A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems

Abstract

This paper addresses the expansion planning problem of modern distribution systems using a novel solution methodology based on matheuristics. The problem is formulated as a mixed-integer quadratic programming model. The proposed technique constitutes a novel local search algorithm that, using linearized and relaxed versions of the original problem, finds successive solutions, improving at each iteration the feasibility of the original problem until attaining a high-quality near-optimal solution. Planning actions include line reconductoring and installation of distributed generation (DG) units, electrical energy storage (EES) systems, and fixed and switchable capacitor banks (CBs). Operation system variability in demand and energy resources is modeled through representative days in order to preserve EES temporal transition. Furthermore, the model guarantees CO2 reduction in order to be on track to limit global warming. The effective performance of the proposed approach in terms of solution quality and computational time has been illustrated with a case study based on a 33-node distribution system.