Document Type : Reseach Article

Authors

• Sundar Ramesh ¹
• Vijayakumar Govindaraj ²
• Soumya Santhosh ³
• Ilakkia Tholkappian ⁴
• Sachin Sumathi Rajaram ⁵
• Rajakumar Palanisamy ⁶

¹ Department of EEE, Muthayammal Engineering College, Namakkal, Tamilnadu, India

² Department of EEE, Sanjivani College of Engineering, Kopargaon, Maharashtra, India

³ Department of Artificial Intelligence and Machine Learning, Acharya Institute of Technology, Bangalore, Karnataka, India

⁴ Department of EEE, Sona College of Technology, Salem, Tamilnadu, India

⁵ Department of Mechanical Engineering, Sanjivani College of Engineering, Kopargaon, Maharashtra, India

⁶ Assistant Professor, Dept. of EEE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology.

Abstract

Efficient and economic operation of distribution power network (DPN) is essential in recent times considering the energy crisis and shortage of fossil fuel. 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 primary fuel, 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 promising outcomes than other algorithms by delivering the least real power losses and better voltage profile enhancement at minimum operating cost.

Keywords

• Radial distribution power network
• distributed generation
• power losses
• voltage stability
• total operating cost