在抽水蓄能等大规模储能电站同时参与现货交易与电网调度的情况下,电网对抽水蓄能的调度难以直接触及对现货市场中可再生电能的消纳.对此,考虑电能现货交易为电网抽水蓄能调度带来的影响,提出内嵌市场博弈模型的多主体协调调度方法.首先,结合电力现货市场出清模型,以抽水蓄能电站现货市场经济收益最大化为目标,制定抽水蓄能电站参与电能现货交易策略.然后,结合两部制电价政策,以最小化电网运行成本与全网新能源弃用量为目标,制定电网运营商对抽水蓄能的容量分配与功率调度策略.制定所提调度策略需要求解内嵌博弈模型的双层优化问题,即抽水蓄能电站参与电能现货市场交易决策问题和内嵌市场博弈模型的抽水蓄能容量分配与功率调度策略优化问题.抽水蓄能参与现货市场决策问题服从Stackelberg博弈模型,通过强对偶理论将其内嵌至抽水蓄能容量分配与功率调度策略优化问题,并通过第2代非支配遗传算法(NSGA-II)对抽水蓄能容量分配与功率调度策略双优化问题进行求解.最后,依托华东某抽水蓄能电站的运行数据构建仿真模型,对所提方法进行验证.测试结果表明,所提方法可以有效协调电网直接调度与抽水蓄能参与电能现货市场的决策方案,提升抽水蓄能经济效益,降低电网运行成本,提高新能源消纳水平.

In the context of large-scale energy storage stations, such as pumped storage, participating in both spot trading and grid scheduling, it is difficult for the grid to directly access the consumption of renewable energy in the spot market. In this regard, the influence of spot electricity trading on the pumped storage scheduling is considered and a multi-agent scheduling method with an embedded market game model is proposed. First, combined with the power spot market clearing model, with the objective of maximizing the benefits of the pumped storage power station in the spot market, a strategy for the pumped storage power station to participate in the spot trading of electric energy is developed. Then, combined with the two-part electricity price policy, the capacity allocation and power dispatching strategy of the grid operator about the pumped storage is formulated to minimize grid operating costs and the amount of renewable energy discarded in the entire grid. To formulate the proposed scheduling strategy, a bi-level optimization problem with an embedded game model is solved: the decision-making problem of the pumped storage power station participating in the electric energy spot market, and the optimization with the embedded marketing game model of capacity allocation and power scheduling strategy about pumped storage. The decision-making problem of pumped storage in the spot market follows a Stackelberg game model, which is integrated into the optimization problem of pumped storage capacity allocation and power scheduling strategy via the strong dual theory. The embedded bi-objective problem is solved by using the NSGA-II algorithm. Finally, based on the data from a pumped storage power station in East China, a simulation model is built to verify the effectiveness of the proposed method. The test results show that the proposed method can effectively coordinate the decision-making of direct grid dispatching and pumped storage participation in the electric energy spot market, enhancing the economic benefits of pumped storage, reducing the operating cost of the grid, and improving the consumption of renewable energy.