Ant Colony Optimization For Active/Reactive Operational Planning

Authors:	Lee Kwang Y., The Pennsylvania State University, United States Vlachogiannis John G., Industrial & Energy Informatics Laboratory, Greece
Topic:	6.3 Power Plants and Power Systems
Session:	Power System Stability
Keywords:	Power systems, Operational planning, Economic dispatch, Reactive power planning, Artificial Intelligence, Ant colony optimization

Abstract

This paper proposes the application of Ant Colony Optimization (ACO) for active/reactive operational planning of power systems. The ACO is a newly developed method belonging to the class of evolutionary computation methods inspired from real ants life. Specifically, ACO algorithm aims to determine the optimal settings of control variables, such as generator outputs, generator voltages, transformer taps and shunt VAR compensation devices, considered as nodes of an Ant-System (AS) graph. Results are compared to those given by Simulated Annealing for the IEEE 30-bus test system, exhibiting superior performance.