A novel method for acquiring rigorous temperature response functions for electricity demand at a regional scale
A novel method for acquiring rigorous temperature response functions for electricity demand at a regional scale
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一种获取区域尺度电力需求严格温度响应函数的新方法
DOI：
10.1016/j.scitotenv.2021.152893
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发表时间：
2022
影响因子：
9.8
通讯作者：
Ashina Shuichi
中科院分区：
文献类型：
--
作者：
Hiruta Yuki;Gao Lu;Ashina Shuichi
对电力的需求通过其对发电过程中温室气体排放的影响影响未来的气候，但气候变化也通过改变对加热和冷却的需求影响电力需求。开发可靠的温度响应函数（TRF），说明电力需求作为温度的函数，是减少气候变化下未来气候预测的不确定性和气候变化对能源系统影响评估的关键。然而，这项任务是具有挑战性的，因为电力需求是由多种因素决定的，这些因素以复杂的方式相互作用，因为需求波动代表了人类对给定气象条件的及时反应。我们提出了一种基于电力需求波动综合建模的区域范围内获取可靠TRF的新方法。六个候选算法进行了检查，和多元自适应回归样条（MARS）被选为最佳算法与所使用的数据集。使用MARS，我们构建了能够精确再现基于多个预测因子的复杂电力需求模式的模型，并模拟了温度对电力需求的影响，同时控制了其他因素的影响。检测了TRF中的时间段，并给出了日本10个地区的TRF参数和函数形式。
The demand for electricity affects the future climate through its effect on greenhouse gas emissions in the electricity generation process, but climate change also impacts electricity demand by changing the need for heating and cooling. Developing reliable temperature response functions (TRFs) that illustrate electricity demand as a function of temperature is key for decreasing uncertainty in future climate projections under a changing climate and for impact assessments of climate change on energy systems. However, this task is challenging because electricity demand is determined by multiple factors that interact in complicated ways because demand fluctuations represent timely human responses to given meteorological conditions. We propose a novel method to acquire reliable TRFs at a regional scale based on comprehensive modeling of electricity demand fluctuations. Six candidate algorithms were examined, and multivariate adaptive regression splines (MARS) was selected as the best algorithm with the dataset used. Using MARS, we constructed models with the capacity to precisely reproduce complex electricity demand patterns based on multiple predictors and simulated the impact of temperature on electricity demand while controlling for the effects of other factors. The temporal segments in TRFs are detected and parameters and functional forms of TRFs for 10 regions in Japan were presented.