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Simulator for optimal scheduling of domestic appliances

机译:用于最佳调度的模拟器

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Introduction of real-time pricing models for the price of electricity may lead to a reduction in both economic and environmental burden compared with existing models. Thanks to the timely response to price changes during the day the user can achieve a reduction in the payments for energy. However, recent studies show that lack of knowledge of users and their unwillingness to adapt their habits to changing energy prices is the biggest obstacle to successful implementation of the model. In our work, we propose to solve this problem by introducing automatic optimal energy consumption scheduling framework. This article presents the authors extension in the past created MILP model for the optimization of household appliances. The model is extended by rules of behavior that allows preserving logical links in the course of periodically triggered optimization (so called receding horizon). We also present and test the software simulator, in which the designed model is implemented. The application simulates the operation of Building Energy Manager, which based on user preferences, prediction electricity prices and other important parameters controls the operation of appliances in the house.
机译:与现有型号相比,电力价格的实时定价模型可能导致经济和环境负担减少。由于在当天及时回复价格变化,用户可以减少能源的付款。然而,最近的研究表明,对用户的习惯缺乏对用户的习惯来改变能源价格的习惯是成功实施模型的最大障碍。在我们的工作中,我们建议通过引入自动最佳能耗调度框架来解决这个问题。本文介绍了过去的作者延伸,为优化家用电器创造了MILP模型。该模型由行为规则扩展,允许在定期触发优化过程中保留逻辑链接(所谓的后退地平线)。我们还存在并测试软件模拟器,其中实现了设计的模型。该应用程序模拟建筑能源管理器的操作,基于用户偏好,预测电价等重要参数控制房屋内器的运行。

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