Two-stage Combinatory Planning Method for Efficient Wind Power Integration in Smart Distribution Systems Considering Uncertainties

Abstract

—A crucial factor that may hinder the usage of renewable energies is the mismatch to load demand in the temporal dimension. In the smart-grid environment, demand response is regarded as a feasible solution to mitigate such a problem. In this study, a combinatory planning method is proposed for efficient integration of wind generation. The problem is formulated as a two-stage fuzzy chance-constrained programming model, which co-optimizes the installation of distributed wind generation along with network transformation and determination of optimal real-time prices to achieve the minimization of the total cost over planning horizons. The impact of both aleatory and epistemic uncertainties associated with wind generation, load growth, and responsive behaviors of customers has been considered. Results of the case study demonstrate the effectiveness of the proposed method and the necessity of considering different uncertainties in the planning.