考虑多目标优化模型的风电场储能容量配置方案
摘要：提出一种风电场配置锂离子电池和超级电容混合储能系统的新方法，利用小波包分频技术对原始风功率进行分解，得到混合储能系统补偿功率。以混合储能配置方案为优化变量，引入改进后的全寿命周期成本，建立了净收益-波动性-弃风量的多目标储能系统配置模型。采用改进概率变异粒子群优化(probabilistic mutation particle swarm optimization，PMPSO)算法对该模型进行求解，得到Pareto解集，对解集进行归一化处理，得出熵权最优配置方案，并与单目标最优方案进行对比，验证了熵权最优配置方案对经济性和功能性的兼容性。通过与自适应量子粒子群优化算法(adaptive quantum particle swarm optimization，AQPSO)进行对比，验证了改进PMPSO算法得到的熵权最优配置方案在保证弃风量和波动性较小的同时，配置更小容量的储能以获得更大的收益，满足多目标配置需求。
Abstract:A new scheme of lithium ion battery and super capacitor hybrid energy storage system in wind farm was proposed. The original wind power was decomposed by the wavelet packet frequency division technology to obtain the compensation power of the hybrid energy storage system. Taking the hybrid energy storage configuration scheme as the optimization variable, the improved life cycle cost was introduced, and a multi-objective energy storage system configuration model of net income volatility waste air volume was established. The model was solved by the improved probabilistic mutation particle swarm optimization (PMPSO) to obtain the Pareto solution set. The solution set was normalized to obtain the optimal allocation scheme of entropy weight. Compared with the single objective optimal scheme, it shows that the optimal allocation scheme of entropy weight takes into account both economy and function. Compared with the adaptive quantum particle swarm optimization (AQPSO), it is verified that the optimal allocation scheme of entropy weight obtained by improved PMPSO algorithm not only ensures the small waste air volume and volatility, but also configures the energy storage with smaller capacity to obtain greater benefits and meet the multi-objective allocation requirements.
标题：考虑多目标优化模型的风电场储能容量配置方案
title:Energy Storage Capacity Allocation Scheme of Wind Farm Considering Multi-Objective Optimization Model
作者：陈晓光, 杨秀媛, 王镇林, 王浩扬
authors:Xiaoguang CHEN, Xiuyuan YANG, Zhenlin WANG, Haoyang WANG
关键词：储能,风电场,多目标求解,优化配置,锂离子电池,超级电容,
keywords:energy storage,wind farm,multi-objective solution,optimal allocation,lithium ion battery,super capacitor,
发表日期：2022-10-31
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