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

Abstract

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.