1 Department of Energy Technology, The Faculty of Engineering and Science, Aalborg University, VBN2 Fluid Mechanics and Combustion, The Faculty of Engineering and Science, Aalborg University, VBN3 The Faculty of Engineering and Science (ENG), Aalborg University, VBN4 Department of Mechanical Engineering, Babol University of Technology, Babol5 unknown
Optimal design of thermal systems that effectively use energy resources is one of the foremost challenges that researchers almost confront. Until now, several researches have been made to enhance the performance of major thermal systems. In this investigation, the authors try to make a conceptual design to maximize the electricity demand of Damavand power plant as the biggest thermal system in Middle East sited in Iran. The idea of designing is laid behind applying a number of thermoelectric modules within the condenser in order to recover the waste heat of the thermal systems. Besides, the authors have developed some intelligent tools to elaborate on the performance of their proposed model. Firstly, an artificial neural network has been utilized to estimate the potential power generation of the thermoelectric modules. At the second step, computational fluid dynamic solver, FLUENT is used to determine the variation of the temperature through the length of the thermoelectric module assembly. Based on the gained results, an intelligent multi-objective optimization algorithm called Pareto based mutable smart bee is developed to optimize the properties of the thermoelectric component.
Meccanica, 2014, Vol 49, Issue 5, p. 1211-1223
Artificial neural network; Damavand power plant; Engineering optimization; Mutable smart bee algorithm; Waste heat recovery system