Investigation on transient energy consumption of cold storages: Modeling and a case study
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DOI: 10.1016/j.energy.2019.04.217
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- Harish, V.S.K.V. & Kumar, Arun, 2016. "A review on modeling and simulation of building energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1272-1292.
- Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
- Roth, Jonathan & Rajagopal, Ram, 2018. "Benchmarking building energy efficiency using quantile regression," Energy, Elsevier, vol. 152(C), pages 866-876.
- Dorotić, Hrvoje & Pukšec, Tomislav & Duić, Neven, 2019. "Multi-objective optimization of district heating and cooling systems for a one-year time horizon," Energy, Elsevier, vol. 169(C), pages 319-328.
- Chen, Yixing & Hong, Tianzhen & Piette, Mary Ann, 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis," Applied Energy, Elsevier, vol. 205(C), pages 323-335.
- Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
- Fuchs, Marcus & Teichmann, Jens & Lauster, Moritz & Remmen, Peter & Streblow, Rita & Müller, Dirk, 2016. "Workflow automation for combined modeling of buildings and district energy systems," Energy, Elsevier, vol. 117(P2), pages 478-484.
- Amber, K.P. & Ahmad, R. & Aslam, M.W. & Kousar, A. & Usman, M. & Khan, M.S., 2018. "Intelligent techniques for forecasting electricity consumption of buildings," Energy, Elsevier, vol. 157(C), pages 886-893.
- Lee, Sang Hoon & Hong, Tianzhen & Piette, Mary Ann & Taylor-Lange, Sarah C., 2015. "Energy retrofit analysis toolkits for commercial buildings: A review," Energy, Elsevier, vol. 89(C), pages 1087-1100.
- Deng, S. & Wang, R.Z. & Dai, Y.J., 2014. "How to evaluate performance of net zero energy building – A literature research," Energy, Elsevier, vol. 71(C), pages 1-16.
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- Wang, Xiaoyu & Tian, Shuai & Ren, Jiawen & Jin, Xing & Zhou, Xin & Shi, Xing, 2024. "A novel resistance-capacitance model for evaluating urban building energy loads considering construction boundary heterogeneity," Applied Energy, Elsevier, vol. 361(C).
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Keywords
Thermal modeling; Transient energy consumption; Model calibration; Cold storage;All these keywords.
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