HunterPrey Optimization Algorithm for Optimal Allocation of PV, DSTATCOM, and EVCS in Radial Distribution Systems
intelligent algorithm; optimal allocation; radial distribution systems; voltage stability
This research article instigates a seminal approach for optimizing reactive power in renewable energy sources (RES) and electric vehicles (EVs) coalescing distribution systems, using the innovative HunterPrey Optimization (HPO) algorithm in conjunction with DSTATCOM as a reactive power compensator. The proposed methodology aims to minimize losses, enhance voltage stability, and improve overall system performance by simultaneously optimizing reactive power flows in photovoltaic RES (PV_DG), EV charging stations (EVCS), and DSTATCOMs within the distribution system. Simulations carried on IEEE-33, IEEE-69, and IEEE-118 test bus systems in MATLAB environment demonstrate that the HPO-based approach achieves a 91.47% and 96.61% reduction in real power losses and an improvement in voltage profile with a minimum voltage value of 0.991 and 0.994 p.u. (respectively for IEEE-33 and 69 bus systems), compared to traditional algorithms. These results highlight the lofty performance of the HPO method, effectively addressing the challenges posed by the integration of RES and EVs along with DSTATCOM. 2024 John Wiley & Sons Ltd.
Advanced Control for Applications: Engineering and Industrial Systems, Vol-6, No. 4
https://doi.org/10.1002/adc2.231 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206210803&doi=10.1002%2fadc2.231&partnerID=40&md5=9e65f59124d79bd01b44887e69545f37
Pappu S.L., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Bangalore, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Bangalore, India; Veerendra A.S., Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India