메뉴 건너뛰기




Volumn 1, Issue 14, 2016, Pages 1016-1019

Energy household forecast with ANN for demand response and demand side management

Author keywords

ANN; Demand response; Demand side management; Energy; Forecast; Household

Indexed keywords


EID: 85013022550     PISSN: None     EISSN: 2172038X     Source Type: Journal    
DOI: 10.24084/repqj14.559     Document Type: Article
Times cited : (4)

References (12)
  • 2
    • 84923412468 scopus 로고    scopus 로고
    • The daily and hourly energy consumption and load forecasting using artificial neural network method: A case study using a set of 93 households in Portugal
    • F. Rodrigues, C. Cardeira, and J.M.F. Calado, “The daily and hourly energy consumption and load forecasting using artificial neural network method: a case study using a set of 93 households in Portugal”, Energy Procedia, vol. 62, pp. 220–229, 2014.
    • (2014) Energy Procedia , vol.62 , pp. 220-229
    • Rodrigues, F.1    Cardeira, C.2    Calado, J.M.F.3
  • 3
    • 0242306123 scopus 로고    scopus 로고
    • Prediction of the time of room air temperature descending for heating systems in buildings
    • I.H. Yang, and K.W. Kim, “Prediction of the time of room air temperature descending for heating systems in buildings”, Building and Environment, vol. 39, pp. 19–29, 2004.
    • (2004) Building and Environment , vol.39 , pp. 19-29
    • Yang, I.H.1    Kim, K.W.2
  • 4
    • 85072211071 scopus 로고    scopus 로고
    • Demand side management. End-use metering campaign in 400 households of the European Community
    • Project Eureco, “Demand side management. End-use metering campaign in 400 households of the European Community”, in: SAVE Programme, Commission of the European Communities, 2002.
    • (2002) SAVE Programme, Commission of the European Communities
  • 5
    • 2942647905 scopus 로고    scopus 로고
    • A hierarchical neural model in short-term load forecasting
    • O. Carpinteiro, A. Reis, and A. Silva, “A hierarchical neural model in short-term load forecasting”, Applied Soft Computing, vol. 4, pp. 405-412, 2004.
    • (2004) Applied Soft Computing , vol.4 , pp. 405-412
    • Carpinteiro, O.1    Reis, A.2    Silva, A.3
  • 6
    • 0023563676 scopus 로고
    • Short-term load forecasting
    • G. Gross, and F. Galiana, “Short-term load forecasting”, Proceedings of IEEE, vol. 75, pp. 1558-1573, 1987.
    • (1987) Proceedings of IEEE , vol.75 , pp. 1558-1573
    • Gross, G.1    Galiana, F.2
  • 7
    • 84856296455 scopus 로고    scopus 로고
    • Short-term load forecasting with exponentially weighted methods
    • J. Taylor, “Short-term load forecasting with exponentially weighted methods”, IEEE Transactions on Power Systems, vol. 27, pp. 458-464, 2012.
    • (2012) IEEE Transactions on Power Systems , vol.27 , pp. 458-464
    • Taylor, J.1
  • 9
    • 0036756215 scopus 로고    scopus 로고
    • Artificial neural network based peak load forecasting using Levenberg-Marquardt and quasi-Newton methods”, in: IEEE Generation
    • L. Saini, and M. Soni, “Artificial neural network based peak load forecasting using Levenberg-Marquardt and quasi-Newton methods”, in: IEEE Generation, Transmission and Distribution, vol. 149, 578-584, 2002.
    • (2002) Transmission and Distribution , vol.149 , pp. 578-584
    • Saini, L.1    Soni, M.2
  • 10
    • 0035248045 scopus 로고    scopus 로고
    • Neural networks for short-term load forecasting: A review and evaluation
    • H. Hippert, C. Pedreira, and R. Souza, “Neural networks for short-term load forecasting: a review and evaluation”, IEEE Transactions on Power Systems, vol. 16, pp. 44-55, 2001.
    • (2001) IEEE Transactions on Power Systems , vol.16 , pp. 44-55
    • Hippert, H.1    Pedreira, C.2    Souza, R.3
  • 11
    • 84988463773 scopus 로고    scopus 로고
    • Artificial neural networks application to boolean input systems control
    • W. Holderbaum, R. Canart, and P. Borne, “Artificial neural networks application to boolean input systems control”, Studies in Informatics and Control, vol. 8, pp. 107-120, 1999.
    • (1999) Studies in Informatics and Control , vol.8 , pp. 107-120
    • Holderbaum, W.1    Canart, R.2    Borne, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.