A novel algorithm based on the combination of AC-OPF and GA for the optimal sizing and location of DERs into distribution networks

Abstract

This article proposes an algorithm to obtain an optimal local solution for the network planning process related to the optimal integration of different renewable energy sources (RES) and different Battery Energy Storage Systems (BESS) into a distribution network (DN). The algorithm provides strategic information related to investment and operation costs regarding the type of technology, location, and sizing. The mathematical formulation is based on an AC optimal power flow (OPF) to ensure the network’s minimal stability conditions. Besides, through the use of linearization and a modified version of a genetic algorithm (GA), the algorithm proposed breaks the 24 h wall, used until now in the literature, and extend it to 8760 h, which represents a much more realistic scenario to define the storage and power generation capacity of a DN in a planning context. The algorithm has been tested in a modified version of the IEEE 33-bus considering two cases of study: an off-grid case and grid-connected case, to measure the CapEx and OpEx variability, achieving to show that a grid-connected system reduces the installed capacity of DG and BESS in 37.4% and the CapEx 22.8%. • A novel algorithm is presented for the optimal simultaneous integration of DG and BESS into DN in terms of capacity and location. • A feasible solution for 8760 h as a time horizon, which breaks the 24-hours wall of related literature. • A much more realistic sizing for DG and BESS for distribution network planning is obtained. • The impact of an Off-grid and Grid-connected system on the planning process in terms of CapEx/OpEx.