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Nowadays, there is a global consensus that integrating renewable energy sources (RESs) is highly needed to meet the increasing electricity demand and reduce the overall carbon footprint of energy production. However, large-scale integration of RES-based distributed generation (DG) units often poses several technical challenges in the system from stability, reliability, and power quality perspectives. However, these problems are usually mitigated by the optimal integration of DG units in the distribution networks (DNs). In this regard, the optimal sizing and placement of the DGs are crucial. Otherwise, network performance will deteriorate. This paper proposes to apply a novel population-based technique called the dung beetle optimization (DBO) algorithm for the optimal allocation of Photovoltaic (PV) based DG units to minimize total active energy loss subject to equality and inequality constraints in the DN. A DBO is inspired by the behaviours of dung beetles, including ball-rolling, dancing, foraging, stealing, and reproducing. A standard 33-bus system has been used to demonstrate the proposed method's effectiveness. The simulation results and comparison with other techniques demonstrate our proposed approach's significant energy loss reduction and a suitable voltage profile.

This paper presents an application of the recent metaheuristic Geometric Mean Optimizer (GMO) for the allocation of renewable energy sources (RES), including wind turbine (WT) and biomass-based Distributed Generation (DG) units in the distribution network (DN). The primary objective function is to minimize the total power and energy losses. The Weibull probability distribution function (PDF) is employed to describe the uncertainty of wind speed. The high penetration of RES with intermittent availability and demand variations has introduced many challenges to DN, such as power fluctuations, voltage rise, high losses, and low voltage stability. Therefore, the use of dispatchable biomass is considered to smooth out supply fluctuations and maintain supply continuity. A standard IEEE 69-bus test system is used to verify the performance of the proposed approach. The simulation results and comparison with other techniques demonstrate the significant energy loss reduction achieved by the proposed technique.