Energy advancement integrated predictive optimization of photovoltaic assisted battery energy storage system for cost optimization

In this paper we present forecast-based predictive optimization for grid tied photovoltaic integrated battery energy storage system to minimize consumption from the grid. Forecasts of load demand and photovoltaic with tariff structure and battery energy storage system status are used as decision variables. Forecast-based predictive optimization with battery energy storage system control (energy usage advancement) increases photovoltaic proportion, decreases consumption from the grid during high price periods and reduces cost based on the present and futuristic load demand and photovoltaic potential. The proposed scheme allows consumers to manage their energy consumption, and thus cost, in response to energy price variation (time-of-use tariff) throughout the day by optimizing energy usage in high price periods. The proposed scheme is simple, effective, realistic, and accounts for errors in the forecasts. Results show noticeable savings in energy cost for a consumer and increased usage of otherwise wasted photovoltaic energy.