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A customized transition towards smart homes: A fast framework for economic analyses

机译:向智能家居的定制过渡:经济分析的快速框架

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摘要

Smart homes allow optimized energy usage, allowing households to reduce electricity bills or even make profits. By 2020, 20% of all households in Europe will be expected to become smart homes. Although smart homes seem to be the future for homes, many customers have the perception that a transition from current homes to smart ones is unprofitable. Adopting a smart home concept requires investments for which the households desire a positive return. A question in this context is the following: for a given household, when and/or what set of home appliances/technologies should be acquired so that the investment made by householder has a positive financial return? The available tool to answer that question can be time-consuming from a practical perspective. Based on our previous work, this paper proposes a framework to help the transition from current houses to smart homes considering customized electricity usage and economic measures. A tree algorithm is developed to decrease the time needed by an economic analysis of each possible acquisition combination of smart appliances or equipment for a given user. The proposed framework is tested on 40 cases covering all Brazilian capital cities, whose results are available online and may be used directly as an approximation for economic analyses. An example of one case is described in detail. Results show that the proposed tree algorithm is able to reduce days of CPU time to solve the problem and Net Present Value should be used as an economic measure to answer the aforementioned question.
机译:智能家居可优化能源使用,使家庭减少电费甚至获利。到2020年,预计将有20%的欧洲家庭成为智能家居。尽管智能家居似乎是家庭的未来,但许多客户仍认为从当前的家居到智能家居的过渡是无利可图的。采用智能家居的概念需要家庭希望获得正回报的投资。在这方面的一个问题是:对于给定的家庭,什么时候和/或应该购买什么套家用电器/技术,以使家庭的投资获得正的财务回报?从实用的角度来看,用于回答该问题的可用工具可能很耗时。在我们之前的工作的基础上,本文提出了一个框架,以考虑自定义的用电量和经济措施来帮助从当前房屋向智能家居过渡。开发了树形算法,以减少对给定用户的智能设备或设备的每种可能的购置组合进行经济分析所需的时间。拟议的框架在覆盖巴西所有首都城市的40个案例中进行了测试,其结果可在线获得,并可直接用作经济分析的近似值。详细描述一种情况的示例。结果表明,所提出的树算法能够减少解决问题所需的CPU时间,并且净现值应作为回答上述问题的经济措施。

著录项

  • 来源
    《Applied Energy》 |2020年第15期|1209-1220|共12页
  • 作者

  • 作者单位

    Ecole Polytech Montreal CP 6079 Succursale Ctr Ville Montreal PQ H3C 3A7 Canada;

    Fac Cidade Verde Maringa Parana Brazil;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Smart home; Economic analysis; Energy management system; Interior point; Optimization;

    机译:智能家居经济分析;能源管理系统;内部点;优化;

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