Optimal Design of Distributed Energy Resource Systems under Uncertainties Based on Two-Stage Robust Optimization

Abstract

Distributed energy resource (DER) systems are widely used owing to their excellent economic and environmental performance. However, uncertainties in the system generate difficulties in the optimal design of DER systems. In practice, the distribution of uncertain parameters is generally unknown. In this work, a two-stage robust optimization (RO) model was proposed for the optimal design of DER systems considering uncertainties in renewable energy intensity, energy prices, and load demands. Three uncertainty sets (i.e., the box, ellipsoid, and convex-hull uncertainty sets) were adopted to describe the distribution of uncertain parameters, and the proposed two-stage RO problem was solved using affine decision rules. A typical hospital in Lianyungang, Jiangsu Province, China, was selected as the case study object, and the effectiveness of the model was verified. The case study results showed that uncertainties in energy prices and load demands have a significant impact on system configuration and economic performance, and mainly affect the installed capacities of gas boilers, absorption chillers, and storages. Uncertainty set will affect the optimization results and an appropriate uncertainty set should be adopted to describe uncertainties precisely and increase accuracy of results.