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Empowering the selection of demand response methods in smart homes: development of a decision support framework

机译：增强智能家居中需求响应方法的选择：决策支持框架的开发

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Demand Response (DR) facilitates the monitoring and management of appliances in energy grids by employing methods that, for example, increase the reliability of energy grids and reduce users’ cost. Within energy grids, Smart Home scenarios can be characterized by a unique combination of appliances and user preferences. To increase their impact, a scenario-specific selection of the best performing DR methods is necessary. As the user faces a multitude of heterogeneous DR methods to choose from, a complex decision problem is present. The primary goal of this study is to develop a decision support framework that can determine the best-performing DR methods. Building on literature analyses, expert workshops and expert interviews, we identify seven requirements, derive solution concepts addressing these requirements, and develop the framework by combining the concepts using a benchmarking process as a template. To demonstrate the framework’s applicability, we conduct a simulation study that uses artificial (simulated) data for seven types of households. Within this study, we employ four DR methods, assume changing appliances over time and cost minimization as primary objective. The study indicates, that by using the framework and thus by identifying and using the best DR method for each scenario, the users can achieve further cost benefits. The application of the framework allows practitioners to increase the efficiency of the DR method selection process and to further enhance DR-related benefits, such as cost minimization, load profile flattening, and peak load reduction. Researchers benefit from guidance for benchmarking and evaluating DR methods.
机译：需求响应（DR）通过采用一些方法来促进对电网中设备的监视和管理，这些方法例如可以提高电网的可靠性并降低用户的成本。在能源网格内，智能家居场景的特征在于设备和用户偏好的独特组合。为了增加其影响，必须根据具体情况选择性能最佳的灾难恢复方法。当用户面对众多可供选择的异构DR方法时，就会出现一个复杂的决策问题。这项研究的主要目标是建立一个可以确定性能最佳的灾难恢复方法的决策支持框架。在文献分析，专家研讨会和专家访谈的基础上，我们确定了七个需求，得出了满足这些需求的解决方案概念，并通过使用基准测试过程作为模板将这些概念进行组合来开发了框架。为了证明该框架的适用性，我们进行了一项模拟研究，该模拟研究使用了针对七种类型家庭的人工（模拟）数据。在本研究中，我们采用了四种灾难恢复方法，并假设随时间推移更换设备和将成本降至最低是主要目标。研究表明，通过使用该框架，从而针对每种情况确定和使用最佳的灾难恢复方法，用户可以实现进一步的成本优势。该框架的应用允许从业人员提高灾难恢复方法选择过程的效率，并进一步增强与灾难恢复相关的好处，例如成本最小化，负载分布平坦化和峰值负载降低。研究人员受益于基准测试和评估灾难恢复方法的指南。

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