摘要
随着电力体制改革的不断推进,售电公司作为新的市场主体,准确把握市场机遇,明确市场交易策略尤为重要。为此,立足于中长期电力交易机制,全面考虑多样化市场交易品种,引入合同转让交易和偏差电量考核作为市场化电力电量平衡机制,建立售电公司购电策略优化模型,以售电公司收益最大化为目标,采用混合自适应细菌觅食优化的改进粒子群算法(ABFO-PSO)进行模型求解,最后通过算例分析,验证所建模型和方法的有效性;该研究可为售电公司参与市场竞争提供参考。
With the continuous advancement of power system reform,as a new market entity,it is particularly important for electricity retailers to grasp the business opportunities accurately and understand market trading strategies clearly.Therefore,based on the medium-term and long-term electricity trading mechanism,by taking full account of the diversity of power market and trade,this paper introduces the contract transfer transaction and the energy deviation penalty assessment as the market power balance mechanism,then establishes the optimization decision model of electricity purchasing strategies for electricity retailers.Aiming at the maximization of the profit,a hybrid adaptive bacterial foraging method,i.e.,particle swarm optimization algorithm(ABFO-PSO)is adopted to solve the problem.Finally,the validity of the model and method is verified through case studies.
作者
贾晨
杜欣慧
JIA Chen;DU Xinhui(College of Electrical&Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China;State Grid Taiyuan Power Supply Company,Taiyuan 030012,China)
出处
《中国电力》
CSCD
北大核心
2019年第9期140-147,共8页
Electric Power
关键词
电力市场
售电公司
中长期交易
购电策略
粒子群算法
electricity market
electricity retailers
medium and long-term electricity transaction
electricity purchasing strategy
particle swarm optimization