中国电机工程学报2018，Vol.38Issue(1)：61-71,后插7,12.DOI:10.13334/j.0258-8013.pcsee.162593
基于模糊贝叶斯学习的电动汽车放电电价谈判策略
The Negotiation Strategy of Discharging Price of Electric Vehicle Based on Fuzzy Bayesian Learning
摘要
Abstract
Some subsidy of price should be given to the electric vehicle (EV), when it supply power to the system at peak time as a mobile power resource. And the price should be determined by the EV agents and power companies. To solve the problem, a scheduling negotiation strategy between EV agents and power companies which focus on how to shape the load at peak time was studied, and then the bilateral negotiation function model of discharging price based on fuzzy Bayesian learning was established in this paper. In this model, firstly, the certain parameters of the function were calculated according to the cost and profits of the EV agents and power companies. And the fuzzy probability calculation method was proposed to estimate and calculate the uncertain parameter of the function of EV agents and power companies respectively. Moreover, the fuzzy negotiation model based on Bayesian learning was established to calculate the discharging price by using the parameters above. Finally, the negotiation strategy proposed in this paper was verified to be effective by a practical example.关键词
电动汽车/放电电价/模糊概率/谈判函数/模糊贝叶斯学习Key words
electric vehicle/discharging price/fuzzy probability/negotiation Function/fuzzy Bayesian learning分类
信息技术与安全科学引用本文复制引用
张谦,蔡家佳,李春燕,刘桦臻,李东..基于模糊贝叶斯学习的电动汽车放电电价谈判策略[J].中国电机工程学报,2018,38(1):61-71,后插7,12.基金项目
国家自然科学基金项目(51507022). Project Supported by National Natural Science Foundation of China (51507022). （51507022）
