Investigation of thermal performance of a passive solar building with floor radiant heating

This paper presents a theoretical study of an integrated radiant floor heating–direct gain passive solar system. Thermal mass is utilized both for storage of auxiliary heating energy and direct solar gains incident on the floor. An explicit finite difference model is developed to accurately model nonlinear effects and auxiliary heating control. The numerical simulation model is employed to study the performance of a passive solar outdoor test-room with different amounts of thermal mass under various control strategies with constant and sinusoidal room thermostat setpoints. A satisfactory thermal mass is determined based on energy savings, reduction of room temperature swings, and prevention of floor surface overheating. Control of auxiliary heating based on a room effective (operative) temperature is shown to result in improved thermal comfort and higher utilization of passive solar gains as compared to room air temperature control.     

The importance of a storage tank in the brine cycle of an absorber roof-assisted heat pump

A dynamical model to calculate the performance of an absorber roof-assisted heat pump is developed. The model is applied to a specific example, a normal residence building in Berlin. The heat pump is layed out to meet the heat demand at 0°C outside temperature. The auxiliary heat is provided by a conventional backup system. Conditions of insolation and outdoor temperature are derived from real weather data and simulated in their dynamical behaviour. The analysis investigates how the variation of the storage tank volume and the lower limiting COP is reflected in the annual cost savings.     

Numerical model of a building with transparent insulation

An explicit finite difference simulation model is developed to study the thermal performance of an outdoor test-room with one transparently insulated (TI) wall. The thermal behavior of the room is examined under different control strategies for the shading device and for air flow through the TI wall to the room. Simulation results indicate significant energy savings with practically no auxiliary heating required on cold sunny days in Montreal. However, appropriate control strategies are required to prevent overheating of the room and discomfort. Air flow through the TI wall and then into the room succeeds in lowering its room surface temperature to less than 31°C and reducing to zero the auxiliary heating required on any clear day. Blind control is based on several criteria, including outside temperature, room-facing surface temperature of TI wall (not to exceed 29°C) and room air temperature not to exceed a certain maximum.     

Simulation and cost optimization of solar heating of buildings in adverse solar regions

In the present study a model has been developed which simulates the effects of hourly weather conditions on the performance and cost of a combined solar/conventional heating system for buildings in cold, cloudy climates. The model exhibits the effects of several system and cost parameters on combined system cost so that optimal designs can be determined.Performance and cost results are presented for 1971 Ottawa, Ontario, weather data. The economic analysis, which treats both collector and conventional system fuel costs parametrically, shows that solar heating of a typical house in cold, cloudy climates is economically competitive with fuel oil heating only if the price of oil rises to approximately 80¢/gal.     

混水采暖系统控制策略探讨

运用能量和质量守恒定律创建混水采暖系统动态模型,通过分析和模拟系统特性及不同控制策略动态响应。文中选用三种策略对混水系统予以控制,即室外气候补偿器、基于模糊推理的室外气候补偿器和增加室内温度控制器的控制策略。仿真结果显示,基于模糊推理的室外气候补偿器和室内温度控制器共同控制时既可获得显著经济效益,又能较大改善室内热舒适性。     

A grey‐box model of next‐day building thermal load prediction for energy‐efficient control

Accurate building thermal load prediction is essential to many building energy control strategies. To get reliable prediction of the hourly building load of the next day, air temperature/relative humidity and solar radiation prediction modules are integrated with a grey‐box model. The regressive solar radiation module predicts the solar radiation using the forecasted cloud amount, sky condition and extreme temperatures from on‐line weather stations, while the forecasted sky condition is used to correct the cloud amount forecast. The temperature/relative humidity prediction module uses a dynamic grey model (GM), which is specialized in the grey system with incomplete information. Both weather prediction modules are integrated into a building thermal load model for the on‐line prediction of the building thermal load in the next day. The validation of both weather prediction modules and the on‐line building thermal load prediction model are presented. Copyright © 2008 John Wiley & Sons, Ltd.     

Cost of house heating with solar energy

There has long been a need for a practical method of predicting the true cost of heating a house with solar energy and designing the heating system (solar and auxiliary) to achieve the minimum total annual heating cost possible under the particular climatic, geographic, and residential characteristics involved. Rough approximations based on various types of averaged values of weather and seasonal variables have previously been developed, but the reliability of such methods and results is open to question. The authors have therefore made a rigorous analysis of projected solar heating costs in eight U.S. cities and have optimized the heating system design in each location.The analysis involved the use of a high speed computer and approximately 400,000 hourly observations in eight cities of radiation, temperature, wind, solar altitude, cloud cover, and humidity. Equations for performance of flat plate solar collectors and sensible heat storage systems were developed and programmed with the above weather variables and with eight design parameters comprising house size, collector size, storage size, collector tilt, number of transparent surfaces in collector, hot water demand, insulation on storage unit, and thermal capacity of collector. Capital and operating costs were quantitatively related to heating system design parameters, and the values of all design variables which yielded lowest annual heating cost in each city were then selected.The findings are presented in the form of two tables and ten graphs, showing heating costs as functions of various design and location factors. The relative importance of each factor is discussed, and the overall costs of solar heating are compared with the costs of conventional heat supply in each location. The method for designing the least-cost combination of solar and conventional heat supplies is also shown, and an example of the use of the method is presented.     

Consumer impacts on dividends from solar water heating

Common domestic solar water heating system usage patterns were investigated by a survey of 55 installations. These usage patterns were modelled by simulation based on the actual occupants' use of boiler or other auxiliary heating control strategies. These strategies were not optimal, as often assumed. The effectiveness of the technology was found to be highly sensitive to the time settings used for auxiliary water heating, and the 65% of solar householders using their boilers in the mornings were found to be forgoing 75% of their potential savings. Additionally, 92% of consumers were found to be small households, whose potential savings were only 23% of those of larger households, which use more hot water. Overall the majority (at least 60%) of the systems surveyed were found to be achieving no more than 6% of their potential savings. Incorporating consideration of Legionella issues, results indicate that if solar thermal technology is to deliver its potential to CO₂ reduction targets: solar householders must avoid any use of their auxiliary water heating systems before the end of the main warmth of the day, grants for solar technology should be focused on households with higher hot water demands, and particularly on those that are dependent on electricity for water heating, health and safety requirements for hot water storage must be reviewed and, if possible, required temperatures should be set at a lower level, so that carbon savings from solar water heating may be optimized.     

温控下被动式太阳房辅助热源量的动态分析

减少对辅助热源的依赖是太阳能建筑设计的一个重要目标,利用建筑自身的集热蓄热能力,可以减少辅助热源量.研究了根据一维热网络模型、温控下辅助热源量的计算公式及热平衡方程,计算不同辅助热源的控制常数以及设定温度下室内温度和辅助热源量的变化;分析了不同的热源控制常数取值和设定温度对室内温度和辅助热源量的影响;讨论了设定温度对墙体蓄热利用的影响.     

Variability of energy use for domestic space heating

The level of reported variability of domestic space heating energy use is extremely high, the coefficient of variation being 20% even for groups of similar houses. In consequence, there is a need for heating systems to work effectively and economically over a wide range of energy use levels and there is also a need for large sample sizes in evaluating field results if the effects of individual factors contributing to the overall variability are to be assessed. For dissimilar houses, samples of 25 or more are necessary for the detection of individual factors and hundreds may be required for their accurate estimation.The effect on energy use of night temperature set-back is shown theoretically to be equivalent to a 2$\text{1}\text{2}$% energy saving per degree Kelvin temperature depression. The effects of more intermittent heating system operation are provisionally estimated, a 50% energy saving being estimated for a 6-h period of daily use at the required temperature. Effects of choice of internal temperature and ventilation rate on energy use are assessed.The energy savings made by such personal control strategies can be nullified by equipment deficiencies. The magnitudes of the effects of three such deficiencies (pipe or duct losses, unresponsive emitter control and upstairs overheating in mild weather) are estimated as each adding around 20% to the heating energy use of a typical house.The combined effects of energy saving strategies and equipment deficiencies make possible annual energy use figures from half to one-and-a-half times the designed level. The implications of this variability for heating system design are discussed.     

Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme/model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005 〈www.archenergy.com〉]. Energy savings up to 30.4% were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied.     

Central electric thermal storage (ETS) feasibility for residential applications: Part 1. Numerical and experimental study

Detailed models have been developed and integrated into a TRNSYS calculation tool to evaluate the optimal storage capacity of central electric thermal storage (ETS) units for residential applications. The tool uses hourly weather data to establish the energy use profile of residential buildings under different heating system configurations and control strategies. The reliability of the system for each configuration is determined as the percentage of time the heating system meets the heating requirement of the building. The level of reliability is used to evaluate the appropriate capacity of the system. This study investigates the theoretical development and modelling of a multi‐zone building equipped with a central ETS in TRNSYS. The TRNSYS simulation results are then compared and validated against experimental data obtained during the project. Furthermore, the effect of various parameters such as system configuration, charging capacity, control strategies, heat losses from the building, and electric utility time‐of‐use schedules are analysed. Copyright © 2001 John Wiley & Sons, Ltd.     

Modelling and evaluation of heating strategies for high temperature polymer electrolyte membrane fuel cell stacks

Experiments were conducted on two different cathode air cooled high temperature PEM (HTPEM) fuel cell stacks; a 30 cell 400 W prototype stack using two bipolar plates per cell, and a 65 cell 1 kW commercial stack using one bipolar plate per cell. The work seeks to examine the use of different heating strategies and find a strategy suited for fast start-up of the HTPEM fuel cell stacks. Fast start-up of these high temperature systems enables use in a wide range of applications, such as automotive and auxiliary power units, where immediate system response is needed. The development of a dynamic model to simulate the temperature development of a fuel cell stack during heating can be used for assistance in system and control design. The heating strategies analyzed and tested reduced the start-up time of one of the fuel cell stacks from 1 h to about 6 min.     

On eliminating peak load auxiliary energy consumption in passive solar residences during winter

This paper uses simulation analysis with Albuquerque, NM and Madison, WI weather data to address the following four questions:

1. Assuming a properly designed and controlled passive house, how does total electrical auxiliary energy consumption depend on the choice of peak load blackout periods?

2. What comfort penalties arise from properly coping with a variety of peak load blackout periods?

3. Where should off-peak energy be introduced into the thermal masses of the house?

4. What are the effects of imprecise information on short term future weather?

Using a combination of linear programming and gradient techniques, the following conclusions are obtained:During the worst days of the heating season, passive solar houses built above ground use a substantial amount of peak backup energy even if they are well designed. Even relatively crude off-peak controls provide reasonable comfort provided the energy is introduced in thermal masses well coupled to the room [e.g. 0.05 m (2 inches) beneath the inside face of the Trombe wall or 0.05 m (2 inches) below the top of the slab floor]. Introducing off-peak energy in thermal masses poorly coupled to the room (e.g. deep in the floor slab) makes proper control very difficult without very accurate weather prediction.Reducing backup use to zero from 7 am to 10 pm requires a doubling of daily backup use in Albuquerque and Madison. Excluding backup for shorter periods (e.g. 5 pm to 9 pm) requires an increase of about 25% in daily backup consumption.Even if off-peak energy is stored at points reasonably well coupled to the room, significant backup and comfort penalties are incurred with erroneous weather forecasts. Even in two adjacent days in Madison, reversing the weather patterns while maintaining the same off peak control strategies resulted in either wasting half the backup energy or severely under heating the house. The effects of faulty weather forecasts are more severe when poorly coupled storage sites are used.     

菏泽市气象条件与冬季节能供暖的关系

利用实测和实验数据,探讨气象条件与冬季节能供暖的关系,得出在不同环境温度条件下,室内保持一定温度时,锅炉的采暖时间、时次以及水温的最佳日质调控指标。     

Design parameters and control strategies for a combined passive heating and cooling system in Louisville,KY

ABSTRACT

Conventional passive solar systems can significantly reduce a building's heating load. However, the integration of passive heating and cooling systems in the same building and the benefits of actively controlling passive systems has largely been unexplored. The objective of this study was to determine the relative performance of a passive solar heating and sky cooling system operating with a range of control strategies, with the goal of minimising the overall annual energy use for space conditioning. A combined system (CS) and a separate system (SS) were simulated with thermal networks using MATLAB, with weather data for Louisville, KY. The control strategies simulated included: Seasonal, Ambient, Room and Matrix. The highest fraction of energy supplied by ambient sources for the SS was 0.707 with Matrix control, while for the CS, the highest fraction (0.704) was with Matrix temperature control with switchable attributes for heating and cooling.     

Augmented control strategies for radiant floor heating systems

A dynamic model of a radiant floor heating (RFH) system useful for control analysis is developed. The overall model consists of a boiler, distribution system, an embedded tube floor slab and building enclosure. The overall model is described by non‐linear differential equations which were solved using finite numerical methods. Two control strategies for improving the temperature regulation in RFH systems are proposed. These are: a multistage on–off control and an augmented constant gain control (ACGC). Simulation results show that the multistage control maintains zone air temperature close to the setpoint better than the existing on–off control scheme does. Likewise, ACGC gives good zone temperature control compared to the classical proportional control. The ACGC is shown to be robust to changes in weather conditions and internal heat gains. The advantage of the control strategies proposed is that they eliminate the use of outdoor temperature sensors required in some existing control schemes. Being simple and robust, the proposed control schemes are good candidate controls for RFH systems. Copyright © 2002 John Wiley & Sons, Ltd.     

Variable air volume ventilation control strategies analysed in six climate zones

This paper presents eight ventilation control strategies and their annual energy and indoor air quality simulation results for an academic building as if it were situated in each of six geographic locations. The results show that without tempering at the terminal boxes, no ventilation strategy could satisfy the outdoor air requirements when the thermal loads are low. The fixed outdoor air percentage method is the worst one. From an economic perspective, strategies using optimization techniques minimize the operating energy demand and consumption. Supply air temperature (SAT) and primary airflow rate are the two proper optimization parameters on the air side of heating, ventilating, and air‐conditioning systems. In addition to control strategies, geographic locations or weather patterns influence the benefits of optimization. Generally, a mild‐dry climate intensifies the advantages of the SAT reset and encourages the primary airflow optimization. Inversely, hot‐humid weather minimizes the benefits. Copyright © 1999 John Wiley & Sons, Ltd.     

Performance prediction of a solar/gas driving double effect LiBr–H2O absorption system

This paper presents the performance prediction of a solar/gas driving double effect LiBr–H₂O absorption system. In order to use auxiliary energy more effectively and be less dependent on solar irradiation, a new kind of solar/gas driving double effect LiBr–H₂O absorption system is designed. In this system, the high-pressure generator is driven by conventional energy, natural gas, and solar energy together with water vapor generated in the high-pressure generator, which supplies energy to the low-pressure generator for a double effect absorption system. The temperature of hot water supplied to the low-pressure generator is close to 90 °C. Apart from refrigeration in summer, this system also supplies space heating in winter and hot water throughout the year for family daily use. Simulation results illustrate that this kind of system is feasible and economical. Economic evaluation of several systems is also given in this paper in order to get a clear knowledge of the energy consumption of the system.     

Discharge air system: modelling and optimal control

A state‐space model of a discharge air system (DAS) is developed. Simulation results obtained from the developed model compare well with the published experimental data. The optimal control strategies and optimal performance of DAS to step changes in setpoints are given for two cases: a heating case with temperature control, and a cooling case with temperature and humidity control. Results show that the outputs (discharge air temperature and humidity ratio) of the system reach the chosen setpoints rapidly and smoothly compared with that of PI control results published in the literature. Copyright © 1999 John Wiley & Sons, Ltd.