minimizing the risks brought by uncertainties. In this paper, a multi-objective robust mean-variance model was proposed to solve the above problem and the Pareto frontier of the multi-objective optimization was obtained. Moreover, the proposed robust mean-variance model could be equivalently transformed into a non-robust mean-variance model which was casted as a second-order cone programming（SOCP） optimization. The price of robustness to benefits, risks, and the Pareto frontier were analyzed. Finally,the robust mean-variance model based self-scheduling model optimization and its budget of robustness were tested on a30-bus system. The simulation results demonstrate the effectiveness of the proposed method and analysis.

关 键 词：发电自调度 二阶锥规划 半正定规划 多目标优化 鲁棒均值–方差优化 帕累托前沿 节点电价 

分 类 号：TM73[电气工程—电力系统及自动化] F123[经济管理—世界经济]