HVAC system optimization––condenser water loop

Lu, Lu; Cai, Wenjian; Soh, Yeng Chai; Xie, Lihua; Li, Shujiang

doi:10.1016/s0196-8904(03)00181-x

Cited by 111 publications

(52 citation statements)

References 6 publications

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“…However, energy efficiency will be affected by the increasing/decreasing cooling water return temperature, while reducing this temperature will result in an improved COP [43][44][45][46]. In this section the models to assess the COP for electric chillers will be predicted.…”

Section: Data Modeling Preprocessingmentioning

confidence: 99%

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

et al. 2018

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Abstract:Optimal operation is an important aspect of energy efficiency that can be employed to reduce power consumption. In cooling systems, the chillers consume a large amount of electricity, especially if they are not optimally operated, therefore, they cannot produce the required or rated cooling load capacity. The objective of this paper is to improve coefficient of performance (COP) for the operation of chillers and to reduce power consumption. Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. Particularly, in contribution (1), two models are developed to predict/assess power consumption and cooling load capacity. While in contribution (2), the predictive model's data obtained are used to classify the operating performance of the chiller and to optimize the model in order to reduce power consumption and cooling capacity. Therefore, data classification by APSO is used to enhance the coefficient of performance (COP). The proposed technique reduces the total power consumption by 33.2% and meets the cooling demand requirements. Also, it improves the cooling performance based on COP, thus resulting in a 15.95% increase in efficiency compared to the existing cooling system. The studied ANFIS-based FCS outperforms the ANFIS-based fuzzy C-means clustering in terms of the regression. Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). The data was acquired from the District Cooling System (DCS) at the Universiti Teknologi Petronas (UTP) campus in Malaysia.

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Section: Data Modeling Preprocessingmentioning

confidence: 99%

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

et al. 2018

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“…There are several optimization methods that can effectively address these problems. These methods are the analytical approach [6][7][8][9], direct search method [10], linear quadratic programming [11], nonlinear programming method [12], heuristic optimization algorithm [3,13,14], and artificial neural networks [15]. Kaya et al [6] analysed the influence factors of the effectiveness in pumps and presented an approach for improvement.…”

Section: Introductionmentioning

confidence: 99%

“…Sheng and Duanmu [9] presented electricity consumption and economic analyses. Lu et al [13] and Nassif et al [14] used a genetic algorithm to optimize the models of components in HVAC systems. Fong et al [3] adopted a robust evolutionary algorithm for system optimization.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Dynamical Modelling and Control Approach for Energy Saving of Central Air Conditioning

Yan

Liu

2018

Mathematical Problems in Engineering

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Currently in China, energy conservation and emission reduction are important initiatives for society. Because of its large proportion of building energy consumption, several methods for building energy conservation have been introduced for central air conditioning. This paper presents a hybrid system for a modelling and control approach. By analysing the cooling capacity transfer process and the electromagnetic properties of pumps, the modelling is performed in a hybrid system framework. Pumps are classified as fixed-frequency pumps, variable-frequency pumps, and switchable pumps; a switch control strategy is used in the chilled water system for supplying cooling capacity. In order to adjust indoor temperature and save electrical energy, the cooling capacity allocation and average temperature methods are presented, which satisfy the goal of optimal control of real-time energy consumption. As a numerical example, the temperature variation and cold regulation processes are simulated. Three rooms are the control objects that lower the setting points, and pumps waste as little electrical energy as possible. The results show 49.4% of water pump power consumption when compared with constant water volume technology. The modelling and control approach is more advantageous in ensuring the success of reconstruction projects for central air conditioning.

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“…An increased awareness of these issues has motivated the practitioners in the HVAC (heating, ventilating, and air-conditioning) field to apply the most advanced design philosophies and extensive control strategies for HVAC systems to enhance their energy efficiency and provide robust operational performance. Cooling water systems as the major function components of building HVAC systems, often contribute significant portions to the total energy consumptions of overall HVAC systems [1].…”

Section: Introductionmentioning

confidence: 99%

“…These efforts have resulted in a number of near optimal and optimal control strategies readily available in literature [1][2][3][4][5][6][7]. Among the existing control strategies, two basic strategies are the fixed set-point control method and the fixed approach control method [2,3].…”

Section: Introductionmentioning

confidence: 99%

Online performance evaluation of alternative control strategies for building cooling water systems prior to in situ implementation

Wang

Xiao

2009

Applied Energy

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This paper presents the online test and evaluation of the performance of five practical control strategies (fixed set-point control method, fixed approach control method, two near optimal strategies and one optimal strategy) for building cooling water systems to identify the best strategy for future field validation. All of these strategies were tested and evaluated in a simulated virtual environment similar to the situation when they are actually implemented in practice. A virtual building system representing the real building and its central chilling system was developed and used to test the operational performance of the system controlled by different strategies. The packages of each control strategy are separately computed by the application program of Matlab, as the control optimizers to identify the necessary control settings for the given condition based on the collected operation data. The data exchanger between the virtual building system and the control optimizer was managed by a software platform through a communication interface. The results showed that the optimal control strategy is more energy efficient and cost effective than the other strategies, and its computational cost is manageable and can satisfy the 2 requirements of practical applications. This strategy is being implemented in a super highrise building for field validation.

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HVAC system optimization––condenser water loop

Cited by 111 publications

References 6 publications

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

A Hybrid Dynamical Modelling and Control Approach for Energy Saving of Central Air Conditioning

Online performance evaluation of alternative control strategies for building cooling water systems prior to in situ implementation

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