风电功率波动平抑下储能出力与平滑能力的动态优化控制策略

Dynamic optimization control strategy for energy storage output power and smoothing ability considering smoothing wind power fluctuation

风电场并网处布置储能系统能改善并网经济性,平抑风电并网功率波动。然而,储能出力优化电网运行性能受储能系统的功率、容量和能量状态等诸多因素影响。本文引入储能电池出力能力指标,设计了保护储能电池和保障并网功率平衡能力的多目标优化模型,提出一种基于储能荷电状态模糊动态调节的模型预测控制策略,在整体上保证储能出力最小水平,在局部储能高充/放电区域的时段内提高储能充/放电出力能力,并将本文方法与传统模型预测方法进行仿真对比。结果表明,在相同储能配置比例下,本文方法能有效平抑风电功率波动,综合指标均优于传统模型预测方法,在优化负荷功率波动的同时也提高了储能系统的功率支撑能力,平衡了储能输出和平滑能力的矛盾。

Deploying an energy storage system at the grid connection of a wind farm can improve the economics of grid connection and smooth the fluctuation of grid-connected power of wind power.However,optimizing the operation performance of the power grid by shifting the space-time characteristics of the power grid load is subjected to many factors such as the power,capacity,and energy status of the energy storage system.In order to solve the contradiction between the output and smoothing ability of the energy storage system.This paper introduces the output capacity index of energy storage battery,and designs a multi-objective optimization model to protect the energy storage battery and guarantee the power balance capacity of grid connection.Moreover,it proposes a model predictive control strategy based on fuzzy dynamic adjustment of the energy storage charge state,which can ensure the minimum level of energy storage as a whole,and improve the capacity of energy storage in the period of high charge/discharge area of partial energy storage.The method in this paper is compared with the conventional model prediction method.The results show that,under the same proportion of energy storage configuration,the strategy proposed in this paper can suppress the wind power fluctuation,and the comprehensive index is better than that of the conventional model prediction method.It not only optimizes the load power fluctuation,but also improves the power support ability of the energy storage system,and balances the contradiction between the energy storage output and the smoothing ability.