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Volumn 205, Issue , 2017, Pages 1583-1595

Foresee: A user-centric home energy management system for energy efficiency and demand response

Author keywords

Demand response; Energy efficiency; Home energy management system; Model predictive control; Smart grid; User preference

Indexed keywords

COSTS; DIGITAL STORAGE; DOMESTIC APPLIANCES; ELECTRIC BATTERIES; ELECTRIC POWER TRANSMISSION NETWORKS; ENERGY MANAGEMENT; ENERGY MANAGEMENT SYSTEMS; ENERGY UTILIZATION; ENVIRONMENTAL IMPACT; FORECASTING; GRID COMPUTING; LEARNING ALGORITHMS; LEARNING SYSTEMS; MODEL PREDICTIVE CONTROL; SMART POWER GRIDS; THERMAL COMFORT;

EID: 85028320403     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2017.08.166     Document Type: Article
Times cited : (168)

References (36)
  • 1
    • 85167064273 scopus 로고    scopus 로고
    • U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Buildings Energy Data Book.
    • U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Buildings Energy Data Book.
  • 2
    • 84962254189 scopus 로고    scopus 로고
    • Smart home energy management systems: concept, configurations, and scheduling strategies
    • Zhou, B., Li, W., Chan, K.W., Cao, Y., Kuang, Y., Liu, X., et al. Smart home energy management systems: concept, configurations, and scheduling strategies. Renew Sustain Energy Rev 61 (2016), 30–40.
    • (2016) Renew Sustain Energy Rev , vol.61 , pp. 30-40
    • Zhou, B.1    Li, W.2    Chan, K.W.3    Cao, Y.4    Kuang, Y.5    Liu, X.6
  • 3
    • 84924128867 scopus 로고    scopus 로고
    • An evaluation and implementation of rule-based home energy management system using the rete algorithm
    • 591478
    • Kawakami, T., Fujita, N., Yoshihisa, T., Tsukamoto, M., An evaluation and implementation of rule-based home energy management system using the rete algorithm. Sci World J, 591478, 2014, 8.
    • (2014) Sci World J , pp. 8
    • Kawakami, T.1    Fujita, N.2    Yoshihisa, T.3    Tsukamoto, M.4
  • 4
    • 85006860819 scopus 로고    scopus 로고
    • An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid
    • Shakeri, M., Shayestegan, M., Abunima, H., Reza, S.S., Akhtaruzzaman, M., Alamoud, A., Sopian, K., Amin, N., et al. An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid. Energy Build 138 (2017), 154–164.
    • (2017) Energy Build , vol.138 , pp. 154-164
    • Shakeri, M.1    Shayestegan, M.2    Abunima, H.3    Reza, S.S.4    Akhtaruzzaman, M.5    Alamoud, A.6    Sopian, K.7    Amin, N.8
  • 6
    • 84921756002 scopus 로고    scopus 로고
    • Optimal scheduling of domestic appliances via MILP
    • Bradac, Z., Kaczmarczyk, V., Fiedler, P., Optimal scheduling of domestic appliances via MILP. Energies 8:1 (2015), 217–232.
    • (2015) Energies , vol.8 , Issue.1 , pp. 217-232
    • Bradac, Z.1    Kaczmarczyk, V.2    Fiedler, P.3
  • 7
    • 84883299352 scopus 로고    scopus 로고
    • MPC-based appliance scheduling for residential building energy management controller
    • Chen, C., Wang, J., Heo, Y., Kishore, S., MPC-based appliance scheduling for residential building energy management controller. IEEE Trans Smart Grid 4:3 (2013), 1401–1410.
    • (2013) IEEE Trans Smart Grid , vol.4 , Issue.3 , pp. 1401-1410
    • Chen, C.1    Wang, J.2    Heo, Y.3    Kishore, S.4
  • 9
    • 85167009240 scopus 로고    scopus 로고
    • Residential demand response scheduling with consideration of consumer preferences. Appl Sci 6(1).
    • Jovanovic R, Bousselham A, Bayram IS. Residential demand response scheduling with consideration of consumer preferences. Appl Sci 6(1).
    • Jovanovic, R.1    Bousselham, A.2    Bayram, I.S.3
  • 10
    • 85007318701 scopus 로고    scopus 로고
    • Reputation-based joint scheduling of households appliances and storage in a microgrid with a shared battery
    • AlSkaif, T., Luna, A.C., Zapata, M.G., Guerrero, J.M., Bellalta, B., Reputation-based joint scheduling of households appliances and storage in a microgrid with a shared battery. Energy Build 138 (2017), 228–239.
    • (2017) Energy Build , vol.138 , pp. 228-239
    • AlSkaif, T.1    Luna, A.C.2    Zapata, M.G.3    Guerrero, J.M.4    Bellalta, B.5
  • 11
  • 13
    • 84859873177 scopus 로고    scopus 로고
    • Towards a smart home energy management system – a dynamic programming approach
    • Tischer, H., Verbic, G., Towards a smart home energy management system – a dynamic programming approach. 2011 IEEE PES innovative smart grid technologies, 2011, 1–7.
    • (2011) 2011 IEEE PES innovative smart grid technologies , pp. 1-7
    • Tischer, H.1    Verbic, G.2
  • 14
    • 84883295379 scopus 로고    scopus 로고
    • An optimal power scheduling method for demand response in home energy management system
    • Zhao, Z., Lee, W.C., Shin, Y., Song, K.B., An optimal power scheduling method for demand response in home energy management system. IEEE Trans Smart Grid 4:3 (2013), 1391–1400.
    • (2013) IEEE Trans Smart Grid , vol.4 , Issue.3 , pp. 1391-1400
    • Zhao, Z.1    Lee, W.C.2    Shin, Y.3    Song, K.B.4
  • 16
    • 84939212244 scopus 로고    scopus 로고
    • A review on demand response: pricing, optimization, and appliance scheduling
    • Hussain, I., Mohsin, S., Basit, A., Khan, Z.A., Qasim, U., Javaid, N., A review on demand response: pricing, optimization, and appliance scheduling. Proc Comput Sci 52 (2015), 843–850.
    • (2015) Proc Comput Sci , vol.52 , pp. 843-850
    • Hussain, I.1    Mohsin, S.2    Basit, A.3    Khan, Z.A.4    Qasim, U.5    Javaid, N.6
  • 17
    • 84872075033 scopus 로고    scopus 로고
    • Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization
    • Chen, Z., Wu, L., Fu, Y., Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization. IEEE Trans Smart Grid 3:4 (2012), 1822–1831.
    • (2012) IEEE Trans Smart Grid , vol.3 , Issue.4 , pp. 1822-1831
    • Chen, Z.1    Wu, L.2    Fu, Y.3
  • 18
    • 85018402176 scopus 로고    scopus 로고
    • The new economics of energy storage
    • McKinsey & Company
    • D'Aprile, P., Newman, J., Pinner, D., The new economics of energy storage. 2016, McKinsey & Company.
    • (2016)
    • D'Aprile, P.1    Newman, J.2    Pinner, D.3
  • 20
    • 85167034640 scopus 로고    scopus 로고
    • Electricity storage in buildings for residential sector demand response: control algorithms and economic viability evaluation. Tech. rep. NIST GCR 14-978, Columbia University, NY; June
    • Zheng M, Meinrenken CJ, Lackner KS. Electricity storage in buildings for residential sector demand response: control algorithms and economic viability evaluation. Tech. rep. NIST GCR 14-978, Columbia University, NY; June 2014.
    • (2014)
    • Zheng, M.1    Meinrenken, C.J.2    Lackner, K.S.3
  • 21
    • 84951790312 scopus 로고    scopus 로고
    • Residential demand response algorithms: state-of-the-art, key issues and challenges
    • Springer International Publishing
    • Batchu, R., Pindoriya, N.M., Residential demand response algorithms: state-of-the-art, key issues and challenges. 2015, Springer International Publishing pp. 18–32.
    • (2015) , pp. 18-32
    • Batchu, R.1    Pindoriya, N.M.2
  • 22
    • 85019942306 scopus 로고    scopus 로고
    • Distributed generation: residential storage comes at a cost
    • 17006
    • Hittinger, E., Distributed generation: residential storage comes at a cost. Nature Energy, 2, 2017, 10.1038/nenergy.2017.6 17006.
    • (2017) Nature Energy , vol.2
    • Hittinger, E.1
  • 23
    • 0003517858 scopus 로고    scopus 로고
    • Model predictive control
    • Springer Science & Business Media
    • Camacho, E.F., Alba, C.B., Model predictive control. 2013, Springer Science & Business Media.
    • (2013)
    • Camacho, E.F.1    Alba, C.B.2
  • 24
    • 35548949549 scopus 로고
    • Smarts and smarter: Improved simple methods for multiattribute utility measurement
    • Edwards, W., Barron, F.H., Smarts and smarter: Improved simple methods for multiattribute utility measurement. Organ Behav Hum Decis Process 60 (1994), 306–325.
    • (1994) Organ Behav Hum Decis Process , vol.60 , pp. 306-325
    • Edwards, W.1    Barron, F.H.2
  • 28
    • 33846516584 scopus 로고    scopus 로고
    • Pattern recognition and machine learning
    • Springer-Verlag New York
    • Bishop, C., Pattern recognition and machine learning. 2006, Springer-Verlag, New York.
    • (2006)
    • Bishop, C.1
  • 29
    • 85012895569 scopus 로고    scopus 로고
    • Transactive home energy management systems: the impact of their proliferation on the electric grid
    • Pratt, A., Krishnamurthy, D., Ruth, M., Wu, H., Lunacek, M., Vaynshenk, P., Transactive home energy management systems: the impact of their proliferation on the electric grid. IEEE Electrif Mag 4:4 (2016), 8–14.
    • (2016) IEEE Electrif Mag , vol.4 , Issue.4 , pp. 8-14
    • Pratt, A.1    Krishnamurthy, D.2    Ruth, M.3    Wu, H.4    Lunacek, M.5    Vaynshenk, P.6
  • 30
    • 85167015043 scopus 로고    scopus 로고
    • Top 10 weather APIs
    • API University
    • Wagner, J., Top 10 weather APIs. 2014, API University.
    • (2014)
    • Wagner, J.1
  • 32
    • 85167005533 scopus 로고    scopus 로고
    • Residential building stock assessment: metering study. Tech. rep. E 14-283, Northwest Energy Efficiency Alliance; April
    • Ecotope Inc. Residential building stock assessment: metering study. Tech. rep. E 14-283, Northwest Energy Efficiency Alliance; April 2014.
    • (2014)
    • Ecotope Inc.1
  • 33
    • 85166991432 scopus 로고    scopus 로고
    • matlab software for disciplined convex programming, version 2.1; Mar. 2014. <>.
    • Grant M, Boyd S. CVX: matlab software for disciplined convex programming, version 2.1; Mar. 2014. < http://cvxr.com/cvx>.
    • Grant, M.1    Boyd, S.C.2
  • 34
    • 85166994523 scopus 로고    scopus 로고
    • OpenEI. Utility rate database. <>.
    • OpenEI. Utility rate database. < http://en.openei.org/wiki/Utility_Rate_Database>.
  • 35
    • 85167026463 scopus 로고    scopus 로고
    • Protection Agency. Emissions & generation resource integrated database (eGRID) 2006 version 2.1; April 2007.
    • U.S. Environmental Protection Agency. Emissions & generation resource integrated database (eGRID) 2006 version 2.1; April 2007.
    • Environmental, U.S.1
  • 36
    • 85167044964 scopus 로고    scopus 로고
    • Integrating renewables into the generation mix: challenges and unknowns. Tech. rep. Docket 11-IEP-1N, PSI Media;
    • Integrating renewables into the generation mix: challenges and unknowns. Tech. rep. Docket 11-IEP-1N, PSI Media; 2011.
    • (2011)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.