基于经验模态分解和模糊机会约束的混合储能容量配置方法
摘要:为了进行储能容量配置，采用经验模态分解方法，从频域上对储能功率进行划分，并分配给能量型电池和功率型电池，以储能成本最小为约束，以修正系数作为模糊变量，建立模糊机会约束模型，并用于模糊模拟的遗传算法求解。通过仿真算例得出储能电池和超级电容器系统的容量和功率，达到了储能容量配置的要求，采用混合储能系统可以满足平滑风电功率波动的要求，同时充分发挥储能电池和超级电容器的特性，将储能电池和超级电容器的荷电状态控制在合理范围内，保证了储能系统能够稳定运行。
Abstract：Empirical mode decomposition (EMD) method was introduced to make capacity configuration for the hybrid energy storage system (HESS), dividing the energy storage power in frequency domain and assigning to energy density and power density batteries. Capacity allocation model, based on fuzzy chance constrained programming, was built with the minimum annual cost and state of charge(SOC) confidence level as constraints. The fuzzy simulation-based genetic algorithm was used to solve the fuzzy model. The capacity and power of storage battery and super capacitor were obtained by simulation calculation. The hybrid energy storage system can be introduced to smooth the fluctuations of wind power-output and control the load of storage battery and super capacitor, so as to guarantee the stable operation of storage system.
标题：基于经验模态分解和模糊机会约束的混合储能容量配置方法
title:Capacity Allocation Method of Hybrid Energy Storage System Based on Empirical Mode Decomposition and Fuzzy Chance Constrained Programming
作者：曹超, 马玉鑫, 常悦, 关瑞丰
authors:CAO Chao, MA Yuxin, CHANG Yue, GUAN Ruifeng
关键词：新能源,风力发电,混合储能平滑,容量配置,遗传算法,
keywords:new energy,wind power,hybrid energy storage system(HESS) smoothing,capacity allocation,genetic algorithm,
发表日期：2016-12-28
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