考虑多重不确定性的电动汽车聚合商参与能量-调频市场的鲁棒优化模型

A Robust Optimization Model for Electric Vehicle Aggregator Participation in Energy and Frequency Regulation Markets Considering Multiple Uncertainties

为了充分挖掘电动汽车(EV)参与电力市场交易的市场价值,电动汽车聚合商(EVA)可将众多EV资源聚合起来作为一个投标主体参与日前能量和调频市场。针对EVA参与电力市场的投标决策面临多重不确定性因素影响问题,计及EV电量和功率边界,建立了EVA响应能力评估模型;对EV用户响应意愿、调频信号和市场电价的不确定性进行建模;以EVA的投标净收益最大化为目标,构建一种考虑多重不确定性的EVA参与能量-调频市场的鲁棒优化模型,以合理制定次日各交易时段EVA的基线功率和所提供的调频容量。通过算例验证了模型的有效性,并分析了各种不确定因素对投标净收益的影响,所提策略可为EVA的投标决策提供参考。

In order to fully exploit the market value of electric vehicle(EV)participation in the electricity market,EV aggregator(EVA)can aggregate large number of EV resources to participate in the day-ahead energy and frequency regulation markets as a bidding entity.To address the problem that EVA face multiple uncertainties in bidding decisions to participate in the electricity market,a response capability evaluation model of EVA is developed,the uncertainty characteristics of EV users'willingness to respond,frequency regulation signals and market electricity prices are modeled,and a robust optimization model for EVA participation in the energy and frequency regulation markets considering multiple uncertainties is constructed.Firstly,the energy and power boundaries of an individual EV are evaluated,and the energy and power boundaries of the EVA are obtained by aggregation,based on which the response capability evaluation model of the EVA is constructed.Furthermore,the uncertainties facing by EVA participation in the energy and frequency regulation markets are modeled.Among them,EV users'willingness to respond is characterized based on consumer psychology principles,and EVA energy accumulation triggered by frequency regulation signals is portrayed by frequency regulation energy coefficients.Uncertainties including EV users'willingness to respond,frequency regulation signals and market electricity prices can be handled by robust optimization methods.Finally,A robust optimization model for EVA participation in the energy and frequency regulation markets considering multiple uncertainties is constructed with the objective of maximizing the net bidding revenue of EVA.The bidding strategies of EVA in the day-ahead electricity market under several scenarios are constructed and their net bidding revenues are compared.The case simulation results show that the proposed robust optimization model can reasonably formulate the dispatching strategy for EVA to participate in the day-ahead energy and frequency regulation markets.Based on the case simulation results,the main conclusions can be obtained as follows.①EVA mainly profits by participating in the frequency regulation market,and it is more appropriate for EVA to participate in the frequency regulation market in order to fully reflect the market value of EVA.②Increasing the incentive level can increase the response willingness of EV users,which in turn increases the response capability of EVA,and to a certain extent can improve the bidding revenue of EVA.However,increasing the incentive level may make the dispatching cost of EVs increase significantly,and the net revenue of EVA decreases instead.Therefore,EVA should set a reasonable incentive level according to the frequency regulation demand.③Increasing the robust control coefficient can reduce the bidding risk of EVA,but the net bidding revenue also decreases.The robustness of different uncertainty factors has different degrees of importance on the net bidding revenue of EVA,among which the uncertainty of frequency regulation signal has the greatest impact on the net bidding revenue of EVA.④The model proposed comprehensively considers the impact of various uncertainties faced by EVA in the energy and frequency regulation markets joint optimization bidding decision,and the optimization results can provide a reliable reference for EVA's bidding decision.