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基于减载风电和储能的双层模型预测控制风电波动平抑策略

Predictive Control and Suppression Strategy for Wind Power Fluctuation Based on a Double Layer Model on Load Shedding Wind Power and Energy Storage
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摘要 储能在平抑风电功率快速波动过程中频繁地充放电和过高地放电将深度影响储能寿命。为此,提出一种减载风电和储能协同平抑风电功率的方法,利用减载风电出力来减小储能充放电切换次数和放电深度。建立风储系统模型,利用双层模型预测控制优化方法:上层控制基于风功率预测数据进行滚动优化,在满足风电并网波动要求基础上,以储能和减载风电总出力最小为目标函数,通过模型预测控制方法求得储能和减载风电总功率;下层控制以储能功率变化率最小和出力能力最大为目标函数,通过模型预测控制方法分配储能和减载风电出力。最后对某风电场进行仿真研究。结果表明,所提控制策略使储能寿命和出力能力得到有效提升。 In the process of suppressing rapid fluctuations in wind power,frequent charging and discharging of energy storage operations and excessively high discharge depths will affect the energy storage life.For this reason,a method was proposed to address the issue by coordinating load shedding wind power and energy storage to suppress wind power.The switching frequency and depth of energy storage charging and discharging was reduced by utilizing load shedding wind power output.A wind storage system model was established and a two-level model prediction control optimization method was used:the upper level control was based on wind power prediction data for rolling optimization,on the basis of meeting the fluctuation requirements of wind power grid connection,the objective function was to minimize the total output of energy storage and load shedding wind power,and the total power of energy storage and load shedding wind power was obtained through the model prediction control method;the lower level control took the minimum change rate of energy storage power and the maximum output capacity as the objective function,and allocates energy storage and load shedding wind power output through the model prediction control method.Finally,a simulation research was conducted in a certain wind farm.The results indicate that the proposed control strategy effectively improves the energy storage life and output capacity.
作者 钟诚 田得池 初文昊 陈继开 吴星昭 Zhong Cheng;Tian Dechi;Chu Wenhao;Chen Jikai;Wu Xinzhao(School of Electrical Engineering,Northeast Electric Power University,Jilin Jilin 132012,China;State Grid Tangshan Power Supply Company,Tangshan Hebei 063000,China)
出处 《电气自动化》 2024年第2期76-79,共4页 Electrical Automation
基金 国家自然科学基金(52077030) 吉林省自然科学基金(20190201289JC)。
关键词 风储系统 减载控制 模型预测控制 风电功率波动 功率平抑 wind storage system load shedding control model prediction control wind power fluctuation power suppression
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