Real-time power balancing in photovoltaic-integrated smart micro-grid

The conceptual framework of future power grid incorporates self-automated power flow components. It incorporates high penetration of intermittent renewable energy and variable users' load demands. To establish an efficient real-time power flow mechanism, a realization of the exact amount of energy generation and consumption is inevitable. Hence, we propose a novel framework of a smart micro-grid (SMG), that keeps balance among generation and consumption. It empowers day-ahead supply and demand prediction mechanism along with real-time intelligent energy management (IEM) system. Practically, day-ahead predictions are attained with certain level of errors. These errors are due to the difference in predicted and measured data, also known as uncertainties. Lyapunov optimization under various IEM strategies using flexible loads and battery storage is considered to exploit these uncertainties. The proposed scheme comprises of subsequent steps: 1) the day-ahead predicting solar power and user load demands; 2) the day-ahead procurement of grid power to balance the overall load demands; 3) differentiating real-time uncertainties into user's unused excess power and unserved load demands; 4) real-time balancing of supply and demands by scheduling flexible loads and battery storage, considering the cost effective SMG operations. Our IEM system effectively demonstrates the results of the proposed framework by balancing the user demand arrivals with various energy supplies.