Distributed Generation Planning and Optimization: Deterministic versus Heuristic Approaches

Abstract

This paper presents the distributed generation (DG) planning problem of finding the optimal locations, sizing, and optimal placement (locations and sizing) for single and multiple DG units, with the objective functions of minimizing total active power losses and maximizing total DG penetration in the network. The planning problem is firstly formulated as a mixed integer nonlinear programming (MINLP) problem using optimal power flow (OPF)-based technique, and then implemented and solved considering: 1) a deterministic/exact approach, and 2) a heuristic optimization approach based on the Genetic Algorithm (GA). The methods are tested in two benchmark models; the 25-kV IEEE 6-bus and the 33kV 16-bus UKGDS, where several case studies are analyzed. The results and analyses provide insights about models' validation, problem complexity, computation time, feasible solutions, and planning criteria. Overall, the paper provides a good reference for scholars and researchers to learn about the basics/tools of DG planning studies (e.g., deterministic and heuristic methods, different planning problems, formulations and constraints, optimization software, etc.).