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Simulator for optimal scheduling of domestic appliances

机译：用于家用电器最佳调度的模拟器

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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：与现有模型相比，引入电价实时定价模型可以减少经济和环境负担。由于白天对价格变化的及时响应，用户可以减少能源支出。但是，最近的研究表明，用户缺乏知识以及他们不愿意使自己的习惯适应不断变化的能源价格，是成功实施该模型的最大障碍。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此问题。本文介绍了作者在过去创建的用于优化家用电器的MILP模型的扩展。该模型由行为规则扩展，该行为规则允许在定期触发的优化过程中保留逻辑链接（所谓的后退范围）。我们还介绍并测试了实现所设计模型的软件模拟器。该应用程序模拟了建筑节能管理器的操作，该管理器基于用户的偏好，预测电价和其他重要参数来控制房屋中电器的操作。

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