OICC Press Majlesi Journal of Electrical Engineering 2345-3796 18 3 2024 09 30 Jellyfish search optimizer algorithm based multipledistributed generation placements 1 13 10.57647/j.mjee.2024.180347 EN Sundar Ramesh Department of EEE, Muthayammal Engineering College, Namakkal, Tamilnadu, India https://orcid.org/0000-0002-6611-4145 Vijayakumar Govindaraj Department of EEE, Sanjivani College of Engineering, Kopargaon, Maharashtra, India https://orcid.org/0000-0003-1412-9879 Soumya Santhosh Department of Artificial Intelligence and Machine Learning, Acharya Institute of Technology, Bangalore, Karnataka, India https://orcid.org/0009-0001-8261-8343 Ilakkia Tholkappian Department of EEE, Sona College of Technology, Salem, Tamilnadu, India https://orcid.org/0000-0001-5486-3176 Sachin Sumathi Rajaram Department of Mechanical Engineering, Sanjivani College of Engineering, Kopargaon, Maharashtra, India Rajakumar Palanisamy Department of EEE, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, Tamilnadu, India https://orcid.org/0000-0003-1405-7318 Journal Article 2024 09 30 The efficient and economical operation of a distribution power network (DPN) has been essential in recent times, considering the energy crisis and shortage of fossil fuels. A DPN is known to be efficient and economical if power losses are minimal, the voltage drop along the lines is less, and stability is maintained during different operating conditions. However, due to the crisis for primaryfuel, all DPNs including radial power distribution networks (RPDN) are operated at threshold level. This has led to higher power losses, more voltage drops, and stability issues in RDPN. Hence, to reduce the power losses and voltage deviation and improve the stability of the power system network, distributed generation (DG) units are optimally allocated into radial DPN. In this study, an optimization technique using Jellyfish search optimizer (JSO) algorithm is proposed to optimize multiple DGs into RDPN to minimize a multi-objective function corresponds to real power loss (RPL) minimization, voltage stability (VS) enhancement, and total operating cost (TOC) minimization. The performance of the proposed technique is evaluated for multiple type I and type III DGs placement on an IEEE standard 33-bus RDPN. Besides, the effectiveness of the proposed technique is investigated considering a nominal and peak power demand. The efficacy of the research outcome of the suggested JSO approach has been compared with the outcome of other optimization algorithms presented in the literature. The comparison exemplifies that JSO gives more promising outcomes than other algorithms by delivering the least real power losses and better voltage profile enhancement at minimum operating cost.