Spinning reserve scheduling of power systems: An ant colony approach

This paper presents an Ant Colony System (ACS) based optimization approach to solve the optimal spinning reserve problem for a power system. Unit commitment risk is used as an index to evaluate the level of spinning reserve. The outage cost and the fuel cost of thermal units were considered in the unit commitment program. The optimal spinning reserve and unit commitment risk were reached while the sum of fuel cost and outage cost was minimized. A 52 units power system was used as a numerical example to test the new algorithm. The optimal spinning reserve and unit commitment risk could be reached in the testing while satisfying the requirement of the objective function.