暖通空调系统通用小型DDC温度控制模型设计

针对现有DDC在暖通空调系统中应用存在的不足,在分析暖通空调系统对DDC功能需求的基础上,设计了一系列专门针对暖通空调系统应用的温度控制模型并介绍了相应的算法。     

智能建筑中暖通空调和照明系统的计算机控制系统与策略

以美国一大学建筑物性能测试中心的智能工作区间为例,说明了暖通空调和照明系统的计算机控制系统,以及应用设备和软件流程图,介绍了智能建筑的控制系统结构和控制策略。     

基于MATLAB的空调系统专家PID控制的建模与仿真

以一个典型的空调系统为研究对象,建立了空调房间的简化数学模型,通过MATLAB编程实现了专家PID控制系统的设计和仿真。仿真结果表明,专家PID控制在快速性、抗干扰性等方面优于常规PID控制。     

Intelligent system based on wavelet decomposition and neural network for predicting of fan speed for energy saving in HVAC system

In this study, a heating, ventilating and air-conditioning (HVAC) system with different zones was designed and tested. Its fan motor speed and damper gap rates were controlled by two controllers (i.e. a PID controller and an intelligent controller) in real time to minimize its energy consumption. The desired temperatures were realized by variable flow-rate by considering the ambient temperature for each zone and evaporator. The PID parameters obtained in our previous theoretical work using fuzzy logic were utilized in this study. The experimental data used in this study was collected using a HVAC system built in a laboratory environment. The fan motor speed and damper gap rates were predicted using wavelet packet decomposition (WPD), entropy, and neural network (NN) techniques. WPD was used to reduce the input vector dimensions of the intelligent model. The suitable architecture of the NN model is determined after certain trial and error steps. According to test results, the developed model performance is at desirable level. Efficiency of the developed method was tested and a mean 95.62% recognition success was obtained. This model is an efficient and robust tool to predict damper gap rates and fan motor speed to minimize energy consumption of the HVAC system.     

Application of an energy management and control system to assess the potential of different control strategies in HVAC systems

The significant and continuous increment in the global electricity consumption is asking for energy saving strategies. Efficient control for heating, ventilation and air-conditioning systems (HVAC) is the most cost-effective way to minimize the use of energy in buildings. In this framework, an energy management and control system (EMCS) has been developed to schedule electricity end-uses in the campus of the Universidad Politécnica de Valencia (UPV), Spain. This paper presents an evaluation performed by using the EMCS of different control strategies for HVAC split systems. It analyzed the effect of different schedules for a common air-conditioning device and demand response strategies are tested in several situations. The economic saving is calculated taking into account the electricity contract clauses. Finally, a test is made for the control of a group of similar devices in order to reduce the maximum peak power in consumption and to obtain a flexible load shape with the HVAC loads. The studies are then extrapolated to a larger system, the whole University campus, for which energy and economic savings are quantified.     

An experimental system for advanced heating,ventilating and air conditioning (HVAC) control

While having the potential to significantly improve heating, ventilating and air conditioning (HVAC) system performance, advanced (e.g., optimal, robust and various forms of adaptive) controllers have yet to be incorporated into commercial systems. Controllers consisting of distributed proportional-integral (PI) control loops continue to dominate commercial HVAC systems. Investigation into advanced HVAC controllers has largely been limited to proposals and simulations, with few controllers being tested on physical systems. While simulation can be insightful, the only true means for verifying the performance provided by HVAC controllers is by actually using them to control an HVAC system. The construction and modeling of an experimental system for testing advanced HVAC controllers, is the focus of this article.     

Multivariable control of indoor air temperature and humidity in a direct expansion (DX) air conditioning (A/C) system

Controlling indoor humidity at an appropriate level is very important since this affects occupants' thermal comfort and indoor air quality (IAQ). The paper presents an investigation on developing a multi-input multi-output (MIMO) control strategy for simultaneously controlling the indoor air temperature and humidity by varying the speeds of both compressor and supply fan in an experimental DX A/C system. The MIMO-based controller was designed based on the linearized dynamic model of the experimental DX A/C system. The Linear Quadratic Gaussian (LQG) technique was used in designing the MIMO-based controller. The controllability tests with respect to both the disturbance rejection capability and the command following capability were carried out to assess the control performance of MIMO controller. The results of disturbance rejection capability test showed that the MIMO control strategy can effectively maintain the indoor air temperature and humidity to their respective settings after an unmeasured heat load disturbance was imposed by simultaneously varying speeds of both the compressor and the supply fan of the DX A/C system. Furthermore, in the command following capability test for indoor air temperature, the test results showed that the indoor air temperature can be controlled to its new setting while indoor humidity remained unchanged. Similar test results were also observed in the command following capability test for indoor humidity. Therefore, the MIMO controller developed can effectively control indoor air temperature and humidity simultaneously by varying compressor speed and supply fan speed of the DX A/C system. Compared to the previous related studies using conventional on–off control method or single-input single-output (SISO) control strategy, which can only effectively control either air temperature or relative humidity, the MIMO controller can simultaneously control the indoor air temperature and humidity with adequate control sensitivity and accuracy. The application of MIMO control strategy developed can be extended to other HVAC systems in the future to improve their operating performance and energy efficiency.