Forecast load impact from demand response resources
Forecast load impact from demand response resources
复制标题
预测需求响应资源的负载影响
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Raymond Johnson
中科院分区：
文献类型：
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作者：
Xiaoyang Zhou;N. Yu;W. Yao;Raymond Johnson
为了提高需求响应资源的基线负荷和负荷影响的预测准确性，本文开发了三种创新的统计模型。这些模型是回归样条固定效应模型、固定效应变点模型和混合效应变点模型。开发的模型用于预测南加州空调循环需求响应计划的基线负荷和负荷影响。所有三个预测模型都能对基线负载和需求响应事件的负载影响进行准确的预测。从数据集中观察到需求响应事件的明显反弹效应。
To improve forecasting accuracy for baseline load and load impact from demand response resources, this paper develops three innovative statistical models. These models are regression spline fixed effect model, fixed effect change point model and mixed effect change point model. The models developed are applied to forecast baseline load and load impact from air conditioning cycling demand response program in Southern California. All three forecasting models yield accurate forecasts for baseline load and load impact from demand response events. Noticeable rebound effect from demand response events are observed from the dataset.