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考虑移动储能引导的柔性配电网定价策略

Pricing strategy for flexible distribution networks guided by mobile energy storage

  • 摘要: 随着电力市场的发展,节点边际电价的概念已渗透到配电网侧。基于电价信息,可实现用户的合理引导。同时,移动储能(mobile energy storage,MES)可作为第三方独立运营商,通过各时段下节点边际电价差异实现盈利,提升配电网运行经济性。因此,提出基于节点边际电价引导的MES调度策略。首先,基于考虑网络损耗的灵敏度计算,建立柔性配电网(flexible distribution network,FDN)线性运行模型;然后,构建以MES盈利最大和柔性配电网运行成本最小的双层定价引导模型;最后,基于卡罗需-库恩-塔克(karush-kuhn-tucker,KKT)条件和均衡约束数学规划理论,实现模型的高效求解。算例结果表明,所提方法能有效引导MES出力,在实现MES运营商盈利的同时,显著提升配电网运行水平。在正常运行场景下可降低FDN运行总成本5.14%;在故障场景下,可将负荷恢复率提升至98.07%,并降低供电恢复成本39.1%。该策略为协同提升MES盈利与配电网经济性、可靠性提供了有效解决方案。

     

    Abstract: With the development of the electricity market, the concept of nodal marginal electricity price has permeated the distribution network side. Based on electricity price information rational guidance of users can be achieved. Meanwhile, mobile energy storage (MES) can act as a third-party independent operator, achieving profitability through the price differences of nodal marginal electricity different time periods, thereby improving the economic efficiency of distribution network operation. Therefore, a scheduling strategy for MES based on nodal marginal electricity price guidance is proposed. First, based on sensitivity calculation considering network, a linear operation model of the flexible distribution network (FDN) is established; then, a bi-level pricing guidance model is constructed with the objectives of maximizing MES profit and FDN operation cost; finally, the efficient solution of the model is achieved based on the Karush-Kuhn-Tucker (KKT) conditions and the theory of equilibrium constrained programming. Case study results show that the proposed method can effectively guide MES output, significantly improving the distribution network operation level while achieving MES operator profitability. Under normal operation scenarios, it can the total FDN operation cost by 5.14%; under fault scenarios, it can increase the load recovery rate to 98.07% and reduce the power supply cost by 39.1%. This strategy provides an effective solution for synergistically improving MES profitability and the economic efficiency and reliability of the distribution network.

     

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