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        Planning and Optimization of Energy Scheduling in Cohesive Renewable Energy Microgridto Meet Electric Load Demand of an Educational Institution

        Bharathi G. Jaya,Padmanabhan T. Suresh 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.6

        Promoting promising and environment-friendly energy systems with smart microgridsis one of the imperativesolutions to realize sustainable development goal 7 (SDG 7) of uninterrupted electricity for all. On this premise, we develop a Cohesive Renewable Energy Microgrid (CREM) that providesa guarantee for universal access to electricity in a sustainable, aff ordable, and reliable way by integrating diff erent energy sources. In this work, we propose a grid-independent microgrid with cohesive solar-wind generating units, a diesel powered electric generator, and a storagebank to meet the power requirements of an educational institution, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India (10° 48.2′ N, 79° 50.1′ E). This work targets to evaluate the performance of diff erent renewable energy sources as analternate for traditional fossil fuel to provide uninterrupted power supply in the college premises. In this work, a software tool called Hybrid Optimization Model for Electric Renewable, is employed to fi nd out the optimal confi gurations of the proposed CREM and to validate the potential of the microgrid by performing techno-economic analysis against the given load demand.The statistics related to thesunradiations and wind velocities of the Nagapattinam district are employed in this study to achieve accurate results.The optimization results provide minimumannual system cost andconsistent power supply related to the actual utility grid.The optimal confi guration of the proposed CREM comprises of 3.3 kW wind turbine, 13 kW solar photovoltaics (PV) panels, and a 15 kW Genset with an annualized cost of $115,451 and energy costof 0.082$/kWh. The proposed CREM produces 71,457 kWh/year of energy to fulfi llthe institutional load demand of 58,043 kWh/year. The results reveal that the annualized cost of a Gensetis the maximum and contributes 64.63% of annualized system cost followed by solar energy system with 12.97%, battery bank with 11.47%, a wind turbine with 6.61%, and converter with 4.31%

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