Optimal Control of Air-Side Economizer
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yu-Jin Kim & Kwang-Hee Kim & Ju-Wan Ha & Young-Hak Song, 2024. "Research on a Plan of Free Cooling Operation Control for the Efficiency Improvement of a Water-Side Economizer," Energies, MDPI, vol. 17(12), pages 1-17, June.
- Li, Qiong & Meng, Qinglin & Cai, Jiejin & Yoshino, Hiroshi & Mochida, Akashi, 2009. "Applying support vector machine to predict hourly cooling load in the building," Applied Energy, Elsevier, vol. 86(10), pages 2249-2256, October.
- Xu, Yuanjin & Li, Fei & Asgari, Armin, 2022. "Prediction and optimization of heating and cooling loads in a residential building based on multi-layer perceptron neural network and different optimization algorithms," Energy, Elsevier, vol. 240(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Gao, Zhikun & Yang, Siyuan & Yu, Junqi & Zhao, Anjun, 2024. "Hybrid forecasting model of building cooling load based on combined neural network," Energy, Elsevier, vol. 297(C).
- Jinrong Wu & Su Nguyen & Damminda Alahakoon & Daswin De Silva & Nishan Mills & Prabod Rathnayaka & Harsha Moraliyage & Andrew Jennings, 2024. "A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types," Energies, MDPI, vol. 17(6), pages 1-18, March.
- Hyo-Jun Kim & Young-Hum Cho, 2021. "Optimal Control Method of Variable Air Volume Terminal Unit System," Energies, MDPI, vol. 14(22), pages 1-15, November.
- Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
- Ahmad, Muhammad Waseem & Mourshed, Monjur & Rezgui, Yacine, 2018. "Tree-based ensemble methods for predicting PV power generation and their comparison with support vector regression," Energy, Elsevier, vol. 164(C), pages 465-474.
- 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.
- Muideen Adegoke & Alaka Hafiz & Saheed Ajayi & Razak Olu-Ajayi, 2022. "Application of Multilayer Extreme Learning Machine for Efficient Building Energy Prediction," Energies, MDPI, vol. 15(24), pages 1-21, December.
- Yuwen You & Zhonghua Wang & Zhihao Liu & Chunmei Guo & Bin Yang, 2024. "Load Prediction of Regional Heat Exchange Station Based on Fuzzy Clustering Based on Fourier Distance and Convolutional Neural Network–Bidirectional Long Short-Term Memory Network," Energies, MDPI, vol. 17(16), pages 1-19, August.
- Ling, Jihong & Zhang, Bingyang & Dai, Na & Xing, Jincheng, 2023. "Coupling input feature construction methods and machine learning algorithms for hourly secondary supply temperature prediction," Energy, Elsevier, vol. 278(C).
- Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
- Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
- Jiang, Ben & Li, Yu & Rezgui, Yacine & Zhang, Chengyu & Wang, Peng & Zhao, Tianyi, 2024. "Multi-source domain generalization deep neural network model for predicting energy consumption in multiple office buildings," Energy, Elsevier, vol. 299(C).
- Jiang, Lai & Yao, Runming & Liu, Kecheng & McCrindle, Rachel, 2017. "An Epistemic-Deontic-Axiologic (EDA) agent-based energy management system in office buildings," Applied Energy, Elsevier, vol. 205(C), pages 440-452.
- Shao, Junqiang & Huang, Zhiyuan & Chen, Yugui & Li, Depeng & Xu, Xiangguo, 2023. "A practical application-oriented model predictive control algorithm for direct expansion (DX) air-conditioning (A/C) systems that balances thermal comfort and energy consumption," Energy, Elsevier, vol. 269(C).
- Afroz, Zakia & Urmee, Tania & Shafiullah, G.M. & Higgins, Gary, 2018. "Real-time prediction model for indoor temperature in a commercial building," Applied Energy, Elsevier, vol. 231(C), pages 29-53.
- Yu, Binbin & Li, Jianjing & Liu, Che & Sun, Bo, 2022. "A novel short-term electrical load forecasting framework with intelligent feature engineering," Applied Energy, Elsevier, vol. 327(C).
- Mohammad Nikoo & Akbar Karimi & Reza Kerachian & Hamed Poorsepahy-Samian & Farhang Daneshmand, 2013. "Rules for Optimal Operation of Reservoir-River-Groundwater Systems Considering Water Quality Targets: Application of M5P Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2771-2784, June.
- Jawed Mustafa & Fahad Awjah Almehmadi & Saeed Alqaed & Mohsen Sharifpur, 2022. "Building a Sustainable Energy Community: Design and Integrate Variable Renewable Energy Systems for Rural Communities," Sustainability, MDPI, vol. 14(21), pages 1-21, October.
- Feng, Yanxiao & Duan, Qiuhua & Chen, Xi & Yakkali, Sai Santosh & Wang, Julian, 2021. "Space cooling energy usage prediction based on utility data for residential buildings using machine learning methods," Applied Energy, Elsevier, vol. 291(C).
- Rackes, Adams & Melo, Ana Paula & Lamberts, Roberto, 2016. "Naturally comfortable and sustainable: Informed design guidance and performance labeling for passive commercial buildings in hot climates," Applied Energy, Elsevier, vol. 174(C), pages 256-274.
More about this item
Keywords
economizer control; air-side economizer; optimal control; prediction model;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5383-:d:1509342. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.