Solution of unit commitment problem using quasi-oppositional teaching learning based algorithm
This paper presents QOTLBO based algorithm to solve UC problems. Presents quasi oppositional based learning strategy to improve TLBO algorithm. Valve-point effects, ramp rate, spinning reserve and up/down time constraints are considered. The robustness of the QOTLBO is demonstrated in five standard UC problems. Performance of QOTLBO is found to be better than other techniques.
unit commitment ramp rate spinning reserve generation scheduling teaching learning based algorithm (tlbo) quasi-oppositional based learning (qobl)