Turkish Journal of Electrical Engineering and Computer Sciences
A novel covid-19 herd immunity-based optimizer for optimal accommodation of solar PV with battery energy storage systems including variation in load and generation
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.
Battery energy storage system, coronavirus herd immunity optimizer, optimization, power loss, solar photovoltaic, voltage profile
PEMMADA, SUMANTH; PATNE, NITA; KUMAR, DIVYESH; and MANCHALWAR, ASHWINI
"A novel covid-19 herd immunity-based optimizer for optimal accommodation of solar PV with battery energy storage systems including variation in load and generation,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 31:
2, Article 7.
Available at: https://journals.tubitak.gov.tr/elektrik/vol31/iss2/7
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons