A Novel Hybrid Algorithm based Planning of Power Distribution System Considering Emission Pollutants

Abstract

This study investigates a new hybrid algorithm, which is a combination of an enhanced elephant herding algorithm (EEHA) and the Jaya algorithm (JA). This hybrid enhanced elephant herding jaya algorithm (EEHJA) controls the searching properly from global exploration to local exploitation to obtain a near-global optimum. The suggested algorithm is employed to optimise the reconfiguration and integration of renewable distributed generations (DGs) taking the novel type of buses P, PQV. The voltage at the PQV bus is regulated by the P bus with a reactive power assist (RPA). Sensitivity factors based on curtailment in active power loss (APL) and enhancement in bus voltages are proposed to obtain optimal DG locations. During reconfiguring network topology (RNT), a smart graph theory technique based on the spanning tree concept authenticates the topological restrictions. The proposed algorithm is applied to optimise the RPA at the P bus, solar photovoltaic DGs ratings, and optimal RNT of the power distribution system (PDS) to minimise the APL. The placement of solar photovoltaic DGs has been studied in two approaches namely, sequential and non-sequential allotment. Further, different cases are studied based on optimum RNT including and excluding DGs, and RPA by the suggested methodology on 33 and 69 bus radial PDS. Moreover, the pollutant emissions like CO2, SO2, and NOX in the environment due to traditional energy sources are further reduced. The adequacy of this novel methodology is verified with recently developed meta-heuristic algorithms and the obtained numerical results demonstrate the validity and its effectiveness.