Multi-Agent Recommendation System for Electrical Energy Optimization and Cost Saving in Smart Homes

被引:14
作者
Jimenez-Bravo, Diego M. [1 ]
Perez-Marcos, Javier [1 ]
De la Iglesia, Daniel H. [1 ]
Villarrubia Gonzalez, Gabriel [1 ]
De Paz, Juan F. [1 ]
机构
[1] Univ Salamanca, Fac Sci, Expert Syst & Applicat Lab, Plaza Caidos S-N, Salamanca 37002, Spain
关键词
data acquisition; data processing; electricity; energy optimization; Internet of Things; money saving; multiagent; recommendation system; smart home; MANAGEMENT; TECHNOLOGIES; CITY;
D O I
10.3390/en12071317
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The European Union Establishes that for the next few years, a cleaner and more efficient energy system should be used. In order to achieve this, this work proposes an energy optimization method that facilitates the achievement of these objectives. Existing technologies allow us to create a system that optimizes the use of energy in homes and offers some type of benefit to its residents. Specifically, this study has developed a recommendation system based on a multiagent system that allows to obtain consumption data from electronic devices in a home, obtain information on electricity prices from the Internet, and provide recommendations based on consumption patterns of users and electricity prices. In this way, the system recommends new hours in which to use the appliances, offering the economic benefit that it would propose recommendations for the user. In this way, it is possible to distribute and optimize the use of energy in homes and reduce the peaks in electricity consumption. The system provides encouraging results in order to resolve the problem proposed by the European Union by optimizing the use of energy among different hours of the day and saving money for the customer.
引用
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页数:22
相关论文
共 30 条
  • [1] Aye N N., 2014, Global Journal of Flexible Systems Management, V15, P191, DOI [DOI 10.1007/s40171-014-0066-9, 10.1007/s40171-014-0066-9, DOI 10.1007/S40171-014-0066-9]
  • [2] A comparison of consumer perceptions towards smart homes in the UK, Germany and Italy: reflections for policy and future research
    Balta-Ozkan, Nazmiye
    Amerighi, Oscar
    Boteler, Benjamin
    [J]. TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2014, 26 (10) : 1176 - 1195
  • [3] Bian JL, 2011, 2011 4TH IEEE INTERNATIONAL CONFERENCE ON BROADBAND NETWORK AND MULTIMEDIA TECHNOLOGY (4TH IEEE IC-BNMT2011), P526, DOI 10.1109/ICBNMT.2011.6155990
  • [4] Braem B., 2017, SERIES COMPUTERS OPE, V8, P279, DOI DOI 10.1142/9789813200012_0012
  • [5] Occupancy based household energy disaggregation using ultra wideband radar and electrical signature profiles
    Brown, Robert
    Ghavami, Navid
    Siddiqui, Hafeez-Ur-Rehman
    Adjrad, Mounir
    Ghavami, Mohammad
    Dudley, Sandra
    [J]. ENERGY AND BUILDINGS, 2017, 141 : 134 - 141
  • [6] Day-ahead prediction of hourly electric demand in non-stationary operated commercial buildings: A clustering-based hybrid approach
    Chen, Yibo
    Tan, Hongwei
    Berardi, Umberto
    [J]. ENERGY AND BUILDINGS, 2017, 148 : 228 - 237
  • [7] Long-Term Care Services and Support Systems for Older Adults: The Role of Technology
    Czaja, Sara J.
    [J]. AMERICAN PSYCHOLOGIST, 2016, 71 (04) : 294 - 301
  • [8] On the Bayesian optimization and robustness of event detection methods in NILM
    De Baets, Leen
    Ruyssinck, Joeri
    Develder, Chris
    Dhaene, Tom
    Deschrijver, Dirk
    [J]. ENERGY AND BUILDINGS, 2017, 145 : 57 - 66
  • [9] ELHAWARY ME, 2016, PROCEEDINGS OF THE 2, P27
  • [10] Novel home energy management system using wireless communication technologies for carbon emission reduction within a smart grid
    Elkhorchani, Habib
    Grayaa, Khaled
    [J]. JOURNAL OF CLEANER PRODUCTION, 2016, 135 : 950 - 962