Multi-objective optimal scheduling of a microgrid with uncertainties of renewable power generation considering user satisfaction

The Microgrid (MG) system combines different types of distributed generation units. It realizes the complementary of multiple energy sources, thereby improving energy efficiency, and power supply reliability. However, it brings significant challenges to the stable operation of MG due to the randomness and uncertainty of renewable energy power generation. By modeling the uncertainty of renewable power generation with probabilistic constraints, a practical multi-objective optimal scheduling model of grid-connected MGs is proposed for minimizing the operating costs and improving the user experience based on chance-constrained programming (CCP). Besides, the sample average approximation (SAA) is applied to transform the model into a multi-objective mixedinteger linear programming (MILP) formulation. Then, the membership function is employed to obtain the optimal weights of the multi-objective problem. Furthermore, from the perspective of demand-side management, a user satisfaction indicator is introduced to evaluate the user experience when the economy and reliability of the MG system are guaranteed. The simulation results of a real world MG demonstrates the effectiveness of the proposed method.