A stochastic chiller optimization operation strategy based on uncertainty analysis. (February 2019)
- Record Type:
- Journal Article
- Title:
- A stochastic chiller optimization operation strategy based on uncertainty analysis. (February 2019)
- Main Title:
- A stochastic chiller optimization operation strategy based on uncertainty analysis
- Authors:
- Qiu, Shunian
Zhang, Weijie
Feng, Fan
Li, Zhengwei
Li, Zhenhai - Abstract:
- Abstract: Deterministic chiller optimization control strategies, such as COP optimization strategy, are intended to save energy based on deterministic sensor measuring data and equipment characteristics. However, the sensor data and the equipment characteristics are typically uncertain due to poor calibration of sensors, poor maintenance of chillers, etc., which could harm the energy-saving performance of deterministic chiller optimization operation strategies. In order to tackle this problem, a stochastic chiller optimization operation strategy based on uncertainty analysis is proposed in this paper. The strategy consists of three steps: (1) Analyze the uncertainty of the HVAC system and specify the probability distribution of each uncertain parameter. (2) Calculate the mathematical expectation value of energy consumption and return chilled water temperature in each operation plan under uncertainty. (3) Select the operation plan with the least energy consumption expectation and limited return chilled water temperature. The performance of the proposed strategy is validated on TRNSYS with measured hourly cooling load data of an office building located in Shanghai. Compared with the deterministic optimized operation strategy, the proposed stochastic strategy performs better on robustness (i.e., keeping return chilled water temperature within safe criteria) because of the consideration of measurement uncertainty. Also, compared with traditional operation strategy withoutAbstract: Deterministic chiller optimization control strategies, such as COP optimization strategy, are intended to save energy based on deterministic sensor measuring data and equipment characteristics. However, the sensor data and the equipment characteristics are typically uncertain due to poor calibration of sensors, poor maintenance of chillers, etc., which could harm the energy-saving performance of deterministic chiller optimization operation strategies. In order to tackle this problem, a stochastic chiller optimization operation strategy based on uncertainty analysis is proposed in this paper. The strategy consists of three steps: (1) Analyze the uncertainty of the HVAC system and specify the probability distribution of each uncertain parameter. (2) Calculate the mathematical expectation value of energy consumption and return chilled water temperature in each operation plan under uncertainty. (3) Select the operation plan with the least energy consumption expectation and limited return chilled water temperature. The performance of the proposed strategy is validated on TRNSYS with measured hourly cooling load data of an office building located in Shanghai. Compared with the deterministic optimized operation strategy, the proposed stochastic strategy performs better on robustness (i.e., keeping return chilled water temperature within safe criteria) because of the consideration of measurement uncertainty. Also, compared with traditional operation strategy without optimization, the proposed strategy performs better on saving energy … (more)
- Is Part Of:
- IOP conference series. Volume 238(2019)
- Journal:
- IOP conference series
- Issue:
- Volume 238(2019)
- Issue Display:
- Volume 238, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 238
- Issue:
- 2019
- Issue Sort Value:
- 2019-0238-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-02
- Subjects:
- Earth sciences -- Periodicals
Environmental sciences -- Congresses
Environmental sciences -- Periodicals
550.5 - Journal URLs:
- http://iopscience.iop.org/1755-1315 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1755-1315/238/1/012023 ↗
- Languages:
- English
- ISSNs:
- 1755-1307
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4565.243000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9845.xml