A study for price-based unit commitment with carbon trading by DI&C simulation

Ting Chia Ou, Kai Hung Lu, Whei Min Lin, Chih Ming Hong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)


In this paper, the Hybrid Genetic Algorithm-Ant Colony Optimization (GACO) approach is presented to solve the unit commitment problem, and comparison with the results obtained using literature methods by nuclear-grade Digital Instrumentation and Control (DI&C) simulation. Then this paper applied the ability of the Genetic Algorithm (GA) operated after Ant Colony Optimization (ACO) can promote the ACO efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence. The other objective of this paper is to investigate an influence of emission constraints on generation scheduling. The motivation for this objective comes from the efforts to reduce negative trends in a climate change. In this market structure, the nuclear power plants (NPPs) and independent power producers (IPPs) have to deal with several complex issues arising from uncertainties in spot market prices, and technical constraints which need to be considered while scheduling generation and trading for the next day. In addition to finding dispatch and unit commitment decisions while maximizing its profit, their scheduling models should include trading decisions like spot-market buy and sell. The model proposed in this paper build on the combined carbon finance and spot market formulation, and help generators in deciding on when these commitments could be beneficial.

Original languageEnglish
Title of host publicationProceedings - INDIN 2010
Subtitle of host publication8th IEEE International Conference on Industrial Informatics
Number of pages6
Publication statusPublished - 2010
Event8th IEEE International Conference on Industrial Informatics, INDIN 2010 - Osaka, Japan
Duration: 2010 Jul 132010 Jul 16

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
ISSN (Print)1935-4576


Conference8th IEEE International Conference on Industrial Informatics, INDIN 2010

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems


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