Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power. (15th November 2016)

• Record Type: Journal Article
• Authors: Azizipanah-Abarghooee, Rasoul; Golestaneh, Faranak; Gooi, Hoay Beng; Lin, Jeremy; Bavafa, Farhad; Terzija, Vladimir
• Is Part Of: Applied energy. Volume 182(2016)
• Page Start: 634
• Page End: 651
• Publication Date: 2016-11-15
• Subjects: Chance-constrained programming -- Cycle based on/off -- Wind energy -- Incentive-based demand response program -- Unit commitment -- Improved Jaya algorithm; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.07.117
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Suggesting a new UC mixing a probabilistic security and incentive demand response. Investigating the effects of uncertainty on UC using chance-constraint programming. Proposing an efficient spinning reserve satisfaction based on a new ED correction. Presenting a new operational cycles way to convert binary variable to discrete one. Abstract: We propose a probabilistic unit commitment problem with incentive-based demand response and high level of wind power. Our novel formulation provides an optimal allocation of up/down spinning reserve. A more efficient unit commitment algorithm based on operational cycles is developed. A multi-period elastic residual demand economic model based on the self- and cross-price elasticities and customers' benefit function is used. In the proposed scheme, the probability of residual demand falling within the up/down spinning reserve imposed by n − 1 security criterion is considered as a stochastic constraint. A chance-constrained method, with a new iterative economic dispatch correction, wind power curtailment, and commitment of cheaper units, is applied to guarantee that the probability of loss of load is lower than a pre-defined risk level. The developed architecture builds upon an improved Jaya algorithm to generate feasible, robust and optimal solutions corresponding to the operational cost. The proposed framework is applied to a small test system with 10 units and also to the IEEE 118-bus system to illustrate its advantages in efficient scheduling of generation in the power systems.