A new improved algorithm for optimal sizing of battery-supercapacitor based hybrid energy storage systems

S. Mandal, K. Mandal, M. De, G. Das
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引用次数: 2

Abstract

One of the major challenges in harvesting energy from renewable energy sources is the intermittent nature of available energy sources like solar, wind etc. Thus, it is has become essential to deploy suitable energy storage devices to compensate for the intermittent and random output power generation from various resources. A hybrid energy storage systems (HESS) consisting of battery and supercapacitor is suitable to overcome the difficulties in battery storage system which is normally used. Differential evolution (DE) is one of the powerful evolutionary optimization and has been successfully applied to solve various optimization problems. But one of major difficulties in DE is the selection of control parameters. A wrong parameter selection may lead to premature convergence and even stagnation. In the this work, a new improved algorithm using differential evolution and chaos theory is proposed for optimal sizing of hybrid energy storage system consisting of battery and super capacitor with an aim to avoid premature convergence. A hybrid system consisting of solar and wind is considered for the present work. A suitable objective function is developed which is optimized under several equality and inequality constraints. Simulation results are presented. A comparison of the results with other heuristic techniques is also presented and it shows that proposed techniques can produce good quality solutions.
基于电池-超级电容器的混合储能系统优化尺寸的改进算法
从可再生能源中获取能源的主要挑战之一是现有能源(如太阳能、风能等)的间歇性。因此,部署合适的储能设备来补偿各种资源的间歇性和随机输出发电变得至关重要。一种由电池和超级电容器组成的混合储能系统(HESS)适合克服常规电池储能系统的困难。差分进化是一种功能强大的进化优化方法,已成功地应用于求解各种优化问题。但是,控制参数的选择是遗传算法的主要难点之一。错误的参数选择可能导致过早收敛甚至停滞。本文提出了一种基于差分进化和混沌理论的电池与超级电容器混合储能系统尺寸优化算法,以避免系统过早收敛。本文考虑了一种由太阳能和风能组成的混合系统。提出了一个合适的目标函数,并在若干等式和不等式约束下进行了优化。给出了仿真结果。将结果与其他启发式技术进行了比较,结果表明所提出的技术可以产生高质量的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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