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Multi-objective optimization of steam power plants for sustainable generation of electricity

A unified framework that combines process simulation and multi-objective optimization is presented to simultaneously maximize the annual profit, while minimizing environmental impact (i.e., greenhouse gas emissions) of steam power plants with fixed flowsheet structures. The proposed methodology includes the selection of suitable primary energy sources (i.e., fossil fuels, biomass, biofuels, and solar energy) for sustainable electricity generation. For solving the problem of optimal selection of energy sources, a linear model is developed and included within a highly nonlinear simulation model for the parameter optimization of steam power plants that is solved by using genetic algorithms. This approach is robust and avoids making discrete decisions. Life cycle assessment technique is used to quantify the greenhouse gas emissions resulting from different combinations of energy sources and operating conditions of the power plants. The thermodynamic properties for liquid water and steam are calculated rigorously using the IAPWS-IF 97 formulation. An example problem of an advanced regenerative-reheat steam power plant is presented to illustrate the proposed method, which provides the Pareto optimal solutions, the types and amounts of primary energy sources as well as the optimal values of the operating conditions of the plant that simultaneously maximize the profit while minimizing environmental impact.
- King Abdulaziz University Saudi Arabia
- Universidad Michoacana de San Nicolás de Hidalgo Mexico
- The University of Texas System United States
- King Abdulaziz University Saudi Arabia
- Universidad Michoacana de San Nicolás de Hidalgo Mexico
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
