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Research Papers: Gas Turbines: Cycle Innovations

Energy and Reserve Co-optimization of a Combined Cycle Plant Using Mixed Integer Linear Programming

[+] Author and Article Information
F. A. Campos

Institute for Research in Technology (IIT),
Technical School of Engineering (ICAI),
Comillas Pontifical University,
Santa Cruz de Marcenado 26,
Madrid 28015, Spain
e-mail: alberto.campos@iit.upcomillas.es

J. Reneses

Institute for Research in Technology (IIT),
Technical School of Engineering (ICAI),
Comillas Pontifical University,
Santa Cruz de Marcenado 26,
Madrid 28015, Spain
e-mail: javier.reneses@iit.upcomillas.es

Statistical analyses using real data taken directly from the CCP confirm that all the regressions are very accurate, with coefficients of determination always higher than 0.9 even in pessimistic scenarios.

Contributed by the Cycle Innovations Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received October 15, 2013; final manuscript received June 24, 2014; published online July 29, 2014. Assoc. Editor: Paolo Chiesa.

J. Eng. Gas Turbines Power 136(10), 101702 (Jul 29, 2014) (11 pages) Paper No: GTP-13-1372; doi: 10.1115/1.4028002 History: Received October 15, 2013; Revised June 24, 2014

The growth in the importance of interruptible sources of energy is increasing the concerns of many electricity market regulators with respect to the reliability and stability of electricity supply. Decisions such as that to increase the number of reserve markets, their reserve requirements, or the role of reserve prices in the final electricity price have meant that generation plants are currently often operating with strategies to obtain not only large energy market quotes but also reserve ones. In this paper, a mixed integer linear programming (MILP) model is proposed to obtain the energy and reserve dispatch of a real combined cycle plant (CCP) to optimize its use on a weekly or annual basis. The dispatch is optimal in the sense that it maximizes the joint energy and reserve profits, including an estimation of the energy and reserve prices. The detailed technical and economic characteristics of the plant have been considered, such as start-ups, shut-downs, minimum hours for steam generation, supplementary firing, or natural gas contracts. The cases studies validate the main features of the mathematical model and analyze the computational efficiency in a realistic simulation.

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References

Figures

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Fig. 2

Gas consumption as a linear function of gross power

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Fig. 4

Economic results for Jan. 2013

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Fig. 3

Day-ahead and reserve prices for Jan. 2013

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Fig. 5

Production, reserve and gas consumption for Jan. 2013

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Fig. 9

Gas consumption, and daily and monthly contracted capacities, for Jan. 2013

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Fig. 6

Dispatch results for 6 h on Jan. 2013

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Fig. 7

Dispatch results for Jan. 3, 2013

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Fig. 8

Daily and monthly contracted capacities of gas for Jan. 2013

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