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Optimal Battery Utilization Based on Weather Forecasting Data Leading to DSI

Prosumer microgrids are playing a significant role in the electrical grid system. In the recent decade the injection of renewable energy sources is rapidly increasing. Whereas the output power of photovoltaic sources can be influenced by the unpredictable behaviour of weather factors like solar irradiance and ambient temperature. Under such bad weather conditions, the prosumer fulfils their energy gap from the grid system, which causes an extra compulsion to the utility, concerning the grid instability. Also, by using the energy of peak period, consumers have to bear an additional cost. The underlying study identifies the mitigation method and proposed a Smart Battery scheduling system based on weather forecasting data for achieving an affordable and reliable energy supply. The battery scheduling system collects weather information from the weather station through HTTP protocol using thingspeak server. The information gathered can be used to schedule battery charges and establish a demand response scheme. The obtained test result illustrates that the suggested system's forecasting mechanism may significantly reduce grid dependence.