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Design Optimization Analysis Based On Demand Side Management of a Stand-alone Hybrid Power System Using Genetic Algorithm for Remote Rural Electrification

机译:基于远程农村电气化遗传算法的独立混合动力系统需求侧管理的设计优化分析

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The utilization of diesel generators to provide power to the load demand on remote rural areas in Tanzania has extensively spread which results in a shortage of energy facilities. With increments in oil cost and the stresses over an unnatural weather change, the hybridization of the accessible sustainable assets with diesel generator has become a powerful answer for increment framework reliability for supplying the load demand. This work proposes an Adaptive Genetic Algorithm (AGA) based new methodology for the ideal structure of hybrid energy framework involving sunlight based PV, diesel generator, and battery associated frameworks for providing the electrical energy in remote rural areas. The proposed framework utilizes the meteorological information of sun-powered illuminations and temperature gathered from the meteorological site of Tanzania and real-time data from HOMER programming created by the National Renewable Energy Laboratory (NREL). Improvement of the Hybrid Energy System (HES) incorporates minimization of net present cost (NPC), diminished emanations of harmful gases in terms of CO2, NOx, and SOx which makes the system more economical as well as reliable for the residential household applications for remote rural areas. The optimized results were accomplished by utilizing AGA, which utilizes the factors, such as PV cluster ratings in terms of irradiation and temperature data, the number of battery banks, diesel generator appraised power, fuel cost, framework initialization cost, operation, and maintenance cost and emission constraints are considered as the input information chromosomes for the calculation. A reasonable AGA program based demand-side management (DSM) was defined utilizing MATLAB tool kit with the target capacity of limiting the net present expense and emissions of gases which leads to maximization of system reliability of the proposed HES for electrifying the rural areas in independent applications.
机译:利用柴油发电机为坦桑尼亚遥远农村地区的负荷需求提供电力,广泛传播,导致能源设施短缺。在石油成本的增量和不自然的天气变化的压力,可容易可持续资产与柴油发电机的杂交已成为提供负载需求的增量框架可靠性的强大答案。这项工作提出了一种基于自适应遗传算法(AGA)的基于混合能量框架的理想结构的新方法,涉及阳光的PV,柴油发电机和电池相关框架,用于在远程农村地区提供电能。拟议的框架利用来自国家可再生能源实验室(NREL)创建的坦桑尼亚气象遗址和从坦桑尼亚气象遗址收集的太阳动力照射和温度的气象信息。杂交能量系统(HES)的改进包括最小化净目前的成本(NPC),在CO中减少有害气体的散发物 2 ,NOx和SOX,使系统更经济,可靠地为远程农村地区的住宅家庭应用。优化的结果是通过利用AGA来实现的,它在照射和温度数据方面利用PV群集额定值,电池组的数量,柴油发电机被评估的电源,燃料成本,框架初始化成本,操作和维护成本发射约束被认为是计算的输入信息染色体。采用MATLAB工具套件定义了合理的AGA计划的需求 - 侧管理(DSM),其目标能力限制了净目前的净额和气体排放,这导致提升系统的可靠性最大化,以便在独立中通电农村地区应用程序。

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