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

Michael David de Souza Dutra(michaeldavidsd***at***gmail.com)
Gerson da Conceição Júnior(gjunior***at***thinkmax.com)
William de Paula Ferreira(william.ferreira***at***polymtl.ca)
Matheus Roberto Campos Chaves(chaves.matheus***at***hotmail.com.br )

Abstract: Smart homes allow the optimization of energy usage so that households can reduce electricity bills, or even make profits. By 2020, 20% of all households in Europe and 35% in North America 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 not worth the price. Adopting a smart home concept requires a significant amount of 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, including the net present value (NPV) one. 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 details for implementation purposes. Results show that the proposed tree algorithm is able to reduce days of CPU time to solve the problem and NPV should be used as an economic measure to answer the aforementioned question.

Keywords: Smart Home, Economic Analysis, Energy Management System, Interior Point.

Category 1: Applications -- OR and Management Sciences

Category 2: Applications -- Science and Engineering (Smart Grids )

Citation:

Download: [PDF]

Entry Submitted: 10/24/2019
Entry Accepted: 10/24/2019
Entry Last Modified: 10/24/2019

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