메뉴 건너뛰기




Volumn 112, Issue , 2016, Pages 222-233

Energy forecasting for event venues: Big data and prediction accuracy

Author keywords

Big Data; Energy forecasting; Energy prediction; Machine learning; Sensor based forecasting; Smart meters

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORECASTING; LEARNING SYSTEMS; OFFICE BUILDINGS; SMART METERS;

EID: 84951309793     PISSN: 03787788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enbuild.2015.12.010     Document Type: Article
Times cited : (137)

References (33)
  • 1
    • 84922420765 scopus 로고    scopus 로고
    • Department of Energy, US Department of Energy
    • Department of Energy, US Department of Energy, "Green Button." http://energy.gov/data/green-button.
    • Green Button
  • 5
  • 6
    • 67649921626 scopus 로고    scopus 로고
    • Improving efficiency in ice hockey arenas
    • P.L. Nichols Improving efficiency in ice hockey arenas ASHRAE Journal 2009
    • (2009) ASHRAE Journal
    • Nichols, P.L.1
  • 7
    • 84928419830 scopus 로고    scopus 로고
    • Mid-Term Interval Load Forecasting using Multi-Output Support Vector Regression with a Memetic Algorithm for Feature Selection
    • Z. Hu, Y. Bao, R. Chiong, and T. Xiong Mid-Term Interval Load Forecasting using Multi-Output Support Vector Regression with a Memetic Algorithm for Feature Selection Energy 84 2015 419 431
    • (2015) Energy , vol.84 , pp. 419-431
    • Hu, Z.1    Bao, Y.2    Chiong, R.3    Xiong, T.4
  • 8
    • 85027927176 scopus 로고    scopus 로고
    • Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities
    • F.L. Quilumba, W. Lee, H. Huang, D.Y. Wang, and R.L. Szabados Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities IEEE Transactions on Smart Grid 6 2 2015 911 918
    • (2015) IEEE Transactions on Smart Grid , vol.6 , Issue.2 , pp. 911-918
    • Quilumba, F.L.1    Lee, W.2    Huang, H.3    Wang, D.Y.4    Szabados, R.L.5
  • 9
    • 84951281228 scopus 로고    scopus 로고
    • Independent Electricity System Operator (IESO) Independent Electricity System Operator (IESO)
    • Independent Electricity System Operator (IESO) Independent Electricity System Operator (IESO), "Electricity Pricing in Ontario, Large Electricity Consumers." http://www.ieso.ca/Pages/Ontario's-Power-System/Electricity-Pricing-in-Ontario/Large-Electricity-Consumers.aspx
    • Electricity Pricing in Ontario, Large Electricity Consumers
  • 10
    • 84894583621 scopus 로고    scopus 로고
    • Development and Validation of a Gray Box Model to Predict Thermal Behavior of Occupied Office Buildings
    • T. Berthou, P. Stabat, R. Salvazet, and D. Marchio Development and Validation of a Gray Box Model to Predict Thermal Behavior of Occupied Office Buildings Energy and Buildings 74 2014 91 100
    • (2014) Energy and Buildings , vol.74 , pp. 91-100
    • Berthou, T.1    Stabat, P.2    Salvazet, R.3    Marchio, D.4
  • 11
    • 84896085639 scopus 로고    scopus 로고
    • Forecasting Energy Consumption of Multi-Family Residential Buildings using Support Vector Regression: Investigating the Impact of Temporal and Spatial Monitoring Granularity on Performance Accuracy
    • R.K. Jain, K.M. Smith, P.J. Culligan, and J.E. Taylor Forecasting Energy Consumption of Multi-Family Residential Buildings using Support Vector Regression: Investigating the Impact of Temporal and Spatial Monitoring Granularity on Performance Accuracy Applied Energy 123 2014 168 178
    • (2014) Applied Energy , vol.123 , pp. 168-178
    • Jain, R.K.1    Smith, K.M.2    Culligan, P.J.3    Taylor, J.E.4
  • 12
    • 77957308800 scopus 로고    scopus 로고
    • Modeling and Prediction of Turkey's Electricity Consumption using Support Vector Regression
    • K. Kavaklioglu Modeling and Prediction of Turkey's Electricity Consumption using Support Vector Regression Applied Energy 88 1 2011 368 375
    • (2011) Applied Energy , vol.88 , Issue.1 , pp. 368-375
    • Kavaklioglu, K.1
  • 13
    • 84861822310 scopus 로고    scopus 로고
    • Multiple Regression Models to Predict the Annual Energy Consumption in the Spanish Banking Sector
    • A. Aranda, G. Ferreira, M. Mainar-Toledo, S. Scarpellini, and E. Sastresa Multiple Regression Models to Predict the Annual Energy Consumption in the Spanish Banking Sector Energy and Buildings 49 2012 380 387
    • (2012) Energy and Buildings , vol.49 , pp. 380-387
    • Aranda, A.1    Ferreira, G.2    Mainar-Toledo, M.3    Scarpellini, S.4    Sastresa, E.5
  • 14
    • 84876346648 scopus 로고    scopus 로고
    • Modeling of the Energy Demand of the Residential Sector in the United States using Regression Models and Artificial Neural Networks
    • A. Kialashaki, and J. Reisel Modeling of the Energy Demand of the Residential Sector in the United States using Regression Models and Artificial Neural Networks Applied Energy 108 2013 271 280
    • (2013) Applied Energy , vol.108 , pp. 271-280
    • Kialashaki, A.1    Reisel, J.2
  • 15
    • 84898955375 scopus 로고    scopus 로고
    • Statistical Modeling of the Building Energy Balance Variable for Screening of Metered Energy Use in Large Commercial Buildings
    • H. Masuda, and D.E. Claridge Statistical Modeling of the Building Energy Balance Variable for Screening of Metered Energy Use in Large Commercial Buildings Energy and Buildings 77 2014 292 303
    • (2014) Energy and Buildings , vol.77 , pp. 292-303
    • Masuda, H.1    Claridge, D.E.2
  • 17
    • 84899701114 scopus 로고    scopus 로고
    • Development of Prediction Models for Next-Day Building Energy Consumption and Peak Power Demand using Data Mining Techniques
    • C. Fan, F. Xiao, and S. Wang Development of Prediction Models for Next-Day Building Energy Consumption and Peak Power Demand using Data Mining Techniques Applied Energy 127 2014 1 10
    • (2014) Applied Energy , vol.127 , pp. 1-10
    • Fan, C.1    Xiao, F.2    Wang, S.3
  • 18
    • 84922822619 scopus 로고    scopus 로고
    • Hourly Prediction of a Building's Electricity Consumption using Case-Based Reasoning, Artificial Neural Networks and Principal Component Analysis
    • R. Platon, V. Dehkordi, and J. Martel Hourly Prediction of a Building's Electricity Consumption using Case-Based Reasoning, Artificial Neural Networks and Principal Component Analysis Energy and Buildings 92 2015 10 18
    • (2015) Energy and Buildings , vol.92 , pp. 10-18
    • Platon, R.1    Dehkordi, V.2    Martel, J.3
  • 19
    • 84923378659 scopus 로고    scopus 로고
    • Short-Term Load Forecasting in a Non-Residential Building Contrasting Models and Attributes
    • J. Massana, C. Pous, L. Burgas, J. Melendez, and J. Colomer Short-Term Load Forecasting in a Non-Residential Building Contrasting Models and Attributes Energy and Buildings 92 2015 322 330
    • (2015) Energy and Buildings , vol.92 , pp. 322-330
    • Massana, J.1    Pous, C.2    Burgas, L.3    Melendez, J.4    Colomer, J.5
  • 20
    • 84924909991 scopus 로고    scopus 로고
    • A Hybrid Short-Term Load Forecasting with a New Input Selection Framework
    • M. Ghofrani, M. Ghayekhloo, A. Arabali, and A. Ghayekhloo A Hybrid Short-Term Load Forecasting with a New Input Selection Framework Energy 81 2015 777 786
    • (2015) Energy , vol.81 , pp. 777-786
    • Ghofrani, M.1    Ghayekhloo, M.2    Arabali, A.3    Ghayekhloo, A.4
  • 21
    • 84893024652 scopus 로고    scopus 로고
    • Long-Term Electrical Energy Consumption Forecasting for Developing and Developed Economies Based on Different Optimized Models and Historical Data Types
    • F. Ardakani, and M. Ardehali Long-Term Electrical Energy Consumption Forecasting for Developing and Developed Economies Based on Different Optimized Models and Historical Data Types Energy 65 2014 452 461
    • (2014) Energy , vol.65 , pp. 452-461
    • Ardakani, F.1    Ardehali, M.2
  • 22
    • 84924565263 scopus 로고    scopus 로고
    • Short-Term Smart Learning Electrical Load Prediction Algorithm for Home Energy Management Systems
    • W. El-Baz, and P. Tzscheutschler Short-Term Smart Learning Electrical Load Prediction Algorithm for Home Energy Management Systems Applied Energy 147 2015 10 19
    • (2015) Applied Energy , vol.147 , pp. 10-19
    • El-Baz, W.1    Tzscheutschler, P.2
  • 23
    • 84919935314 scopus 로고    scopus 로고
    • A Variance Inflation Factor and Backward Elimination Based Robust Regression Model for Forecasting Monthly Electricity Demand using Climatic Variables
    • D. Vu, K. Muttaqi, and A. Agalgaonkar A Variance Inflation Factor and Backward Elimination Based Robust Regression Model for Forecasting Monthly Electricity Demand using Climatic Variables Applied Energy 140 2015 385 394
    • (2015) Applied Energy , vol.140 , pp. 385-394
    • Vu, D.1    Muttaqi, K.2    Agalgaonkar, A.3
  • 25
    • 34250170125 scopus 로고    scopus 로고
    • Predicting Electricity Energy Consumption: A Comparison of Regression Analysis, Decision Tree and Neural Networks
    • G.K.F. Tso, and K.K.W. Yau Predicting Electricity Energy Consumption: A Comparison of Regression Analysis, Decision Tree and Neural Networks Energy 32 9 2007 1761 1768
    • (2007) Energy , vol.32 , Issue.9 , pp. 1761-1768
    • Tso, G.K.F.1    Yau, K.K.W.2
  • 27
    • 84925182116 scopus 로고    scopus 로고
    • Ensemble of Various Neural Networks for Prediction of Heating Energy Consumption
    • R.Ž. Jovanović, A.A. Sretenović, and B.D. Živković Ensemble of Various Neural Networks for Prediction of Heating Energy Consumption Energy and Buildings 94 2015 189 199
    • (2015) Energy and Buildings , vol.94 , pp. 189-199
    • Jovanović, R.Ž.1    Sretenović, A.A.2    Živković, B.D.3
  • 29
    • 84861802647 scopus 로고    scopus 로고
    • Predicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study
    • R. Edwards, J. New, and L. Parker Predicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study Energy and Buildings 49 2012 591 603
    • (2012) Energy and Buildings , vol.49 , pp. 591-603
    • Edwards, R.1    New, J.2    Parker, L.3
  • 30
    • 84857652807 scopus 로고    scopus 로고
    • On the use of Cross-Validation for Time Series Predictor Evaluation
    • C. Bergmeir, and J.M. Benítez On the use of Cross-Validation for Time Series Predictor Evaluation Information Sciences 191 2012 192 213
    • (2012) Information Sciences , vol.191 , pp. 192-213
    • Bergmeir, C.1    Benítez, J.M.2
  • 32
    • 84907570987 scopus 로고    scopus 로고
    • Neural Network Model Ensembles for Building-Level Electricity Load Forecasts
    • J. Jetcheva, M. Majidpour, and W. Chen Neural Network Model Ensembles for Building-Level Electricity Load Forecasts Energy and Buildings 84 2014 214 223
    • (2014) Energy and Buildings , vol.84 , pp. 214-223
    • Jetcheva, J.1    Majidpour, M.2    Chen, W.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.