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Optimisation of energy management in commercial buildings with weather forecasting inputs: A review

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  1. Azuatalam, Donald & Paridari, Kaveh & Ma, Yiju & Förstl, Markus & Chapman, Archie C. & Verbič, Gregor, 2019. "Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 555-570.
  2. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  3. Eva Lucas Segarra & Germán Ramos Ruiz & Vicente Gutiérrez González & Antonis Peppas & Carlos Fernández Bandera, 2020. "Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
  4. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
  5. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
  6. Mohammad Navid Fekri & Ananda Mohon Ghosh & Katarina Grolinger, 2019. "Generating Energy Data for Machine Learning with Recurrent Generative Adversarial Networks," Energies, MDPI, vol. 13(1), pages 1-23, December.
  7. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
  8. Thomas Schmitt & Tobias Rodemann & Jürgen Adamy, 2021. "The Cost of Photovoltaic Forecasting Errors in Microgrid Control with Peak Pricing," Energies, MDPI, vol. 14(9), pages 1-13, April.
  9. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
  10. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Nor, Khalil M.D. & Khoshnoudi, Masoumeh, 2016. "Using fuzzy multiple criteria decision making approaches for evaluating energy saving technologies and solutions in five star hotels: A new hierarchical framework," Energy, Elsevier, vol. 117(P1), pages 131-148.
  11. Chmielewski, Adrian & Gumiński, Robert & Mączak, Jędrzej & Radkowski, Stanisław & Szulim, Przemysław, 2016. "Aspects of balanced development of RES and distributed micro-cogeneration use in Poland: Case study of a µCHP with Stirling engine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 930-952.
  12. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2018. "Predictive management of cogeneration-based energy supply networks using two-stage multi-objective optimization," Energy, Elsevier, vol. 162(C), pages 1269-1286.
  13. Zhang, Liang & Wen, Jin & Li, Yanfei & Chen, Jianli & Ye, Yunyang & Fu, Yangyang & Livingood, William, 2021. "A review of machine learning in building load prediction," Applied Energy, Elsevier, vol. 285(C).
  14. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei & Aki, Hirohisa, 2016. "Operation management of residential energy-supplying networks based on optimization approaches," Applied Energy, Elsevier, vol. 183(C), pages 340-357.
  15. James Allen & Ari Halberstadt & John Powers & Nael H. El-Farra, 2020. "An Optimization-Based Supervisory Control and Coordination Approach for Solar-Load Balancing in Building Energy Management," Mathematics, MDPI, vol. 8(8), pages 1-28, July.
  16. Haoran Zhao & Sen Guo, 2021. "Uncertain Interval Forecasting for Combined Electricity-Heat-Cooling-Gas Loads in the Integrated Energy System Based on Multi-Task Learning and Multi-Kernel Extreme Learning Machine," Mathematics, MDPI, vol. 9(14), pages 1-32, July.
  17. Rong, Aiying & Lahdelma, Risto, 2016. "Role of polygeneration in sustainable energy system development challenges and opportunities from optimization viewpoints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 363-372.
  18. Yildiz, B. & Bilbao, J.I. & Sproul, A.B., 2017. "A review and analysis of regression and machine learning models on commercial building electricity load forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1104-1122.
  19. Buttitta, Giuseppina & Jones, Colin N. & Finn, Donal P., 2021. "Evaluation of advanced control strategies of electric thermal storage systems in residential building stock," Utilities Policy, Elsevier, vol. 69(C).
  20. Franco, Alessandro & Versace, Michele, 2017. "Optimum sizing and operational strategy of CHP plant for district heating based on the use of composite indicators," Energy, Elsevier, vol. 124(C), pages 258-271.
  21. Kohlhepp, Peter & Harb, Hassan & Wolisz, Henryk & Waczowicz, Simon & Müller, Dirk & Hagenmeyer, Veit, 2019. "Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 527-547.
  22. Chen, Yibo & Tan, Hongwei, 2017. "Short-term prediction of electric demand in building sector via hybrid support vector regression," Applied Energy, Elsevier, vol. 204(C), pages 1363-1374.
  23. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
  24. Shimoda, Yoshiyuki & Yamaguchi, Yohei & Iwafune, Yumiko & Hidaka, Kazuyoshi & Meier, Alan & Yagita, Yoshie & Kawamoto, Hisaki & Nishikiori, Soichi, 2020. "Energy demand science for a decarbonized society in the context of the residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  25. Erdener, Burcin Cakir & Feng, Cong & Doubleday, Kate & Florita, Anthony & Hodge, Bri-Mathias, 2022. "A review of behind-the-meter solar forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  26. Işık, Erdem & Inallı, Mustafa, 2018. "Artificial neural networks and adaptive neuro-fuzzy inference systems approaches to forecast the meteorological data for HVAC: The case of cities for Turkey," Energy, Elsevier, vol. 154(C), pages 7-16.
  27. van der Meer, D.W. & Widén, J. & Munkhammar, J., 2018. "Review on probabilistic forecasting of photovoltaic power production and electricity consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1484-1512.
  28. Gabaldón, A. & García-Garre, A. & Ruiz-Abellón, M.C. & Guillamón, A. & Álvarez-Bel, C. & Fernandez-Jimenez, L.A., 2021. "Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models," Utilities Policy, Elsevier, vol. 70(C).
  29. Eva Lucas Segarra & Hu Du & Germán Ramos Ruiz & Carlos Fernández Bandera, 2019. "Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models," Energies, MDPI, vol. 12(7), pages 1-16, April.
  30. Mat Daut, Mohammad Azhar & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Abdullah, Md Pauzi & Hussin, Faridah, 2017. "Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1108-1118.
  31. Dimitris Lazos & Merlinde Kay & Alistair Sproul, 2016. "Development of a Numerical Weather Analysis Tool for Assessing the Precooling Potential at Any Location," Energies, MDPI, vol. 10(1), pages 1-19, December.
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