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 multiobjective 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 (VPI), voltage stability index (VSI), 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 33 bus system and implemented on Dada 46 bus, a Nigerian practical distribution network. Various cases were considered for the two test systems. For IEEE 33 bus, the proposed method achieved 89.44% and 86.77% reduction in real and reactive power, respectively, with 93.73% and 39.27% in TGHGe and TEC. Also, for Dada 46 bus system, 89.44% and 86.77% reduction in real and reactive power loss respectively was achieved with 98.66% and 64.42% in TGHGe and TEC. Furthermore, the highest level of greenhouse gas emission reduction was achieved (says 99.69%) 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.