Hybrid modeling for the multi-criteria decision making of energy systems: An application for geothermal district heating system

Abstract

The efficiency analysis technique with output satisficing (EATWOS) is a successful tool for determining the most efficient design for energy systems. Since EATWOS is rationally based on the maximal output throughout the minimal inputs, the weights of input and output values considerably affect the analysis results. Therefore, the impact ratio of each input and output term should be sensitively determined. In this study, the artificial neural network (ANN) modeling was used to determine the weights of the input values due to the quantitative effects of these values, whereas the analytical hierarchic process (AHP) was used for the output values due to qualitative effects. A new hybrid method was formed, embedding the ANN and AHP results into EATWOS. The new hybrid model was then applied to a sample geothermal district heating system for optimization. In this aim, 148 designs were formed throughout the different inlet parameters and evaluated by exergoeconomic and exergoenvironmental analysis to conduct the outputs. For the optimum case, the exergy efficiency was calculated as 20.25 %, whereas the SI was determined as 1.25, with the highest score. 1/r and 1/rb were determined as 0.002337 and 0.001677, respectively. The NPV value was determined as 4.44 million $.