居住建筑供暖调节器设计

针对我国北方城市冬季连续集中供暖的情况,设计了基于模糊温度控制的节能供暖调节器.该控制器实时性好,控制速度快,稳定性好.     

校园楼宇供暖节能控制系统的研究与应用

针对高校供暖的特点及供暖过程中存在的问题,研发了楼宇供暖节能控制系统.该系统能够根据不同建筑物的使用情况,自动调节供暖温度.并通过校园网实现远传监控.节能效果显著,同时还解决了供暖管网热力失调问题.     

供暖建筑物的节能体型设计

通过分析建筑物供暖耗热量，求出了建筑物的最佳节能长宽比与节能体型系数，并进一步分析了建筑物长宽比与体型系数对建筑供暖耗热量的影响，为供暖建筑节能体型设计提供了参考依据。     

高校楼宇集中供暖节能系统的设计

目前,我国建筑集中供热系统节能的水平不高,在高校供暖系统中存在的问题同样严重。为了解决高校楼宇集中供暖节能问题,研制了高校楼宇集中供暖节能系统,它根据不同建筑物不同时段的供暖需求与气候特征,调节安装在建筑物供暖主管道上的电动调节阀,降低处于无人状态的建筑物对热能的消耗。系统以进回水温差和进回水压力差为参照调节电动调节阀开度,解决了供暖管网热力失调问题。     

智能建筑照明控制系统的设计与实现

本文通过使用西门子公司开发的APOGEE顶峰系统,对某建筑物照明系统实施自动控制。介绍了控制器选型、系统图、接线图设计等硬件设计过程及搭建系统架构、系统数据库以及编写控制程序的软件设计过程,最后对设计完成的整个系统进行现场调试,实现了对建筑物照明系统的智能控制。     

对供暖建筑节能体型的研究

通过分析建筑物的供暖耗热量,求出建筑物的最佳节能长宽比与节能体型系数,并分析了体型系数对供暖、热量的影响,为节能建设的设计提供依据。     

过渡区供暖室外计算温度及供暖期的确定

①　　设计计算用的供暖期及供暖期室外计算温度,是计算供暖建筑物的能量消耗,进行技术经济分析比较不可缺少的基础数据。因此确定供暖室外临界温度标准及供暖期的统计方法,是一个十分重要且急需解决的问题。目前在电力系统的暖通设计中,对于建筑物设不设采暖主要是根据ＤＬ／Ｔ５０３５－９４《火力发电厂采暖通风与空气调节设计技术规定》来确定。该规定划分了集中采暖区与采暖过渡区,并在条文中明确规定：采暖室外临界温度为５℃,并且按滑动平均（即稳定通过）的方法统计和确定采暖期天数。从早在５０年代到近年我国卫生部门关于室…     

单体住宅建筑围护结构供暖能耗分析

对不同朝向、外形和围护结构传热系数的6种典型住宅建筑物的热特性进行逐时模拟计算,概括了描述建筑物及其内部户型的指标和参数。计算表明,建筑物或户型的供暖指标与其平均传热系数和体形系数的乘积成正比。认为根据建筑物不同朝向和房间所处位置接受的太阳辐射热及外围护结构情况,可以判断房间的供暖指标。     

具有不同供暖参数环路的区域供暖系统--辽宁省人民政府大院锅炉房设计体会

对区域内各建筑物要求有不同供暖参数,供暖时间的供暖系统进行了分析和研究,并提出了可行的系统设计方案。     

集照明、供暖、风扇、心理效应于一体的智能教室系统

基于微波传感器、单片机、电磁阀等核心技术设计了集照明、供暖、风扇、心理效应于一体的智能教室系统,各模块相互独立、相互联系,旨在达到节能减排的目的,且满足了不同人的舒适度需求。以标准教室为模型详细分析该智能教室系统的显著节能效果。该系统只需根据不同环境的特点改变系统中涉及的参数,即可推广到其他公共场所。     

Quasi-adaptive fuzzy heating control of solar buildings

Significant progress has been made on maximising passive solar heat gains to building spaces in winter. Control of the space heating in these applications is complicated due to the lagging influence of the useful solar heat gain coupled with the wide range of construction materials and heating system choices. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set-up and commissioning procedures. This paper addresses the development and testing of a quasi-adaptive fuzzy logic control method that addresses these issues. The controller is developed in two steps. A feed-forward neural network is used to predict the internal air temperature, in which a singular value decomposition (SVD) algorithm is used to remove the highly correlated data from the inputs of the neural network to reduce the network structure. The fuzzy controller is then designed to have two inputs: the first input being the error between the set-point temperature and the internal air temperature and the second the predicted future internal air temperature. The controller was implemented in real-time using a test cell with controlled ventilation and a modulating electric heating system. Results, compared with validated simulations of conventionally controlled heating, confirm that the proposed controller achieves superior tracking and reduced overheating when compared with the conventional method of control.     

Accounting free gains in a non-residential building by means of an optimal stochastic controller

A prototype predictive controller, based on the theory of optimal stochastic control, was developed and installed in a non-residential building in Delémont (Switzerland). This building is very well insulated (U = 0.65 W/m²K for windows) and, moreover, equipped with an active floor heating and cooling system. Solar and free gains supply more than 50% of its heating energy during winter. The controller determines, with the aid of the predicted free gains, the heat to supply for the next hour in order to optimise comfort and minimise energy consumption over a period of 24 h. The performance of this controller is compared with that of an advanced external temperature controller installed in the same building. A detailed energy balance of the building is presented for both controller types. The maximal energy savings observed in favour of the predictive controller amount to 24% during the cold season (October through April) and even reach 31% during the hot season (May through September). The thermal comfort was evaluated through questionnaires filled in by the occupants, but also thanks to an analysis based on temperature monitoring in the building. The analysis results show that comfort was maintained by the predictive controller.     

高校楼宇供暖节能控制系统研制

针对高校供暖面积大、能耗多,供热管线长、水力失调严重等特点,研制了一种楼宇供暖节能控制装置。该装置由现场控制器、温度传感器和电动调节阀组成,现场控制器完成数据的采集和处理,并根据各时段的供暖温度要求,自动调节电动阀门的开度,从而调整进入楼宇的供水流量。另外,在控制流程中还加入了节假日保证最低供暖温度的模式,避免了能源的浪费。     

Model predictive control of a building heating system: The first experience

This paper presents model predictive controller (MPC) applied to the temperature control of real building. Conventional control strategies of a building heating system such as weather-compensated control cannot make use of the energy supplied to a building (e.g. solar gain in case of sunny day). Moreover dropout of outside temperature can lead to underheating of a building. Presented predictive controller uses both weather forecast and thermal model of a building to inside temperature control. By this, it can utilize thermal capacity of a building and minimize energy consumption. It can also maintain inside temperature at desired level independent of outside weather conditions. Nevertheless, proper identification of the building model is crucial. The models of multiple input multiple output systems (MIMO) can be identified by means of subspace methods. Oftentimes, the measured data used for identification are not satisfactory and need special treatment. During the 2009/2010 heating season, the controller was tested on a large university building and achieved savings of 17–24% compared to the present controller.     

智能家居网关设计

该文主要论述了以太网技术在智能家居系统中的应用与实现,完成了智能家居网关的设计。智能家居网关以32位高性能单片机STM32为核心控制器,通过以太网控制器支持TCP、UDP和DHCP PPPOE协议。智能家居网关通过以太网接收各智能节点所采集的环境数据(温度、湿度、CO浓度等)并对数据进行处理,同时用液晶屏显示各个节点的信息。另外智能网关可按需设置不同的报警阈值,当设定的报警阈值小于节点的实际测量值时,可对危险信息进行报警同时通过以太网向节点发送相应的控制命令。测试结果表明该网关能够有效实现对各个智能节点信息的有效管理和处理。     

Assessing the saving potential of blind controller via multi-objective optimization

This paper presents the results of computational experiments where multi-objective algorithms were used to tune a controller for blind movements in a residential building and a room of the LESO (Solar Energy and Building Physics Laboratory) experimental building. The blind controller, which is based on fuzzy logic, was optimized not only in terms of energy consumption but also in terms of thermal comfort. The goal is to show saving potential for intelligent blind controller in a real world example rather than in tailored idealized test rooms. Therefore, a state of the art simulation program with a multi-objective evolutionary algorithm was combined. It was found that with elementary control systems, like schedules for the lighting in a building, almost 40% of the energy could be saved. With the help of more advanced controllers this can be further increased. Also discussed in this paper are the results and the feasibility of implementing such a controller.     

火灾报警系统及发展

概述了火灾报警控制器的工作原理及其发展以及传统火灾自动报警控制器在工程应用中存在的问题，并就现代火灾自动报警控制器在某些方面的改进方法进行了阐述，指出多功能火灾报警控制器为楼宇自动化管理系统提供中央监控和智能分散管理发挥着重大的作用。     

Are the energy efficient rates (RVRs) approximate in different climatic locations for the same building with the same reform?

This paper studies the annual heating and cooling energy consumption and the variation law with the tools of characteristic temperature method (CTM) when making the same energy-saving measures on the same building under 43 different climate conditions. It can be found that for the same building, under different climate conditions, the maximal difference in annual energy consumption is up to more than 70 times and after improving building envelope, annual heating and cooling energy reductions are greatly different under various weather conditions, which illustrates that building energy consumption and its reduction is completely dependent on climate conditions; and the energy-saving potentiality and economic value with the same measures are quite different under various climatic conditions. Nevertheless, annual energy efficient rates of cooling are approximate (33.9–39.8%) for the same building with the same energy efficient measures in 43 climate conditions with quite different climatic conditions, and those of heating are also approximate (between 16.2% and 19.5%). This paper proves again the common rule that climate conditions determine energy consumption while energy efficient rates depend on the energy efficient measures.     

适合热计量的室外供热系统控制方式与分析

针对可热计量的两种室内供热系统，在计算分析的基础上认为，对于采用集中式热力站的系统，在用户入口处，单管跨越式系统应加流量限制器，双管系统应设差压控制器；对于采用分散式热力站的供热系统，单管跨越式系统可不设流量限制器，双管系统二次侧宜采用循环水泵变频调速控制，不宜加差压控制器。     

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.