基于FL-NSGA-Ⅱ的室内设定温度计算方法研究
Research on calculation method of indoor set temperature based on FL-NSGA-Ⅱ
摘要：
以高校教室为应用对象,将热舒适与空调系统能耗作为优化目标,结合舒适度指标与建筑生物气候图构建了简化的舒适度计算模型,利用梯度提升回归(GBR)方法构建了空调系统能耗预测模型。在此基础上,采用模糊逻辑(FL)结合非支配排序遗传算法Ⅱ(NSGA-Ⅱ)的方法,计算了室内设定温度的帕累托(Pareto)解集,运用决策树方法确定了室内设定温度的唯一最优解。对比了实际与优化温度下的热舒适度和空调系统能耗,结果表明,该模型在提高舒适度的同时,有效降低了空调系统能耗。
Abstract：
This paper takes college classrooms as application objects, takes the thermal comfort and the energy consumption of air conditioning systems as optimization objectives, combines comfort indicators and building bioclimate maps to build a simplified comfort calculation model, and uses the gradient boosted regression (GBR) method to construct a prediction model of energy consumption of air conditioning systems. On this basis, the fuzzy logic (FL) combined with non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) method is used to calculate the Pareto solution set for the indoor set temperature, and the decision tree method is used to determine the unique optimal solution for the indoor set temperature. The thermal comfort and the energy consumption of air conditioning systems under actual working conditions and optimized temperatures are compared. The results show that the model can effectively reduce the energy consumption of air conditioning systems while improving comfort.
Keywords:indoor set temperature; thermal environment control; thermal comfort; energy conservation; fuzzy logic; non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ); college classroom