Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1705-92
Abstract
This paper establishes a probabilistic scenario-based framework for the stochastic dynamic economic emission dispatch with unit commitment (SDEED-UC) problem, by considering wind power integration. The scenario generation and reduction method are implemented to describe wind power uncertainty. Accordingly, each wind power scenario is analyzed separately to determine the on/off status of the units. As for a predetermined significance level, the UC scheduling solution can be obtained with a probabilistic point of view, considering all the original scenarios. Then the SDEED problem is converted into a number of deterministic scheduling problems. For each scenario in the reduced set, an enhanced multiobjective particle swarm optimization algorithm is proposed to produce the Pareto optimal solutions. The practicability and performance of the proposed approach are illustrated through a case study, and the results are compared with the existing multiobjective evolutionary algorithms.
Keywords
Wind power, unit commitment, dynamic economic emission dispatch, probabilistic analysis method, enhanced multiobjective particle swarm optimization
First Page
4805
Last Page
4817
Recommended Citation
ZHANG, YACHAO; LIU, KAIPEI; LIAO, XIAOBING; QIN, LIANG; and AN, XUELI
(2017)
"A probabilistic scenario-based framework for solving stochastic dynamic economic emission dispatch with unit commitment,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25:
No.
6, Article 30.
https://doi.org/10.3906/elk-1705-92
Available at:
https://journals.tubitak.gov.tr/elektrik/vol25/iss6/30
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons