被动式太阳能温室-采暖房中对流传热的数值分析

针对一种被动式太阳能温室-采暖房，分析采暖房北墙采用或不采用隔热保温措施时，温室-采暖房内的温度和气流分布情况，模拟具有蓄热层的太阳能温室-采暖房中的对流传热，研究温室-采暖房中采用岩石床吸收和贮存太阳能的传输特性。     

太阳能采暖办公楼

乌兰浩特位于兴安岭南麓丘陵地带,按建筑热工设计分区,属严寒地区,采暖期长达178天。乌兰浩特冬季以晴为主,日光充足,11月到来年3月日照1040.8小时,日照率高达70.8％,为利用太阳能取暖创造了有利条件。我们利用当地的自然条件,设计出一栋适合北方气候的太阳能采暖办公楼。     

一种太阳能相变蓄热沙发采暖系统分析

介绍一种把太阳能热利用、相变蓄热与局部采暖技术结合的新型太阳能相变蓄热沙发采暖系统,阐述该系统的组成和工作原理,并给出沙发散热量、蓄热材料用量、集热器面积等关键设计参数的计算方法。     

民用建筑主动式太阳能采暖技术研究

结合青海西宁地区的气象资料及当地的气候变化特征,分析民用建筑采暖需求与供热量的关系,提出民用建筑主动式太阳能采暖技术的设计方案.分别从室内空气热平衡和热量传递两个方面,构建民用热过程数学模型.根据该模型下,安装集热器和蓄热器等太阳能采暖所需的设备,确定累计太阳辐照量和建筑供热负荷,计算建筑主动式太阳能的热量.最终通过强...     

太阳能反季节蓄热采暖蓄冷降温技术研究(1)

一概述通过对气象资料分析发现,从统计角度各地的太阳年总辐射量是基本稳定不变的,是太阳能蓄热的稳定热源;冬季最冷月平均气温也变化不大,是冬季     

清华阳光发力太阳能采暖技术

<正>太阳能采暖技术被视为太阳能热利用产业升级的一个重要方向。太阳能被动采暖技术早已在太阳能建筑上得到广泛应用,但可从根本上提升室内采暖温度的主动式太阳能采暖技术却由于技术、政策、市场等方面滞后的原因,一直没有实现规模化推广应用。时移世易、技术进步、环境变迁、产业升级等     

太阳能采暖与牧业工程

从1980年内蒙古建筑科学研究所建成自治区第一座被动式采暖太阳能办公楼算起,至今已建成41栋(不含太阳能畜舍),累计建筑面积达15600m~2。几年来,太阳房的研究设计工作已经引起自治区建筑设计研究院所的重视,并取得了一些成果。     

用于被动太阳能采暖适用技术选择的气候分区研究

中国各地区气候差异较大,不同地区被动太阳能建筑适用的被动太阳能采暖技术类型各不相同,针对现有分区方法忽略室外温度波动对技术选择的影响,该文提出南向最冷月辐射温差比、采暖度日数和冬季室外温度日较差度日数三级指标,分别表征气候适宜性、采暖需求和冬季室外温度的波动差异.首先,以南向最冷月辐射温差比、采暖度日数作为一级和二级指...     

太阳能反季节蓄热采暖蓄冷降温技术研究(2)

三对25个典型气候省会城市及直辖市的计算分析所选25个省会城市及直辖市哈尔滨、长春、沈阳、呼和浩特、西宁、乌鲁木齐、拉萨、兰州、银川、太原、石家庄、北京、天津、西安、郑州、济南、合肥、上海、南京、杭州、南昌、武汉、长沙、重庆及成都代表了我国严寒、寒冷、夏热冬冷建筑气候区的主要经济区域。     

太阳能低温热水地板辐射采暖

随着塑料工业的飞速发展 ,开发出了具有高柔韧性、抗老化、耐高温、耐高压的塑料软管。从 70年代开始 ,塑料管低温热水地板辐射采暖技术在北美、欧洲等发达国家及日本、韩国等得到了广泛应用。我国已引进该项技术 ,并开发出了国产的这种塑料管材。北京亚运村康乐宫、沈阳夏宫等国内一批大型公共建筑已成功使用了地板辐射采暖技术。节能和提高房间的热舒适度是地板辐射采暖的两大优点。地板辐射采暖的热媒是低温热水 ,从而使利用太阳集热器作为热源成为可能。在建设部制定的《中国“住宅阳光计划”纲要》(草稿 )中提出 :根据当前太阳能技术与…     

OPTIMIZATION OF DOMESTIC SOLAR WATER HEATING SYSTEM

TRNSYS program was used to simulate the performance of a thermosyphon type domestic solar water heating system which is used in the West Bank. The system installation and operation parameters were optimized including collector tilt angle, the hot water storage tank volume and location relative to the collector, and the hot water consumption pattern and daily rate.     

OPTIMIZATION OF COLLECTOR AREA IN SOLAR WATER HEATING SYSTEMS

Domestic household thermosyphons are economically feasible and are used by over than 70% of houses in Palestine. Although domestic solar water heating for commercial applications has a good potential, only a few systems have been installed in Palestine. A systematic sizing approach for the solar system is presented in this paper and applied to a certain case study. The solar system sizing is based on the life-cycle cost LCC analysis. For the chosen case study of domestic water heating for a hotel, with hot water consumption of 2600 liters per day, the optimum collector area was found to be 37 m², the solar fraction of heating 0.78, the LCC of system is SI 3778, with annual savings of 1338$/year and a pay back period of 3 years. With this optimized system, the cost of water heating is 1.8 $/m³comparing with 2.6 $/m³ for the conventional system.     

温室太阳能供暖

对全玻璃真空管太阳集热器给大型四连栋蔬菜温室冬季供暖进行实验研究 ,在集热器面积与温室面积为 1∶6 ,温室热损系数为 8 37W /m2 ·℃条件下 ,保持温室内温度在 5℃左右 ,在 2 0 0 0年 12月中旬以前和 2 0 0 1年 2月中旬以后期间 ,温室外日最低气温在 - 4℃以上时 ,太阳能主动和被动供暖能够维持室温 ,无需燃油炉供暖 ,平均太阳能主动供暖率达 2 6 % ,12月中旬到第二年 2月中旬期间需太阳能和燃油炉联合供暖 ,由于此间气温较低 ,平均太阳能供暖率约为 10 %。     

强制循环式太阳热水系统动态特性分析

基于集热器，水箱及换热器等部件热,地晴天无负荷条件下运行的强制循环式太阳能热水系统进行数值模拟，分析了贮热水箱内温度分层，水量，高径比和水流率等对瞬时集热效率和系统日效率的影响。特别探讨了带热交换器的复合回路系统在两种介质热容流率比值改变时，系统热性能变化规律。对设计和控制运行强制循环式太阳热水系统提出了一些建议。     

光照资源富集区太阳能集中供热系统容量配置及热网管径协同设计优化研究

针对常规太阳能供热系统优化设计中太阳集热供热站设计与供热管网设计相互分离,供热管网热传输过程中热损失难以精准计算的问题,建立太阳能集中供热系统容量配置及热网管径协同优化模型,以系统全生命周期成本最小为优化目标,采用遗传算法求解,并通过具体算例与常规优化方法以及工程设计方法的计算结果进行对比分析。结果表明,利用协同优化模型进行太阳能集中供热系统设计,能够有效避免设计系统太阳能保证率偏小以及供热管网比摩阻不满足规范要求的现象。针对具体算例,当太阳能保证率由50%增至100%时,系统最优最低供水温度从60℃降至45℃;随着太阳能保证率的升高,系统单位太阳集热器面积所匹配的储热水箱体积增大,而系统供热管网管径保持不变。     

我国典型城市太阳热水系统热及经济性能分析

对太阳热水系统热及经济性能的分析是系统设计合理的关键。采用了f-CHART方法对太阳热水系统的热和经济性能进行计算和优化分析。首先对我国的太阳能资源分布和f-CHART方法进行了简要的描述，随后对我国太阳能区划的5个典型城市的太阳热水系统的热及经济性能进行模拟计算。计算结果包括太阳能利用率、太阳热水系统优化配置方案、寿命期(10年)内的经济性能等。该方法及其结果可以为实际太阳热水工程的设计和评价提供依据。     

低温多效太阳能海水淡化装置最优集热系统的匹配研究

利用实际天气的太阳辐射值,根据一套低温四效太阳能海水淡化系统稳态实验数据,通过模拟计算,研究分析与该海水淡化系统匹配的太阳能集热系统参数,给出太阳能集热系统集热器面积和储热水箱容量、海水淡化系统启动和暂停温度等参数的最佳取值范围,计算了该装置的年淡水产量,为太阳能海水淡化装置的设计提供一种有效地方法.     

太阳能地面采暖系统蓄热水箱容积分析

通过分析太阳能采暖系统所需蓄热鼍与建筑热负荷、太阳能集热量日变化规律之间的关系,得出太阳能采暖系统所需蓄热水箱容积的理论算式.根据拉萨、银川、西宁、西安等地的太阳辐射强度及建筑热负荷的日变化规律,模拟得出系统所需蓄热量变化规律;并对各种蓄热温差下对应的蓄热水箱容积进行了模拟分析,结果表明:太阳能采暖系统所需蓄热量随太阳集热器的集热量与建筑热负荷之间的差值增大而增加;蓄热水箱容积随蓄热温差增大而减小,当蓄热水温达到80℃时,在各种地面采暖系统取水温度下,单位集热器面积所需蓄热水箱容积趋于相等.     

MODELING OF SOLAR DOMESTIC WATER HEATING SYSTEMS USING ARTIFICIAL NEURAL NETWORKS

Artificial Neural Networks (ANN) are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can be trained to predict results from examples, are fault tolerant, are able to deal with non-linear problems, and once trained can perform prediction at high speed. ANNs have been used in diverse applications and they have shown to be particularly useful in system modeling and for system identification. The objective of this work was to train an ANN to learn to predict the useful energy extracted and the temperature rise in the stored water of solar domestic water heating (SDHW) systems with the minimum of input data. An ANN has been trained based on 30 known cases of systems, varying from collector areas between 1.81 m² and 4.38 m². Open and closed systems have been considered both with horizontal and vertical storage tanks. In addition to the above, an attempt was made to consider a large variety of weather conditions. In this way the network was trained to accept and handle a number of unusual cases. The data presented as input were the collector area, storage tank heat loss coefficient (U-value), tank type, storage volume, type of system, and ten readings from real experiments of total daily solar radiation, mean ambient air temperature, and the water temperature in the storage tank at the beginning of a day. The network output is the useful energy extracted from the system and the temperature rise in the stored water. The statistical R²-value obtained for the training data set was equal to 0.9722 and 0.9751 for the two output parameters respectively. Unknown data were subsequently used to investigate the accuracy of prediction. These include systems considered for the training of the network at different weather conditions and completely unknown systems. Predictions within 7.1% and 9.7% were obtained respectively. These results indicate that the proposed method can successfully be used for the estimation of the useful energy extracted from the system and the temperature rise in the stored water. The advantages of this approach compared to the conventional algorithmic methods are the speed, the simplicity, and the capacity of the network to learn from examples. This is done by embedding experiential knowledge in the network. Additionally, actual weather data have been used for the training of the network, which leads to more realistic results as compared to other modeling programs, which rely on TMY data that are not necessarily similar to the actual environment in which a system operates.