Abstract
This paper describes a comprehensive analysis of a hybrid energy system (HES) when satisfying the load demand of an off-grid, rural and hilly community in Bangladesh. Different combinations of HES, such as PV/Pump-hydro storage (PHS), Diesel/PHS, and PV/Diesel/Battery, are formulated, analysed, and compared using hybrid optimization of multiple energy resources (HOMER) software. The system configurations, together with the size and selection of system components, are suitably modelled and optimised with the least cost of energy (COE), net present cost (NPC), and CO2 emissions. In addition, to illustrate the adaptability and the economic benefits of the studied systems, the scalability of the system is evaluated by changing the load demand and the size of the generator. The study is further extended to include a sensitivity analysis on the uncertain parameters in connection with the climatic data and hardware components. Results indicate that the cost of energy for a pumped HES with a single diesel generator is higher (0.27$/kWh) than that with two small generators (0.24$/kWh. The energy cost for the optimised PV/Diesel/PHS system (0.27$/kWh) is found to be significantly lower than those of both PV/PHS (0.43$/kWh) and Diesel/PHS (0.41$/kWh) options. This research identifies that the PV/Diesel/PHS system is more cost-effective than the PV/Diesel/Battery-based hybrid system, with cost of energy at 0.34$/kWh. Results indicate that the genetic algorithm (GA) method provides cost effective and sustainable solution than the HOMER software tool.
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