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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. [ABSTRACT FROM AUTHOR]

The world has now looked towards installing more renewable energy sources type distributed generation (DG), such as solar photovoltaic DG (SPVDG), because of its advantages to the environment and the quality of power supply it produces. However, these sources' optimal placement and size are determined before their accommodation in the power distribution system (PDS). This is to avoid an increase in power loss and deviations in the voltage profile. Furthermore, in this article, solar PV is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG as well as the reduction in peak demand. This paper presented a novel coronavirus herd immunity optimizer algorithm for the optimal accommodation of SPVDG with BESS in the PDS. The proposed algorithm is centered on the herd immunity approach to combat the COVID-19 virus. The problem formulation is focused on the optimal accommodation of SPVDG and BESS to reduce the power loss and enhance the voltage profile of the PDS. Moreover, voltage limits, maximum current limits, and BESS charge-discharge constraints are validated during the optimization. Moreover, the hourly variation of SPVDG generation and load profile with seasonal impact is examined in this study. IEEE 33 and 69 bus PDSs are tested for the development of the presented work. The suggested algorithm showed its effectiveness and accuracy compared to different optimization techniques. [ABSTRACT FROM AUTHOR]