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Optimal design and performance evaluation of a grid independent hybrid micro hydro-solar-wind-fuel cell energy system using meta-heuristic techniques

机译:基于元启发式技术的非网格混合型微水太阳能-风燃料电池能量系统的优化设计与性能评估

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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.
机译:本文介绍了由电网,太阳能,风能和燃料电池组成的,与电网无关的混合能源系统的设计和最佳尺寸,可满足特定负载的需求。使用称为Bees算法(BA)的相对较新的优化技术来获得最佳大小,并将该算法的性能与已建立的称为粒子群优化(PSO)的元启发式技术进行比较,并根据系统成本。为了获得最佳的规模,已经考虑了系统的净现价(NPC)。该系统的设计方式可以最大程度地利用资源和无碳电力。牢记这一方面,除了可再生资源外,还引入了电解器以利用多余的电能生产氢气。观察到该系统在满足负载和能源成本方面是非常可行的,并且还观察到尽管这两种算法都能够给出全局解,但是粒子群优化可快速达到最优解,并且占用更少的CPU时间与Bees算法相比。

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