基于金融输电权和BDE算法的双层最优购电组合策略  

Bi-level optimized purchase portfolio based on FTR and BDE algorithm

作　　者：庄晓丹[1] 冯冬涵[2] 甘德强[1] 

机构地区：[1]浙江大学电气工程学院,浙江杭州310027 [2]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《电力自动化设备》2010年第5期11-17,共7页Electric Power Automation Equipment

摘　　要：在输电网开放的电力市场环境下,利用金融输电权(FTR)进行阻塞管理是近年来阻塞管理领域的研究热点,而拍卖是进行FTR分配的主要方式之一。采用FTR对冲阻塞风险,将FTR拍卖市场和电能交易市场相结合,提出了考虑阻塞风险的供电公司双层最优购电组合模型,上层优化以供电公司效用最大化为目标,下层以FTR拍卖收益最大化为目标。在决策过程中综合考虑了电能市场和FTR拍卖市场的双重不确定因素。针对该双层优化模型的随机性特点设计了基于蒙特卡罗和微分进化的双层微分进化(BDE)算法。算例结果证明了适当的FTR可降低购电组合的风险,并表明了该双层模型和算法的合理性和有效性。In the electricity market with open transmission network,FTR（Financial Transmission Rights） is studied recently for congestion management and the auction is widely used to allocate the FTR. A bi-level optimized energy-purchase portfolio model is proposed,which combines the energy transaction market with the FTR auction market,considers the congestion risk and applies the FTR to hedge it. The upper optimization level is to maximize the service of electric utility while the lower optimization level is to maximize the FTR auction benefit. The uncertain factors of both markets are considered in decision-making procedure. A bi-level optimization algorithm based on Monte-Carlo and differential evolution is designed according to the randomicity of the proposed model. The case study demonstrates the reasonability and validity of the model and algorithm.

关 键 词：电力市场 供电公司 购电组合 阻塞风险 金融输电权 双层优化 BDE算法 

分 类 号：TM73[电气工程—电力系统及自动化] F123.9[经济管理—世界经济]