Energy savings and retrofit assessment for city-scale residential building stock during extreme heatwave events using genetic algorithm-numerical moment matching
Energy savings and retrofit assessment for city-scale residential building stock during extreme heatwave events using genetic algorithm-numerical moment matching
复制标题
使用遗传算法-数值矩匹配对极端热浪事件期间城市规模住宅建筑群进行节能和改造评估
DOI：
10.1007/s10098-022-02299-w
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发表时间：
2022
影响因子：
4.3
通讯作者：
Cetin, Kristen
中科院分区：
文献类型：
--
作者：
Jahani, Elham;Cetin, Kristen
在热浪事件期间，住宅建筑的电力需求和消耗通常高于非热浪事件期间。因此，这可能会大大增加城市规模的能源需求。为了支持可持续发展，重要的是能够预测建筑物电力消耗的增加水平及其相关影响。在这项研究中，2008年至2018年能源审计数据中的六个关键建筑能源变量被确定为德克萨斯州奥斯汀（湿热气候）17，000个单户住宅（SFH）能耗的重要预测因素。这些变量被用来作为输入的遗传算法为基础的数值矩匹配方法预测的电力消耗和需求的SFHS沿着与不确定性量化。该模型得到了2009年和2011年测量数据的验证。利用该模型，对几种节能改造方案在高峰时段的节电潜力和需求减少量进行了评估。结果表明，冷却系统效率的提高对高峰时段的需求减少有更大的影响，因为大约65%的日常节电发生在这些时间。阁楼隔热改造也可以将空调运行从高峰时间转移到非高峰时间。这种用于评估城市规模电力需求的定量方法支持建立对热浪事件的有效响应。图形摘要
During heatwave events electricity demand and consumption of residential buildings are generally higher than during non-heatwave events. As a result, this can significantly increase the energy demand at the city scale. In an effort to support sustainable development, it is important to be able to predict the level of increased building electricity consumption and its associated impacts. In this study, six key building energy variables from energy audit data from 2008 to 2018 were identified as significant predictors of energy consumption for 17,000 single family homes (SFHs) in Austin, Texas (hot-humid climate). These variables were utilized as input to a Genetic Algorithm-Based Numerical Moment Matching method to predict the electricity consumption and demand of SFHs along with uncertainty quantification. The model was validated with measured data for 2009 and 2011. Using this model, the potential electricity saving and demand reduction during peak hours for several energy efficiency retrofits were evaluated. The results indicate that, cooling system efficiency improvements have higher impact on demand reduction during peak hours since approximately 65% of daily electricity saving occurs during these hours. Attic insulation retrofits can also shift air conditioning operation from peak to off-peak hours. This quantitative approach for evaluating city-scale electricity demand supports establishing effective responses to heatwave events.Graphical abstract
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