The IJICS (International Journal of Informatics and Computer Science)
Vol 6, No 1 (2022): March 2022

Micro Genetic Algorithm to Solve Economic Dispatch in IEEE 30 Bus Transmission System

Pressa Perdana Surya Saputra (Universitas Muhammadiyah Gresik, Jawa Timur)



Article Info

Publish Date
31 Mar 2022

Abstract

To produce electric power in a power system, it is necessary to find a way to keep the cost of generator fuel consumption or operating costs of the entire system to a minimum by determining the combined output power of each generating unit under the constraints of the system load demands and the limits of the generation capacity of each generating unit. . This method is known as economic generation. The researcher usually using conventional method such us Lagrange and more modern methods, Artificial Intelligence, such us Particle Swarm Optimization (PSO), Genetic Algorithm (GA) to solve economic dispatch problem. The newest technology in Artificial Intelligence had invented a new method to solve economic dispatch, it’s named micro-Genetic Algorithm (µ-GA). In this paper, µ-GA is applied to solve economic dispatch in IEEE 30 Bus Transmission System. Then the result will be compared by Lagrange and conventional GA. Thus the simulation show that µ-GA has better result than Lagrange and conventional GA. In IEEE 30 Bus System, μ-GA method results generation cost of 568.80 $/h with the generated power of 189.45 MW and system losses of  0.25 MW in 30th generation. It is 2.64% cheaper than the GA method and 1.15% cheaper than the Lagrange method. Finally, it can be said that in the case of economic dispatch in IEEE 30 Bus Transmission System, the μ-GA method is the best method compared to the Lagrange and GA methods.

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Journal Info

Abbrev

ijics

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

The The IJICS (International Journal of Informatics and Computer Science) covers the whole spectrum of intelligent informatics, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian ...