Robust Optimal Operation of AC/DC Hybrid Microgrids Under Market Price Uncertainties

Abstract

Energy management system (EMS) is responsible for the optimal operation of microgrids. EMS adjusts its operational schedule for near future by using the available information. Market price signals are generally used for the operation of microgrids, which are obtained by using estimation/ forecasting methods. However, it is difficult to precisely predict the market prices due to the involvement of various complex factors like weather, policy, demand, errors in forecasting methods, and fuel cost. Therefore, in this paper, the uncertainties associated with the real-time market price signals (buying and selling) are realized via a robust optimization method. In addition to market price signals, uncertainties associated with renewable power sources and forecasted load values are also considered. Initially, a deterministic model is formulated for an ac/dc hybrid microgrid. Then a min–max robust counterpart is formulated by considering the worst-case uncertainties. Finally, an equivalent mixed integer problem is formulated by using linear duality and other optimality conditions. The developed model can provide feasible solutions for all the scenarios if the uncertainties fluctuate within the specified bounds. The effect of market price uncertainties on internal power transfer and external power trading, operation cost, the state-of-charge of energy storage elements, and unit commitment of dispatchable generators is analyzed. Taguchi’s orthogonal array (OA) method is used to find the worst-case scenario within the specified uncertainty bounds. Then, Monte Carlo method is used to generate various scenarios within the uncertainty bounds to evaluate the robustness of the selected scenario via Taguchi’s OA method. Finally, a violation index is formulated to evaluate the robustness of the proposed approach against the deterministic model. Simulations results have validated the robustness of the proposed optimization strategy.