Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Due to the requirements of lower capital investment, higher operational flexibility, and the pressures from environmental legislations on local pollutants and global greenhouse gases (GHGs) emissions, power generation market is in favour of natural gas based electricity production in many regions, which is expected to be tripled between now and 2030. This trend will be particularly marked in developing countries such as China, where electricity demand is expected to rise most rapidly, while their local environment has been or is being severely damaged by heavily using low efficiency high polluted pulverized coal plants. Such a fuel switching can both enhance the local environment protection, and reduce the COz emissions, however, at a higher and more dynamic power generation cost. In this paper, the Pareto Optimal solutions regarding to two objectives of levelized cost of electricity and the associated COz emissions in relation to the design configurations and technical process parameters are obtained and presented for a natural gas combined cycle project in China, based on the developed 'environomic' models and a multiobjective optimizer. The obtained Pareto Optimal Frontiers tend to supply a flexible tool for handling the dynamics of important economic/market and environmental factors, so that the most proper design under a given circumstance can be easily identified through post-optimization simulation.Based upon which, the Clean Development Mechanism potentials of NGCC project in China are also discussed.
François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos
François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos
, ,