Pareto optimization of a combined cycle power system as a decision support tool for trading off investment vs. operating costs |
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| Affiliation: | 1. Goethe GbR, Reimser Str. 52, 52074 Aachen, Germany;2. E.ON Sales & Trading GmbH, Denisstr. 2, 80335 München, Germany;3. Aachen University of Technology, Chair for Technical Thermodynamics, Schinkelstr. 8, 52056 Aachen, Germany;1. Department of Mechanical Power Engineering, Zagazig University, Zagazig 44159, Egypt;2. Department of Aerospace Engineering, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia;3. Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia;1. Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin 300134, China;2. Department of Human and Engineered Environmental Studies, The University of Tokyo, Chiba 277-8563, Japan;3. Foreign Economic Cooperation Office, Ministry of Ecology and Environmrnt of the People''s Republic of China, Beijing 100035, China;4. Future Energy Center, School of Sustainable Development of Society and Technology, Mälardalen University, Västerås SE-72123, Sweden;5. Marine Engineering College, Dalian Maritime University, Dalian, Liaoning 116026, China;1. Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran;2. Faculty of Engineering, Urmia University, Urmia, Iran;3. Mapna O & M, Jahrom Combined Cycle Power Plant, Jahrom, Iran;4. Thermal Department, School of Mechanical Engineering, National Technical University of Athens, Zografou, Heroon Polytechniou 9, 15780 Athens, Greece;1. Dept. of Environmental Science and Engineering, College of Engineering, Center for Environmental Studies, Kyung Hee University, Seocheon-dong 1, Giheung-gu, Yongin-Si, Gyeonggi-Do, 446-701, South Korea;2. School of Mechanical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 136-701, South Korea |
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| Abstract: | The monetary optimization of thermodynamic processes may be approached by inherently thermodynamic frameworks like exergo-economic analysis, or a rigid direct cost evaluation is applied. This paper, treating the optimization of a combined cycle power plant, follows the second path. Operation and investment costs are usually treated as a combined value by means of an annualization factor. Due to the rather far-stretching time horizon of turbine energy conversion systems, differing behaviour of those contributions with time, and varying subjective weighting and assumptions of future developments, this conventional subsumption is not necessarily a sensible one to identify the best solution for a given decision situation. It is therefore favorable to address both costing goals independently and identify the pareto set of the problem prior to a final decision on which parametrization of the system should be chosen. A numerical pareto optimization technique based on an evolutionary base strategy is discussed that addresses this type of problem in an efficient and easy to adapt manner. |
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