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

Abstract

Most power losses in power systems occur in distribution networks, leading to poor service quality, higher electricity costs, and utility revenue losses. This study addresses these challenges by integrating distributed generators (DGs) into distribution networks to minimize revenue losses. The proposed strategy involves determining optimal DG power output at fixed locations, making it a complex NP-hard optimization due to fluctuating system variables. This study involves metaheuristic algorithms to solve the DG power dispatch problem in order to reduce revenue losses. 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, namely Golden jackal optimization (GJO), Grey wolf optimizer (GWO), Walrus optimizer (WO), and Marine Predators Algorithm (MPA) were evaluated. The performance of the algorithms was assessed through convergence profiles and computational times, with GWO emerging as the most effective. The findings reveal that increasing the number of DGs reduces revenue losses, while tariff category analysis shows an average loss reduction of over 56% across all cases. These results highlight the effectiveness of DG integration in minimizing revenue losses and improving the efficiency of electrical distribution networks.