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Modern Power Plant Control for Energy Conservation, Efficiency Increase, and Financial Benefit

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  • First Online:
Handbook of Climate Change Mitigation and Adaptation

Abstract

Process control takes place in all power plants. The main task of all automatic controllers is to assure the optimal values of their controlled variables under all circumstances. The quality of operation of these controllers has evidently a crucial effect on the way of operation of the entire power plant. Whether a power plant – based on either renewable resources or fossil fuels – is operated in a highly effective way, or is a rather resource-consuming one, is evidently of very high importance regarding emissions and other ecological aspects. This fact is the reason for discussing in this chapter the possible ways for increasing the level of control quality in power plants.

An overview will be given at the beginning about the ways and tools the advanced control methods offer – in case of their more intensive applications in power plants – for protecting the environment and for mitigating the climate change. It will be followed by a concise but goal-oriented introduction of the most relevant control methods together with their evaluations regarding the aspects of their applicabilities in power plants. Because the way toward obtaining the environmental benefits offered by the advanced control methods is not a trivial one, some considerations, aspects, and hints will be given on this issue in the next part. A few successful power plant applications will be introduced afterward, and the actual main development directions will be outlined at the very end of this chapter.

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Abbreviations

A(q) :

Polynomial in the ARX model

a 1…a 5 :

Free parameters of the cost function

B 1 (q) :

Polynomial in the two-input ARX model

B 2 (q) :

Polynomial in the two-input ARX model

b 1…b 5 :

Free parameters of the cost function

C CO mol/m3 :

Molar concentration of CO in the flue gas

C NO mol/m3 :

Molar concentration of NO in the flue gas

e :

Control error

e(t) :

Equation error of the ARX model

K :

Cost function

q :

Time shift operator

r :

Air distribution: ratio of primary air to total air

r :

Reference signal (set point)

t s :

Time

u :

Control signal (process input)

\( {\dot{V}}_{\mathrm{A}} \) m3/s:

Total air flow

\( {\dot{V}}_{\mathrm{P}} \) m3/s:

Primary air flow

\( {\dot{V}}_{\mathrm{S}} \) m3/s:

Secondary air flow

y :

Controlled variable

y M :

Controlled variable modeled

ϑ, T K:

Bed temperature

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Acknowledgments

The author is grateful to ProcessEng Engineering GmbH, Vienna, Austria, and to Periodica Polytechnika Civil Engineering, Budapest, Hungary, for permitting to use some materials published by the author earlier in Szentannai (2010, 2011).

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Authors and Affiliations

  1. Department of Energy Engineering, Budapest University of Technology and Economics, Muegyetem rkp. 9, H-1111, Budapest, Hungary

    Pal Szentannai

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  1. Pal Szentannai
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Correspondence to Pal Szentannai .

Editor information

Editors and Affiliations

  1. University of Mississippi Dept. Chemical Engineering, University, Mississippi, USA

    Wei-Yin Chen

  2. Advanced Manufacturing Research Inst. Functional Assembly Technology Group, National Institute of Advanced Industrial Science & Technology (AIST), Nagoya, Japan

    Toshio Suzuki

  3. und Technische Biowissenschaften, TU Wien Inst. Verfahrenstechnik, Umwelttechnik, Wien, Austria

    Maximilian Lackner

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Szentannai, P. (2015). Modern Power Plant Control for Energy Conservation, Efficiency Increase, and Financial Benefit. In: Chen, WY., Suzuki, T., Lackner, M. (eds) Handbook of Climate Change Mitigation and Adaptation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6431-0_22-2

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  • DOI: https://doi.org/10.1007/978-1-4614-6431-0_22-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-6431-0

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