Optimal Allocation of Generation and Reconfiguration of the Distribution Network for Reliability Enhancement using the Mayfly Optimization Algorithm

Integrating Distributed Generators (DGs) towards Radial Distribution Networks (RDNs) is currently gaining prominence in power system engineering. This paper describes a recently developed nature-inspired meta-heuristic Mayfly Optimization Algorithm (MOA) for determining the Renewable Energy (RE) based Distribution Generation (DG) integration in Radial Distribution Network (RDN) considering islanding mode and reconfiguration simultaneously. This algorithm provides improved capabilities in choosing the appropriate combination, category, and capacity of renewable energy resources to address the competing needs of the distribution systems. This study claims two major novelties in comparison to the literature. The first is an MOA application that identifies the optimal distribution of Photovoltaic (PV) and Wind Turbine (WT) generation units in RDN when grid-connected mode is used. The second one is the optimum allocation of PV and WT units for supply-demand balance even when islanding occurs, considering reconfiguration options, voltage profile improvement, distribution loss reduction, and optimization of reliability indices. The proposed MOA is able to offer enhanced results in terms of reduction in power losses ~ 57%, Minimum voltage~ 0.96 p.u., and Power index of reliability ~65% when applied with IEEE 33 bus and IEEE 69 bus test systems with various scenarios.