A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm

This study proposes a global optimized operation strategy to reduce energy consumption of a liquid desiccant air conditioning (LDAC) driven by chiller and electric heater. Energy models of chiller, electric heater, pumps and fans are developed to predict their energy consumptions under different ope...

Full description

Saved in:
Bibliographic Details
Main Authors: Wang, Xinli, Cai, Wenjian, Yin, Xiaohong
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2017
Subjects:
Online Access:https://hdl.handle.net/10356/84993
http://hdl.handle.net/10220/42070
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-84993
record_format dspace
spelling sg-ntu-dr.10356-849932020-03-07T13:57:23Z A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm Wang, Xinli Cai, Wenjian Yin, Xiaohong School of Electrical and Electronic Engineering Energy conservation Liquid desiccant air conditioner This study proposes a global optimized operation strategy to reduce energy consumption of a liquid desiccant air conditioning (LDAC) driven by chiller and electric heater. Energy models of chiller, electric heater, pumps and fans are developed to predict their energy consumptions under different operating conditions with different control settings. Heat transfer models of cooling heat exchanger, heating heat exchanger and recovery heat exchanger are established to analyze the heat transfer processes in these components. An optimization problem considering system constraints and interactions between components is built to optimize the energy usage of the whole liquid desiccant air conditioning and simultaneously maintaining the required indoor air quality (IAQ) level. Nine controllable variables related to the performance and energy usage of LDAC are selected as control settings. Self-adaptive differential evolutionary (SADE) algorithm with fast convergence rate is employed to solve the optimization problem to obtain optimal control settings and to develop optimal operation strategies. Compare study is carried out on a fabricated testing facility to show the energy saving performance of the proposed global optimized operation strategy. Compared with the conventional strategy, 18.5% energy saving can be achieved by using the proposed global optimized operation strategy. The proposed global optimized operation strategy is a valid operation strategy that is suitable for application in energy reduction of the existing LDAC system in building. NRF (Natl Research Foundation, S’pore) Accepted version 2017-02-03T08:41:53Z 2019-12-06T15:55:04Z 2017-02-03T08:41:53Z 2019-12-06T15:55:04Z 2017 Journal Article Wang, X., Cai, W., & Yin, X. (2017). A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm. Applied Energy, 187, 410-423. 0306-2619 https://hdl.handle.net/10356/84993 http://hdl.handle.net/10220/42070 10.1016/j.apenergy.2016.11.073 en Applied Energy © 2016 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Applied Energy, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.apenergy.2016.11.073]. 40 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Energy conservation
Liquid desiccant air conditioner
spellingShingle Energy conservation
Liquid desiccant air conditioner
Wang, Xinli
Cai, Wenjian
Yin, Xiaohong
A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
description This study proposes a global optimized operation strategy to reduce energy consumption of a liquid desiccant air conditioning (LDAC) driven by chiller and electric heater. Energy models of chiller, electric heater, pumps and fans are developed to predict their energy consumptions under different operating conditions with different control settings. Heat transfer models of cooling heat exchanger, heating heat exchanger and recovery heat exchanger are established to analyze the heat transfer processes in these components. An optimization problem considering system constraints and interactions between components is built to optimize the energy usage of the whole liquid desiccant air conditioning and simultaneously maintaining the required indoor air quality (IAQ) level. Nine controllable variables related to the performance and energy usage of LDAC are selected as control settings. Self-adaptive differential evolutionary (SADE) algorithm with fast convergence rate is employed to solve the optimization problem to obtain optimal control settings and to develop optimal operation strategies. Compare study is carried out on a fabricated testing facility to show the energy saving performance of the proposed global optimized operation strategy. Compared with the conventional strategy, 18.5% energy saving can be achieved by using the proposed global optimized operation strategy. The proposed global optimized operation strategy is a valid operation strategy that is suitable for application in energy reduction of the existing LDAC system in building.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Wang, Xinli
Cai, Wenjian
Yin, Xiaohong
format Article
author Wang, Xinli
Cai, Wenjian
Yin, Xiaohong
author_sort Wang, Xinli
title A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
title_short A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
title_full A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
title_fullStr A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
title_full_unstemmed A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
title_sort global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm
publishDate 2017
url https://hdl.handle.net/10356/84993
http://hdl.handle.net/10220/42070
_version_ 1681043761883250688