基于遗传算法的光伏-风力电池储能微电网系统优化

T. Adefarati, S. Potgieter, R. Bansal, R. Naidoo, R. Rizzo, P. Sanjeevikumar
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引用次数: 9

摘要

电力需求的突然增加使可再生能源技术的利用在减少全球无法获得电力供应的人数方面处于至关重要的地位。可持续能源系统是一种具有成本效益的技术,可以满足基于不同应用和多个retts组件组合的负载需求。鉴于此,本文研究了由柴油发电机组、光伏发电机组、WTG和ESS组成的离网电力系统的优化问题。这项研究工作允许微电网系统各组成部分之间的负荷分担作为利用RETs经济效益的标准。本文介绍了遗传算法在微电网系统总成本最小化中的应用。在MATLAB环境下实现了该优化方法,仿真结果表明,该方法可获得最小的总成本。遗传算法具有实现简单、计算时间短等优点。该算法可以帮助配电网运营商降低与微电网系统运行相关的总成本。
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Optimization of PV-Wind-Battery Storage Microgrid System Utilizing a Genetic Algorithm
The sudden increase in power demand has put the utilization of renewable energy technologies (RETs) in a crucial position to reduce the number of people that have no access to the electrical power supply on the global note. The sustainable energy system is the cost effective technology to meet the load demand based on different applications and combinations of several components of RETs. In view of this, the optimization of an off-grid power system that comprises of the diesel generator, PV, WTG and ESS is investigated. This research work permits the load sharing among the components of a microgrid system as a criterion to harness the economic benefits of RETs. This paper presents the application of the GA to minimize the total cost of the proposed microgrid system. This optimization method is implemented in MATLAB environment and the simulation results indicate that minimum total cost is obtained from the technique. The GA is much simpler to implement and uses less computational time to solve the problem of the power system. The proposed algorithm can assist the distribution network operators to reduce the total cost that is related to the operation of a microgrid system.
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