Journal
APPLIED ENERGY
Volume 182, Issue -, Pages 634-651Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2016.07.117
Keywords
Chance-constrained programming; Cycle based on/off; Wind energy; Incentive-based demand response program; Unit commitment; Improved Jaya algorithm
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Funding
- EPSRC [EP/F037686/1, EP/G055211/1, EP/K036173/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K036173/1, EP/G055211/1, EP/F037686/1] Funding Source: researchfish
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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. (C) 2016 Elsevier Ltd. All rights reserved.
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