The technological advancement in the communication and control infrastructure helps those smart households (SHs) that more actively participate in the incentive-based demand response (IBDR) programs. As the agent facilitating the SHs' participation in the IBDR program, load aggregators (LAs) need to comprehend the available SHs' demand response (DR) capacity before trading in the day-ahead market. However, there are few studies that forecast the available aggregated DR capacity from LAs' perspective. Therefore, this article proposes a forecasting model aiming to aid LAs forecast the available aggregated SHs' DR capacity in the day-ahead market. First, a home energy management system is implemented to perform optimal scheduling for SHs and to model the customers' responsive behavior in the IBDR program; second, a customer baseline load estimation method is applied to quantify the SHs' aggregated DR capacity during DR days; third, several features which may have significant impacts on the aggregated DR capacity are extracted and they are processed by principal component analysis; and finally, a support vector machine based forecasting model is proposed to forecast the aggregated SHs' DR capacity in the day-ahead market. The case study indicates that the proposed forecasting framework could provide good performance in terms of stability and accuracy.

中文翻译：

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智能家居基于激励的需求响应计划下负载聚合器的聚合容量预测


通信和控制基础设施的技术进步有助于智能家庭（SH）更积极地参与基于激励的需求响应（IBDR）计划。作为促进SH参与IBDR计划的代理，负荷聚合商（LA）需要在日前市场进行交易之前了解可用SH的需求响应（DR）能力。然而，很少有研究从洛杉矶的角度预测可用的聚合灾难恢复能力。因此，本文提出了一种预测模型，旨在帮助LA预测日前市场上可用的聚合SH的灾难恢复能力。首先，实施家庭能源管理系统来对SH进行优化调度，并在IBDR计划中对客户的响应行为进行建模；其次，采用客户基线负载估算方法来量化SH在灾难恢复日期间的聚合灾难恢复能力；第三，提取可能对聚合灾难恢复能力产生重大影响的几个特征，并通过主成分分析对其进行处理；最后，提出了基于支持向量机的预测模型来预测日前市场上聚合的SH的DR容量。案例研究表明，所提出的预测框架在稳定性和准确性方面可以提供良好的性能。