In a smart grid, efficient load management can help balance and reduce the burden on the national power grid and also minimize local operational electricity cost. Robust optimization is a technique that is increasingly used in home energy management systems, where it is applied in the scheduling of household loads through demand side control. In this work, interruptible loads and thermostatically controlled loads are analyzed to obtain optimal schedules in the presence of uncertainty. Firstly, the uncertain parameters are represented as different intervals, and then in order to control the degree of conservatism, these parameters are divided into various robustness levels. The conventional scheduling problem is transformed into a deterministic scheduling problem by translating the intervals and robustness levels into constraints. We then apply Harris’ hawk optimization together with integer linear programming to further optimize the load scheduling. Cost and trade-off schemes are considered to analyze the financial consequences of several robustness levels. Results show that the proposed method is adaptable to user requirements and robust to the uncertainties.

中文翻译：

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基于价格的需求响应，用于具有区间不确定性的家庭负荷管理

在智能电网中，高效的负荷管理有助于平衡和减轻国家电网的负担，并最大限度地降低当地的运营电力成本。鲁棒优化是一种越来越多地用于家庭能源管理系统的技术，它通过需求侧控制应用于家庭负荷的调度。在这项工作中，分析了可中断负载和恒温控制负载，以便在存在不确定性的情况下获得最佳调度。首先将不确定参数表示为不同的区间，然后为了控制保守程度，将这些参数分为不同的鲁棒性级别。通过将间隔和鲁棒性水平转化为约束，将传统的调度问题转化为确定性调度问题。然后，我们应用 Harris 的 hawk 优化和整数线性规划来进一步优化负载调度。考虑成本和权衡方案来分析几个稳健性水平的财务后果。结果表明，该方法能够适应用户需求，并且对不确定性具有鲁棒性。