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GTPOM: Thermo-Economic Optimization of Whole Gas Turbine Plant
Journal article   Peer reviewed

GTPOM: Thermo-Economic Optimization of Whole Gas Turbine Plant

Richard Knight, Mitsuru Obana, Christer von Wowern, Athanasios Mitakakis, Erhard Perz, Mohsen Assadi, Bjo¨rn F. Mo¨ller, Pratyush Sen, Ian Potts, Alberto Traverso, …
Journal of engineering for gas turbines and power, v 128(3), pp 535-542
01 Jul 2006
DOI: https://doi.org/10.1115/1.1850511
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

power generation economics combined cycle power stations costing bioenergy conversion genetic algorithms gas turbine power stations distributed power generation power markets thermal analysis power system analysis computing
Trends towards distributed power generation and the deregulation of energy markets are increasing the requirement for software tools that optimize power generation plant design and operation. In this context, this paper describes the GTPOM (thermo-economic optimization of whole gas turbine plant) European project, funded in part through the European Commission’s 5th Framework Programme, focusing on the development and demonstration of an original software tool for the thermo-economic analysis and optimization of conventional and advanced energy systems based on gas turbine plant. PSEconomy, the software tool developed during the GTPOM project, provides a thermo-economic optimization capability for advanced and more-conventional energy systems, enabling the complex trade-offs between system performance and installed costs to be determined for different operational duties and market scenarios. Furthermore, the code is capable of determining the potential benefits of innovative cycles or layout modifications to existing plants compared with current plant configurations. The economic assessment is performed through a complete through-life cycle cost analysis, which includes the total capital cost of the plant, the cost of fuel, O&M costs and the expected revenues from the sale of power and heat. The optimization process, carried out with a GA-based algorithm, is able to pursue different objective functions as specified by the User. These include system efficiency, through-life cost of electricity and through-life internal rate of return. Three case studies demonstrating the capabilities of the new tool are presented in this paper, covering a conventional combined cycle system, a biomass plant and a CO2 sequestration gas turbine cycle. The software code is now commercially available and is expected to provide significant advantages in the near and long-term development of energy cycles.

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5 citations in Web of Science
9 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#7 Affordable and Clean Energy

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Collaboration types
Industry collaboration
Domestic collaboration
International collaboration
Web of Science research areas
Engineering, Mechanical
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