Multi-Objective Optimization for Peak Shaving with Demand Response under Renewable Generation Uncertainty

With high penetration of renewable energy sources (RESs), advanced microgrid distribution networks are considered to be promising for covering uncertainties from the generation side with demand response (DR). This paper analyzes effectiveness multi-objective optimization in optimal resource scheduling consumer fairness under uncertainty. The concept is provide conditions power gaps and time gaps. At same time, it used mitigate system peak prevent creating new peaks solution. Multi-objective gray wolf (MOGWO) applied solve complexity three objective functions. Moreover, best compromise solution (BCS) approach determine Pareto-optimal front. simulation results show uncertainty on aggregate load profile operation cost minimization. also performance proposed a DR program reducing effect preventing due over-demand response. meant adjust peak-to-average ratio (PAR) costs without compromising end-user’s comfort.