Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system

• Published in: International Journal of Simulation: Systems, Science and Technology
• Main Author: 2-s2.0-85017215654
• Format: Article
• Language: English
• Published: UK Simulation Society 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017215654&doi=10.5013%2fIJSSST.a.17.41.18&partnerID=40&md5=b648a46a892db1c4189585771a1ad147

This paper presents a comparative analysis of Bacterial Foraging Optimization Algorithm (BFOA) and Evolutionary Programming (EP) in determining the locations and amount of load to be shed in power systems for optimal load shedding. Load shedding is done by removing a certain amount of loads at appointed locations of a bus system. By doing so, the stability of the system can be improved, as well as the total power losses. The objective functions of total power losses and voltage stability index values are used in determining the optimal load shedding in that particular system. In this research, the technique is implemented into IEEE 30-bus bus system. Simulations of BFAO proved that a better result can be obtained than EP when compared to the base case values of total power losses and voltage stability index values of that particular bus system. Results obtained from BFOA are also compared with Evolutionary Programing to determine the performance. © 2017, UK Simulation Society. All rights reserved.