Implementation of HEBMO in Solving Convex Economic Dispatch Problems

• Published in: AIP Conference Proceedings
• Main Author: Ismail N.L.; Musirin I.; Dahlan N.Y.; Mansor M.H.; Senthilkumar A.V.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193460368&doi=10.1063%2f5.0215220&partnerID=40&md5=8e7bee7c8d9aac0be3164960a71b7ca5

Minimization of the cost of generation for any utilities is crucial to ensure the utilities will be able to maintain continuous supply and their survivability. Non-optimal amount of power generated by all generating stations in a country will possibly lead to monetary loss and ineffective operation of the power system. Thus, a robust and reliable optimization technique is the prerequisite to ensuring the lowest cost of generation can be achieved. This paper proposes a hybridized optimization technique that integrates the element of evolutionary programming (EP) into the barnacle mating optimizer (BMO), termed Hybrid Evolutionary Programming-Barnacles Mating Optimization (HEBMO). HEBMO is utilized to address the convex economic dispatch in a power transmission system. Its implementation on the IEEE 30-Bus Reliability Test System (RTS) in addressing the convex ED is remarkable, through the comparison with the traditional EP and BMO. The cost of generations in chosen cases such as base case conditions, stress conditions due to real power, and reactive power increments revealed the superiority of the proposed HEBMO over EP and BMO. © 2024 American Institute of Physics Inc.. All rights reserved.