考虑多应用场景的储能系统滚动优化运行策略

Liangchun Tang, Minyou Chen, Qiang Li, Bo Li, Wenfa Kang
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引用次数: 2

摘要

随着可再生能源在电力系统中的比重不断提高,电网广泛采用储能来吸收可再生能源。然而,传统的储能运行策略效率较低。为提高储能利用率,本文提出了储能系统在参与电网调度后参与多应用场景联合运行的方法,并建立了日前和日内最优运行模型。在日前阶段,制定以电网运行成本最小为目标的调度计划,并根据电价制定ESS的输出计划,同时考虑电池老化成本;将剩余容量分别参与能源市场、频率调节市场和备用市场的竞价;在日内阶段,考虑电网日前出价约束,采用模型预测控制(MPC)算法进行调度。与经典的MPC算法相比,该模型更有效地利用了ESS的市场出价。在IEEE33总线系统上进行了实例研究,结果验证了所提模型的经济性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rolling Optimization Operation Strategy of Energy Storage System Considering Multiple Application Scenarios
As the proportion of renewable energy in the power system continues to increase, energy storage is widely used in the grid to absorb renewable energy. However, the traditional energy storage operation strategy is less efficient. To improve the utilization rate of energy storage, this paper proposes a method for the energy storage system (ESS) to participate in the joint operation of multiple application scenarios after participating in the grid dispatching and establishes an optimal operation model for day-ahead and intra-day. In the day-ahead stage, dispatching plan with the goal of minimizing power grid operation cost is made, and the ESS’s output plan is made based on the electricity price while considering the aging cost of battery; Then, the remaining capacity of ESS participates in bidding in the energy market, frequency regulation market, and reserve market; In the intra-day stage, dispatching is based on the Model Predictive Control (MPC) algorithm considering the constraint of the ESS’s day-ahead bid value. In this model, the market bid value of ESS is more effectively used compared with the classic MPC algorithm. Case studies are carried out on the IEEE33 bus system, the result verifies the economy and effectiveness of the proposed model.
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