Optimization of a three-layer rotary generator using genetic algorithm to minimize fuel consumption

Abstract

Reduction of fuel consumption in power plants is an important issue due to their high rate of fuel usage. In the present article, this was done by optimizing rotary regenerator which have a great role in recovering thermal energy in power stations. Heat transfer and pressure drop through 13 popular flow passages of power plant's rotary regenerators were obtained by CFD simulations. The outcomes were used in a mathematical model of the rotary air heater by considering air leakages. The model was capable of distinguishing between different heating surfaces. Then it was used for optimizing a regenerator by genetic algorithm. Rotational speed and dimensions of all three layers (hot end, intermediate layer, and cold end) were optimized to achieve the highest fuel saving. These dimensions were: hydraulic diameters, heating profile type, and length of each layer. Results showed that redesigning these parameters to the optimal values leads to saving of 443 kg of natural gas per hour for one regenerator. A 10 meter regenerator also had the highest reduction in fuel consumption (660 kg/hr). Finally, the influence of air and hot gas temperatures, and air mass flow rate on fuel saving and optimum values of design parameters was discussed.