@article{jin_prediction-based_2005,
	title = {Prediction-based online optimal control of outdoor air of multi-zone {VAV} air conditioning systems},
	volume = {37},
	issn = {0378-7788},
	url = {http://www.sciencedirect.com/science/article/pii/S0378778805000058},
	doi = {10.1016/j.enbuild.2004.11.011},
	abstract = {An optimal strategy for outdoor air control is developed using a system approach based on prediction to minimize energy consumption. ARMA model is used to predict the energy performance which is expressed by an energy-increment equation. The energy-increment equation is formed to involve the real-time variations of AHU load and energy use of reheaters of VAV terminals. To minimize the Energy-increment equation by genetic algorithm, the optimal settings of outdoor air ratio of AHU and reheating could be obtained. The strategy is tested and evaluated in a simulated environment under various outdoor and indoor conditions.},
	number = {9},
	urldate = {2018-02-08},
	journal = {Energy and Buildings},
	author = {Jin, Xinqiao and Ren, Haigang and Xiao, Xiaokun},
	month = sep,
	year = {2005},
	keywords = {Energy-Increment equation, Outdoor air control, VAV air conditioning systems},
	pages = {939--944},
}

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