Parametric optimization of supercritical coal-fired power plants by MINLP and differential evolution

Abstract

The design trade-offs between thermodynamics and economics of energy conversion systems can be more effective by combining a superstructure and mixed-integer non-linear programming (MINLP) techniques. The front of decision space showing the optimal sets of economic behavior and system efficiency with different corresponding optimal system structures and process variables can provide additional and useful information on cost-effective design of thermal systems. In this paper, this idea was successfully applied to supercritical coal-fired power plants to investigate the economically-optimal designs at each efficiency level. The superstructure involving up to ten feedwater preheaters, up to two reheatings and a secondary turbine with steam extractions (ET) was built. An improved differential evolution algorithm was used to simultaneously solve the parametric and structural optimization problem. The differences among the fronts of various types of plants, the front changes with plant efficiency and the effects of introducing an ET were discussed in detail. For a single reheating unit, a decrease of 2% in cost of electricity can be achieved. The optimal pressure ratios of reheatings are 0.15–0.25 (for single reheating), 0.2–0.3 and 0.15–0.3 (for double reheatings).