Title :
A new approach for profit-based unit commitment using Lagrangian relaxation combined with ant colony search algorithm
Author :
Bavafa, M. ; Navidi, N. ; Monsef, H.
Author_Institution :
Univ. of Tehran, Tehran
Abstract :
The past decade has seen a dramatic change in the manner in which the power industry is organized. It has moved from a formerly vertically integrated and highly regulated industry to one that has been horizontally integrated in which the generation, transmission and distribution are unbundled. In the past, utilities had to produce power to satisfy their customers with objective to minimize costs and all demand/reserve were met. However, it is not necessary in a restructured system. Under new structure, generation companies (GENCOs) schedule their generators with objective to maximize their own profit without regard for system social benefit. Power and reserve prices become important factors in decision process. GENCOs´ decision to commit generating units is associated with financial risks. This unit commitment has a different objective than that of the traditional unit commitment and is referred to as profit-based unit commitment to emphasize the importance of the profit. This paper presents a hybrid model between Lagrangian relaxation (LR) and Ant Colony search algorithm (ACSA) to solve the profit-based UC problem.
Keywords :
power generation scheduling; search problems; Lagrangian relaxation; ant colony search algorithm; financial risks; generation companies; power industry; profit-based unit commitment; system social benefit; Ant colony optimization; Cost function; Demand forecasting; Economic forecasting; Job shop scheduling; Lagrangian functions; Power generation; Power industry; Production systems; Spinning;
Conference_Titel :
Universities Power Engineering Conference, 2008. UPEC 2008. 43rd International
Conference_Location :
Padova
Print_ISBN :
978-1-4244-3294-3
Electronic_ISBN :
978-88-89884-09-6
DOI :
10.1109/UPEC.2008.4651475