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

电动汽车作为移动电源在系统负荷高峰期向电网供电时，电网应给予电价激励，该价格应由电动汽车代理商和电力公司协商确定。针对该问题，研究了电动汽车代理商与电力公司在电动汽车参与系统调峰调度时的谈判策略，建立了基于模糊贝叶斯学习的放电电价双边谈判函数模型。模型中，首先，根据电动汽车代理商和电力公司的成本及收益预估，计算谈判函数中确定性参数。同时，提出基于模糊概率对不确定信息进行模糊估计的计算方法，分别估算电力公司和电动汽车代理商各自谈判函数中的不确定性参数。然后，将上述参数代入基于模糊贝叶斯学习的谈判模型中，得出电动汽车放电电价。最后，通过算例对提出的谈判模型进行仿真分析验证文中方法的有效性。

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 fimction 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.