Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties

Distributed energy resource (DER) systems have elicited increasing attention and applications because of their excellent economic and environmental performance. However, uncertainties exist in such systems, preventing their potential advantages to be realized. In this study, an interval optimization-based model for the optimal design of DER systems is proposed, considering uncertainties in energy prices, renewable energy intensity, and load demands. Uncertainties are described as interval numbers, and the uncertain optimization model is transformed into a deterministic optimization problem using the order relationship and probability degree of interval numbers. The proposed model is applied to a typical hospital in Lianyungang, China, and its effectiveness is verified. One deterministic case and three uncertain cases are designed. The effects of uncertainties on system configuration and economic performance are also analyzed, and the optimal operation strategy under the three uncertainties is determined. A sensitivity analysis is conducted to analyze the effects of probability degree and weighting coefficient on total annual cost. Results show that uncertainties exert a cumulative effect on system optimization outcomes, and the proposed interval optimization model can obtain robust solutions to uncertainties.