Multi-objective Optimal Allocation of Renewable Energy Distributed Generations and Shunt Capacitors in Radial Distribution System using Corona Virus Herd Optimization

This paper proposed the multi-objective optimal allocation of renewable distributed generation and shunt capacitors in the distribution system using corona virus herd optimization techniques. The work aimed to achieve a technical benefit, total electricity cost reduction, and enhancement of greenhouse safety. The objectives considered are real power loss, voltage profile index, voltage stability index, total electricity cost (TEC), and total greenhouse gas emission (TGHGe). Weight function was used to combine the objectives for the six cases considered with different priorities. The proposed CHIO is validated on the standard IEEE ۳۳ bus system and implemented on Dada ۴۶ bus, a Nigerian practical distribution network. Various cases were considered for the two test systems. For IEEE ۳۳ bus, the proposed method achieved ۸۹.۴۴% and ۸۶.۷۷% reduction in real and reactive power, respectively, with ۹۳.۷۳% and ۳۹.۲۷% in TGHGe and TEC. Also, for Dada ۴۶ bus system, ۸۹.۴۴% and ۸۶.۷۷% reduction in real and reactive power loss respectively was achieved with ۹۸.۶۶% and ۶۴.۴۲% in TGHGe and TEC. Furthermore, the highest level of greenhouse gas emission reduction was achieved (says ۹۹.۶۹%) when high priority was placed on the reduction in TGHGe; this shows the significant impact of renewable energy in the distribution system. The results obtained are compared with the existing methods, such as PSO, GA, ABC, GABC, WOA, WCA, to mention a few. In other to show the performance of the proposed CHIO compared to others, the outcome reveals the excellent performance of the proposed algorithm in terms of an optimal result.

Keywords:

Renewable distributed generation , shunt capacitor , Distribution system , Power Loss , Greenhouse gas emission , corona virus herd optimization techniques , voltage profile index