Multiplexed optimization for complex air conditioning systems

Sun, Yongjun; Huang, Gongsheng; Wang, Shengwei

doi:10.1016/j.buildenv.2013.03.024

Cited by 30 publications

(9 citation statements)

References 19 publications

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“…When Tw,set changes, the mean cooling capacity over the on time during on/off cycling period, ̂H P , will change, which affects the length of the heat pump operating time as shown in Eq. (6). Therefore, the relationship between ̂H P…”

Section: Constraints Of Optimizationmentioning

confidence: 99%

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

Gao

Huang

2016

Energy Conversion and Management

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This paper studies the optimization of a small-scale central airconditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.

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Section: Constraints Of Optimizationmentioning

confidence: 99%

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

Gao

Huang

2016

Energy Conversion and Management

Self Cite

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“…Furthermore, there are several alternative optimization methods for HVAC systems. Sun et al [33] have proposed a multiplexed optimization scheme for complex air-conditioning systems. He et al [34] have proposed a computational intelligence algorithm based on the performance optimization for the HVAC.…”

Section: Related Workmentioning

confidence: 99%

HVAC Optimal Control with the Multistep-Actor Critic Algorithm in Large Action Spaces

Huang

Chen

et al. 2020

Mathematical Problems in Engineering

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We propose an optimization method, named as the Multistep-Actor Critic (MAC) algorithm, which uses the value-network and the action-network, where the action-network is based on the deep Q-network (DQN). The proposed method is intended to solve the problem of energy conservation optimization of heating, ventilating, and air-conditioning (HVAC) system in a large action space, principally for the cases with high computation and convergence time. The method employs the multistep action-network and search tree to generate the original state and then selects the optimal state based on the value-network for the original and the adjacent states. The results from the application of the MAC algorithm to a simulation problem on the TRNSYS system, where the simulation problem is referring to a real supertall building in Hong Kong, have shown that the proposed MAC algorithm balances control actions between different HVAC subsystems. Further, it substantially saves the computational time while maintaining a good energy conservation performance.

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“…The refrigeration system requires energy input to create cooling by removing heat from a low-temperature reservoir. In this case, optimization has been considered as a significant tool to minimize the required energy and cost as well as maximize the efficiency of industrial refrigeration systems [3], [4]. Zhao et al (2013) developed a model-based optimization technique for VCRS to minimize total operation cost with respect to the constraints of mechanical limitations, component interactions, environment conditions and cooling load demands [5].…”

Section: Introductionmentioning

confidence: 99%

Parametric Optimization of a Two Stage Vapor Compression Refrigeration System by Comparative Evolutionary Techniques

Mahadzir

Ahmed

2021

E3S Web Conf.

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Multistage refrigeration system plays a vital role in industrial refrigeration for the chemical, petrochemical, pharmaceuticals and food industries. Modern chemical industries are complex, and the problems are commonly multi-dimensional, non-linear and time-consuming. This study presents the application of evolutionary computation techniques, namely PSO (particle swarm optimization), GA (Genetic Algorithm) and SA (Simulated Annealing) to solve a design problem of a two-stage vapor compression refrigeration system. Two objectives are evaluated, namely the minimization of total energy consumption and maximization of the coefficient of performance (COP) of the system. The basis of design for the two-stage refrigeration system is built from and validated against data from published literature. The mass flow ratio, evaporator and condenser temperature, parameters for subcooling and desuperheating, and the coefficient of performance for the basis of design show acceptable results. The errors are below 5% against the data from published literature, which are within errors of significant figures in the calculations. In this work, the optimum solutions show a reduction of the required amount of energy consumption by 30.8% and an increase of the COP by nearly 77% with respect to the basis of design. Further improvements are made to the optimization procedures to prevent early convergence and to increase the search efficiency for finding the global optima. The findings by PSO, GA and SA are in agreement, and all evolutionary techniques achieved proper convergence of the two objective functions. It is also found that PSO requires lower computational effort, less computation time and is also easier to implement compared to GA and SA.

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Multiplexed optimization for complex air conditioning systems

Cited by 30 publications

References 19 publications

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

An optimization strategy for the control of small capacity heat pump integrated air-conditioning system

HVAC Optimal Control with the Multistep-Actor Critic Algorithm in Large Action Spaces

Parametric Optimization of a Two Stage Vapor Compression Refrigeration System by Comparative Evolutionary Techniques

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