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Uncertainty estimation improves energy measurement and verification procedures

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  1. Granderson, Jessica & Touzani, Samir & Custodio, Claudine & Sohn, Michael D. & Jump, David & Fernandes, Samuel, 2016. "Accuracy of automated measurement and verification (M&V) techniques for energy savings in commercial buildings," Applied Energy, Elsevier, vol. 173(C), pages 296-308.
  2. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
  3. Granderson, Jessica & Price, Phillip N. & Jump, David & Addy, Nathan & Sohn, Michael D., 2015. "Automated measurement and verification: Performance of public domain whole-building electric baseline models," Applied Energy, Elsevier, vol. 144(C), pages 106-113.
  4. Ziras, Charalampos & Heinrich, Carsten & Pertl, Michael & Bindner, Henrik W., 2019. "Experimental flexibility identification of aggregated residential thermal loads using behind-the-meter data," Applied Energy, Elsevier, vol. 242(C), pages 1407-1421.
  5. Ye, Xianming & Xia, Xiaohua, 2016. "Optimal metering plan for measurement and verification on a lighting case study," Energy, Elsevier, vol. 95(C), pages 580-592.
  6. Yun Duan, 2022. "A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
  7. Fu, Hongxiang & Baltazar, Juan-Carlos & Claridge, David E., 2021. "Review of developments in whole-building statistical energy consumption models for commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
  8. Jacques Maritz & Foster Lubbe & Louis Lagrange, 2018. "A Practical Guide to Gaussian Process Regression for Energy Measurement and Verification within the Bayesian Framework," Energies, MDPI, vol. 11(4), pages 1-12, April.
  9. Smith, Sarah Josephine & Wei, Max & Sohn, Michael D., 2016. "A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs," Energy Policy, Elsevier, vol. 98(C), pages 505-512.
  10. Lu, Zhijian & Shao, Shuai, 2016. "Impacts of government subsidies on pricing and performance level choice in Energy Performance Contracting: A two-step optimal decision model," Applied Energy, Elsevier, vol. 184(C), pages 1176-1183.
  11. Carstens, Herman & Xia, Xiaohua & Yadavalli, Sarma, 2017. "Low-cost energy meter calibration method for measurement and verification," Applied Energy, Elsevier, vol. 188(C), pages 563-575.
  12. Giglio, T. & Santos, V. & Lamberts, R., 2019. "Analyzing the impact of small solar water heating systems on peak demand and on emissions in the Brazilian context," Renewable Energy, Elsevier, vol. 133(C), pages 1404-1413.
  13. Deng, Qianli & Jiang, Xianglin & Cui, Qingbin & Zhang, Limao, 2015. "Strategic design of cost savings guarantee in energy performance contracting under uncertainty," Applied Energy, Elsevier, vol. 139(C), pages 68-80.
  14. Chitalia, Gopal & Pipattanasomporn, Manisa & Garg, Vishal & Rahman, Saifur, 2020. "Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks," Applied Energy, Elsevier, vol. 278(C).
  15. Angeliki Mavrigiannaki & Kostas Gobakis & Dionysia Kolokotsa & Kostas Kalaitzakis & Anna Laura Pisello & Cristina Piselli & Rajat Gupta & Matt Gregg & Marina Laskari & Maria Saliari & Margarita-Niki A, 2020. "Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe," Sustainability, MDPI, vol. 12(22), pages 1-16, November.
  16. Benedetto Grillone & Gerard Mor & Stoyan Danov & Jordi Cipriano & Florencia Lazzari & Andreas Sumper, 2021. "Baseline Energy Use Modeling and Characterization in Tertiary Buildings Using an Interpretable Bayesian Linear Regression Methodology," Energies, MDPI, vol. 14(17), pages 1-30, September.
  17. Xie, Yiwei & Hu, Pingfang & Peng, Donggen & Zhu, Na & Lei, Fei, 2023. "Development of a group control strategy based on multi-step load forecasting and its application in hybrid ground source heat pump," Energy, Elsevier, vol. 273(C).
  18. Ke, Ming-Tsun & Yeh, Chia-Hung & Su, Cheng-Jie, 2017. "Cloud computing platform for real-time measurement and verification of energy performance," Applied Energy, Elsevier, vol. 188(C), pages 497-507.
  19. Liang, Xin & Hong, Tianzhen & Shen, Geoffrey Qiping, 2016. "Improving the accuracy of energy baseline models for commercial buildings with occupancy data," Applied Energy, Elsevier, vol. 179(C), pages 247-260.
  20. Simon Rouchier, 2022. "Bayesian Workflow and Hidden Markov Energy-Signature Model for Measurement and Verification," Energies, MDPI, vol. 15(10), pages 1-19, May.
  21. Cai, Mengmeng & Pipattanasomporn, Manisa & Rahman, Saifur, 2019. "Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques," Applied Energy, Elsevier, vol. 236(C), pages 1078-1088.
  22. Longo, Stefano & d’Antoni, Benedetto Mirko & Bongards, Michael & Chaparro, Antonio & Cronrath, Andreas & Fatone, Francesco & Lema, Juan M. & Mauricio-Iglesias, Miguel & Soares, Ana & Hospido, Almudena, 2016. "Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement," Applied Energy, Elsevier, vol. 179(C), pages 1251-1268.
  23. Xie, Yiwei & Hu, Pingfang & Zhu, Na & Lei, Fei & Xing, Lu & Xu, Linghong & Sun, Qiming, 2020. "A hybrid short-term load forecasting model and its application in ground source heat pump with cooling storage system," Renewable Energy, Elsevier, vol. 161(C), pages 1244-1259.
  24. Lee, P. & Lam, P.T.I. & Lee, W.L. & Chan, E.H.W., 2016. "Analysis of an air-cooled chiller replacement project using a probabilistic approach for energy performance contracts," Applied Energy, Elsevier, vol. 171(C), pages 415-428.
  25. Herman Carstens & Xiaohua Xia & Sarma Yadavalli, 2018. "Bayesian Energy Measurement and Verification Analysis," Energies, MDPI, vol. 11(2), pages 1-20, February.
  26. Mathew, Paul A. & Dunn, Laurel N. & Sohn, Michael D. & Mercado, Andrea & Custudio, Claudine & Walter, Travis, 2015. "Big-data for building energy performance: Lessons from assembling a very large national database of building energy use," Applied Energy, Elsevier, vol. 140(C), pages 85-93.
  27. Olinga, Zadok & Xia, Xiaohua & Ye, Xianming, 2017. "A cost-effective approach to handle measurement and verification uncertainties of energy savings," Energy, Elsevier, vol. 141(C), pages 1600-1609.
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