Multi-objective optimization of solar resource allocation in radial distribution systems using a refined slime mold algorithm.

The integration of distributed generation resources in power systems offers various advantages, such as peak load management and reduced transmission line congestion. However, it also introduces challenges related to voltage stability. This paper presents a novel multi-objective model for optimizing the allocation of solar resources in radial distribution systems. The model aims to achieve an optimal voltage profile, minimize losses, and maximize penetration levels. To address the conflicting nature of these objectives, a refined multi-objective slime mold algorithm (MOSMA) is proposed. This algorithm demonstrates exceptional capabilities in finding Pareto fronts, avoiding local optima, and effectively solving multi-objective problems compared to other optimization methods. Additionally, the corrected social hierarchy method is integrated to enhance performance. The proposed method is evaluated using a standard system under various operational conditions, showing superior results in terms of maintaining an acceptable voltage profile and significantly reducing losses. The study reveals that while losses decrease for penetration levels ranging from low to medium, they start to increase for levels exceeding 100 %. Notably, the proposed method achieves approximately 12 % system efficiency improvement, as measured by the voltage profile, at a penetration level of 300 %. These findings highlight the effectiveness of the proposed method, even at high penetration levels, surpassing other optimization approaches based on the inverse generation distance parameter.