Reliability-constrained robust expansion planning of active distribution networks

Abstract

Power distribution systems have become more complex in recent years due to the integration of new technologies. Motivated by these challenges, this paper describes a model to solve the multi-period expansion planning problem of active distribution systems, considering uncertainty, reliability, distributed generation, self-healing, reactive power support, switches, and energy storage devices. The objective is to determine the best installation times and locations of new components, minimizing the total cost, and ensuring desired reliability levels. The approach consists of a three-level decomposition. The first level identifies expansion proposals, the second level finds the worst-case scenario using adaptive robust optimization, and the third level performs a Monte Carlo Simulation to compute reliability indexes. The main contributions are the introduction of a novel reliability sensitivity matrix to improve computational performance and the representation of the hours of the day inside the expansion planning formulation. The proposed method is illustrated using the IEEE 123-bus test system. The analyses show high computational efficiency as compared with similar works. The impacts on the number of expansion components placed in the system and on the total cost are presented and discussed using cases varying the uncertainty budget and not considering some of these components.