Ɛ‐constraint multiobjective approach for optimal network reconfiguration and optimal allocation of DGs in radial distribution systems using the butterfly optimizer

In recent days, the optimal allocation of distributed generators (DGs) problem in the distribution system caught several reader's attention to improve the system efficiency, to meet the future load growth. In this article, a multiobjective approach is proposed to determine the optimal locations for DGs, optimal DGs sizes, optimal power factors of DGs in the presence of optimal network reconfiguration to maximize the maximum loadability (λmax), minimize the active power loss and maximize the loading margin factor (λv) of the system. Butterfly Optimization (BO) algorithm is implemented to optimize the desired objectives. The Ɛ‐constraint method is used for multiobjective optimization, spanning tree technique is used for checking the radiality of the system and modified repetitive power flow using radial load flow algorithm is developed for finding theλmax, λv.The proposed approach is tested on 33 bus and 69 bus radial distribution test systems. Four scenarios are considered to achieve the desired objectives and each scenario consists of two cases: optimal allocation of DGs in the initial configured network, optimal allocation of DGs in the optimal reconfigured network. Results suggest that optimal allocation of DGs in scenario 4 gives a better improvement in maximum system loadability, loading margin factor, and active power loss reduction of the system. Obtained results compared with the suitable methods and algorithms that are available in the literature. This article proposes an efficient Ɛ‐constraint multiobjective approach for the optimal placement of DGs in optimally reconfigured radial distribution network with an aim to minimize system active power losses, maximizing maximize the maximum loadability (λmax), and maximize the loading margin factor (λv). And the proposed approach was succeeded in attaining the desired objectives.