Meta-heuristic matrix moth–flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability - Jafar-Nowdeh, Ali; Babanezhad, Manoochehr; Arabi-Nowdeh, Saber; Naderipour, Amirreza; Kamyab, Hesam; Abdul-Malek, Zulkurnain; Ramachandaramurthy, Vigna K. (Environmental technology & innovation, 2020)
This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. Minimizing the power loss, improving the voltage profile and stability of the system, as well as, enhancing the reliability are the main objective functions of the problem to address. The reliability index is assumed as the energy not-supplied (ENS) of the end-users. Optimized variables of the problem include opened lines of the system in the reconfiguration process to maintain the radial structure of the network along with finding the optimal place and size of photovoltaic (PV) systems and wind turbine (WT) units in the distribution system, which are determined based on a new meta-heuristic called moth–flame optimization (MFO) algorithm. Simulations for different scenarios are performed utilizing reconfiguration and placement of renewable sources on an IEEE 33-bus radial distribution system. Obtained results in solving the problem indicate the superiority of the presented method compared with some methods in the literature. Furthermore, the results showed that the combined method as the reconfiguration and WT placement simultaneously bring the best performance for the network with lower power loss, improved voltage profile and stability, and enhanced reliability. Moreover, the results showed that considering reliability helps significantly reduce the energy not-supplied of the customers and supply their maximum load demand. •Optimal multi-criteria reconfiguration of the radial distribution system.•Energy loss minimization, stability improvement and reliability enhancement.•Different scenarios are performed utilizing reconfiguration and placement of renewable sources.