Revenue loss reduction in the electrical distribution networks using distributed generators: A case of Tanzania electrical distribution network

Abstract

Most power losses in power systems occur within distribution networks, resulting in poor service quality, higher electricity costs for consumers, and revenue loss for utility companies. This study suggests strategies for minimizing these revenue losses by integrating distributed generators (DGs) into the distribution networks. The process involves identifying optimal locations and determining the best power output for each DG based on fluctuating power system variables, making it a complex NP-hard optimization problem. Therefore, this study proposes the use of metaheuristic algorithms to solve the DG power dispatch problem and reduce revenue losses in the electrical distribution networks. The proposed technique has been tested in the Tanzanian electrical distribution network using an hourly load profile and tariff D1, T1 and T2 users. Four metaheuristic algorithms were used, namely Golden jackal optimization (GJO), Grey wolf optimizer (GWO), Walrus optimizer (WO) and Marine Predators Algorithm (MPA). The algorithms were evaluated based on convergence profiles and computational times, with GWO performing the best. The study analyzed the impact of the number of DGs on revenue loss reduction, finding that the revenue losses decrease with the increase in the number of DGs. The analysis of the impact of the tariffs category on revenue loss reduction shows that integrating DGs reduced revenue loss by over 56% in all cases. These results demonstrate that DG integration can effectively decrease revenue losses in distribution networks.