Multiobjective Robust Scheduling for Smart Distribution Grids: Considering Renewable Energy and Demand Response Uncertainty

Abstract

The fluctuating nature of renewable energy is a key factor that limits large-scale integration with the power grid. In this paper, a new method of utilizing multitype demand response (DR) resources to smooth fluctuations in renewable energy on different timescales is proposed. A multiobjective robust scheduling model considering renewable energy and DR uncertainties is established using this method. First, the robust optimization theory is introduced, and uncertainties in renewable energy and multitype DR resources are described in the form of robust intervals on multiple timescales. Then, the multiobjective scheduling model is constructed with the objective of obtaining the lowest operating cost and the highest renewable energy utilization rate, while considering renewable energy integration constraints, DR output constraints, and system power balance constraints. Finally, according to the model characteristics, the uncertainty problem is transformed into a deterministic problem by using a robust counterpart transformation, and a nondominated set genetic algorithm-II is used to solve the deterministic problem. A case study is presented to verify the effectiveness of the proposed scheduling model and solution method. The calculation results show that multitype DR resources can effectively smooth fluctuations in renewable energy, and the proposed robust scheduling method can increase the robustness of the scheduling plan.