Load management for voltage control study using parallel immunized-computational intelligence technique

• Published in: Bulletin of Electrical Engineering and Informatics
• Main Author: Bakar A.I.A.; Zamani M.K.M.; Musirin I.; Ghani N.A.M.
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2018
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049887947&doi=10.11591%2feei.v7i2.1172&partnerID=40&md5=19ec405ff822abebea434d6268a846f9

The increase of power demand is a crucial issue in the power system community in many parts of the world. Malaysia has also witnessed the familiar scenario due to the current development throughout the country has invited the urgency of increase in the power supply. Since Malaysia practices vertical system; where the electricity is supplied by only one utility, load management is an important issue so that the delivery of electricity is implemented without discrimination. Parallel Computational Intelligence will be developed which can alleviate and avoid all the unsolved issues, highlighting the weakness of current schemes. Parallel Computational Intelligence is developed to manage the optimal load in making sure the system maintains the stability condition, within the voltage limits. This paper presents evolutionary programming (EP) technique for optimizing the voltage profile. In this study, 3 algorithms which are Gaussian, Cauchy and Parallel EP were developed to solve optimal load management problem on IEEE 26-bus Reliability Test System (RTS). Results obtained from the study revealed that the application of Parallel EP has significantly reduced the time for the optimization process to complete. © 2018 Institute of Advanced Engineering and Science. All rights reserved.