基于元启发式技术的微水电-太阳能-风能混合燃料电池能源系统优化设计与性能评价

B. Tudu, K. Mandal, N. Chakraborty
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引用次数: 17

摘要

提出了一种由微水电、太阳能、风能和燃料电池组成的满足特定负荷的不依赖电网的混合能源系统的设计和优化规模。采用一种较新的优化技术——蜜蜂算法(BA)获得了最优规模,并将该算法的性能与一种已建立的元启发式技术——粒子群优化(PSO)进行了比较,并根据系统的成本对系统性能进行了评估。为了获得最优规模,考虑了系统的净当前成本。该系统的设计是为了最大限度地利用资源和实现无碳电力。考虑到这一点,除了可再生资源外,还引入了电解槽,利用多余的电力生产氢气。结果表明,该算法在满足负载和能量消耗方面都是可行的,两种算法都具有全局解的能力,但粒子群算法比蜜蜂算法更快达到最优解,占用CPU时间更少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal design and performance evaluation of a grid independent hybrid micro hydro-solar-wind-fuel cell energy system using meta-heuristic techniques
This paper presents the design and optimal sizing of a grid independent hybrid energy system consisting of micro hydro, solar, wind and fuel cell for catering a specific load. The optimal sizing is obtained using a comparatively new optimization technique called Bees algorithm (BA) and the performance of the algorithm is compared with an established meta-heuristic techniques called particle swarm optimization (PSO) and also the system performance is evaluated in terms of the cost of the system. For obtaining the optimal sizing, net present cost (NPC) of the system has been considered. The system is designed such a way that the maximum utilization of the resources and carbon free electricity can be achieved. Keeping in mind this aspect, apart from renewable resources, electrolyser is introduced for production of hydrogen utilizing the excess power. It is observed that the system is quite feasible in meeting the load and in terms of cost of energy and also observed that though both the algorithms are capable of giving global solution, but Particle swarm optimization is fast in reaching optimal solution and takes less CPU time as compared to Bees algorithm.
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