基于ABC算法的微电网HESS容量分配,International Journal of Low-Carbon Technologies

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基于ABC算法的微电网HESS容量分配
International Journal of Low-Carbon Technologies ( IF 2.4 ) Pub Date : 2020-05-06 , DOI: 10.1093/ijlct/ctaa014
Yu Zhang ₁ , Zhe Yan ₁ , Cui Cui Zhou ₁ , Tie Zhou Wu ₁ , Yue Yang Wang ₁

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混合储能系统（HESS）是平滑微电网中功率波动的关键组件。适当配置微电网储能能力可以有效提高系统经济性。提出了一种基于人工蜂群算法的微电网HESS容量分配新方法。该方法提出了一种基于低通滤波器和模糊控制的功率分配策略。该策略可协调电池和超级电容器的运行并改善电池运行环境。模糊控制将电池和超级电容器的充电状态（SOC）作为输入，将LPF滤波器的时间常数的校正系数作为输出。LPF的滤波时间常数是及时调整的，电池和超级电容器的SOC在有限范围内稳定，从而可以避免电池的过充和过放，并延长了电池的使用寿命。该方法还利用子算法进行超级电容器和电池容量优化。此外，对统计模型进行了蒙特卡洛模拟，以消除诸如风速，光强度和温度等不确定因素的影响。ABC算法用于优化混合储能的容量分配，避免了精度低，容易陷入超级电容器和电池容量分配子算法的局部最优解以及容量最优分配的问题。 HESS的确定。通过使用这种方法，

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Capacity allocation of HESS in micro-grid based on ABC algorithm

The hybrid energy storage system (HESS) is a key component for smoothing fluctuation of power in micro-grids. An appropriate configuration of energy storage capacity for micro-grids can effectively improve the system economy. A new method for HESS capacity allocation in micro-grids based on the artificial bee colony (ABC) algorithm is proposed. The method proposed a power allocation strategy based on low pass filter (LPF) and fuzzy control. The strategy coordinates battery and supercapacitor operation and improves the battery operation environment. The fuzzy control takes the state of charge (SOC) of the battery and supercapacitors as the input and the correction coefficient of the time constant of the LPF filter as the output. The filter time constant of the LPF is timely adjusted, and the SOC of the battery and supercapacitor is stable within the limited range so that the overcharge and over-discharge of the battery can be avoided, and the lifetime of the battery is increased. This method also exploits sub-algorithms for supercapacitors and battery capacity optimization. Besides, the Monte Carlo simulation of the statistic model is implemented to eliminate the influence of uncertain factors such as wind speed, light intensity and temperature. The ABC algorithm is used to optimize the capacity allocation of hybrid energy storage, which avoids the problem of low accuracy and being easy to fall into the local optimal solution of the supercapacitors and battery capacity allocation sub-algorithms, and the optimal allocation of the capacity of the HESS is determined. By using this method, the number of supercapacitors required for the HESS is unchanged, and the number of battery is reduced from 75 to 65, which proves the rationality and economy of the proposed method.

更新日期：2020-05-06

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