A Discrete Bat Algorithm Based Optimal Location and Sizing of Power Distribution Substation

Distribution substation planning is considered one of the most important steps in the power system planning process. A planning model seeks to determine a strategy that will minimize losses and total costs associated with configuring and operating an electric power distribution system over a given planning horizon. Metaheuristic methods are usually deployed in solving the distribution planning problem but face complexity and constraint limitation in some cases. Discrete Bat Algorithm (DBA) is a combinatorial technique that is a robust algorithm that will be suitable for solving a distribution substation location and sizing problem. The approached comprises two stages which include: Optimal Distribution Substation Location (ODSL) using a Modified Load Gravity (MLG) based method; and Optimum Sizing of Distribution Substation (OSDS) using DBA. Zaria distribution substation network is used as the case study. The results obtained has been compared with other similar literatures and validated. The results obtained using DBA achieved an expansion cost of $2,634,410.08 representing 59.7% cost reduction. While the particle swarm optimization (PSO) which amounted to $6,541,000.00, represent 40.28% cost reduction. By comparing the results of PSO and DBA, it is clear that both methods have the ability to find proper solutions to substation expansion planning, but DBA is more able than PSO to find an optimal solution to substation expansion planning.