Work place: Department of EEE, K.Ramakrishnan College of Technology, Trichy, Tamilnadu, India
E-mail: sabarish.san@gmail.com
Website:
Research Interests:
Biography
Sabarish P. is currently working as Assistant Professor in the Department of Electrical and Electronics Engineering at K.Ramakrishnan College of Technology, Trichy, India. He has totally 9 years of experience in teaching. He holds a Ph.D. degree in Electrical Engineering. His research areas are power system optimization and renewable energy system. He can be contacted at Email: sabarish.san@gmail.com
By Sakthidasan A. Senthil Kumar M. Jovin Deglus Sabarish P. Rajakumar P. Sundar R.
DOI: https://doi.org/10.5815/ijitcs.2025.02.06, Pub. Date: 8 Apr. 2025
The incorporation of distributed generation (DG) in radial distribution systems (RDS) has recently garnered much attention. The prime goal of DG integration is to generate power locally and cut down the total power losses (PL) of RDS to increase the overall efficiency. The present work suggests a hybrid optimization approach integrating loss sensitivity factor (LSF) with a whale optimization algorithm (WOA) to optimize different categories of DG. The LSF locates the ideal site, and WOA optimizes the size. The present study optimizes DG units to minimize the total active power losses (APLT) and enhance the bus voltages (BV). The present work investigates the adaptability of the proposed integrated technique on the small 33-bus and a large 118-bus RDS. The APLT of the 33-bus RDS is minimized from 210.98 kW to 101.3 kW, 124.3 kW, 64.56 kW, and 86.5 kW for Type I, Type II, Type III, and Type IV DG placements, respectively. Correspondingly, the minimum bus voltage (BVmin) is increased from 0.9038 p.u. to 0.9511 p.u., 0.9503 p.u., 0.9608 p.u., and 0.9579 p.u. Likewise, significant PL reduction and bus voltage enhancement are obtained in 118-bus for three units of Type I and Type III DG placements. Further, the adequateness of the hybrid technique is examined for varying power demand on the IEEE 33-bus RDS. The integrated technique effectively narrows the search space of the optimization problem and helps the WOA to find the optimal solution. The simulation outcomes are compared to examine the sovereignty of the proposed optimization technique.
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