Abstract
A model that could ensure the lowest energy consumption and optimize all possible performance parameters simultaneously was proposed based on experiments that run the ground source heat pump passive heat supply tower at given conditions. By studying the relationship between the range, approach, tower characteristic ratio, effectiveness, air condensation rate of the passive heat supply tower and water-air ratio, a multi-objective optimization model and its objective function are proposed. With the target of reducing power consumption to the greatest extent, the unconstrained optimization of all objective functions was performed using the Elite Non-dominated Sorting Genetic Algorithm (NSGA-II), in which five performance parameters were adopted to estimate the air flow via decision making at a given water flow rate. The results show that the heat transfer is independent of the water flow. An optimal water-air ratio of 0.48 is determined according to comprehensive analysis of the parameter weights. Under constant water flow rate, the optimal air flow rate and water flow rate is 108.5 g/s and 47.2 g/s, respectively, as observed by comparing the Decision Matrix Score (DMS) value. According to the multi-objective optimization method and the NSGA-II algorithm, optimizations of the performance of supplementary tower are more effective and reasonable as the Decision Making Matrix (DMM) can reasonably allocate parameters expected by users to occupy a larger weight.
Published Version
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