分档电价和碳配额激励的含电动汽车微电网优化调度策略

在含电动汽车（Electric Vehicle，EV）微电网的调峰调度中，实施分时电价或实时电价引导EV参与调峰，会导致EV过度响应或响应疲惫现象。为此，本文提出了分档电价协同碳配额激励机制下的含电动汽车微电网博弈优化调度策略。建立了微电网与电动汽车的主从博弈优化调度模型，微电网主体以运行成本最小和极小化负荷均方差为优化目标，考虑新能源发电完全消纳，针对等效净负荷水平制定分档电价并和碳配额协同激励，引导电动汽车在新能源发电余缺时充放电的适度响应；电动汽车用户从体响应微电网激励优化电动汽车充放电行为使其成本最小。采用粒子群算法(particle swarm optimization, PSO)求解优化模型纳什均衡点，获得微电网侧最优分档电价和电动汽车调度策略的集合。通过仿真算例验证了所提方法的有效性。

Optimal dispatching strategy for electric vehicle microgrid incentivized by Ladder electricity price and carbon quota

In the peak regulation of microgrid (MG) with Electric Vehicle (EV), the implementation of time-of-use price or real-time price policy guiding EV to participate in peak regulation of MG will lead to the problems of EV over-response or response exhaustion. For this reason, a game optimization scheduling strategy for MG with EVs was proposed under the incentive mechanism of Ladder electricity price and carbon quota. A master-slave game optimization scheduling model is developed with MG as the leader and EVs as the follower. Considering the complete consumption of new energy power generation, with the minimum operation cost and minimum mean load square error as the objectives, Ladder electricity price is formulated based on equivalent net load levels and is cooperated with carbon quotas, guiding EVs to charge and discharge responding to the surplus and deficiency of new energy power generation; Electric vehicle users respond to microgrid incentive policy to optimize EV charging and discharging behavior to minimize its cost. Particle swarm optimization method is used to solve the Nash equilibrium point of the game optimization model, and the MG optimal Ladder price and EV scheduling strategy are obtained. Finally, simulation examples was carried out to verify the correctness and effectiveness of the proposed method.