A simple procedure for selection and sizing of indirect passive solar heating systems

Equivalent sol-air temperatures have been defined for four indirect gain passive solar heating concepts, namely, mass wall, water wall, Trombe wall and solarium. Steady state thermal efficiencies have also been defined as a measure of the ability of each system to deliver heat into the living space.

Design curves have been developed which relate the average instantaneous solar radiation incident on the passive element to thermal efficiency for different values of ambient temperature. These curves are useful in selection of an appropriate passive heating concept for a particular location.

It is inferred that a solarium is most effective at very low levels of incident radiation and low ambient temperature. Water walls and Trombe walls are most efficient at higher levels of incident radiation.

A simple procedure has been developed for a first approximation of sizing the selected system using these design curves and a minimum of meteorological information, namely, monthly average of daily global solar radiation, monthly average maximum and minimum ambient temperatures.     

The impact of hourly solar radiation model on building energy analysis in different climatic regions of Turkey

The purpose of this study is to investigate the effect of solar radiation models on the determination of energy performance of a single-family house assisted with renewable energy system including photovoltaic panels and solar water heater. An Angström-Prescott type solar radiation model was compared with Zhang and Huang model derived based on hourly meteorological data of 12 locations in Turkey. Since regression coefficients of the Zhang and Huang model are valid for China, new regression coefficients were derived by using local meteorological data. A clear distinction could not be observed in simulated annual heating load intensity for each model since the average relative deviation of the models’ results was 2.5%. However, the average deviation was 12.5% for space cooling load intensity. Primary energy ratings (PER) and the renewable energy ratio (RER) were determined for each location. For total PER, the highest deviation was 4.6% and 3.3% for Mersin and Mu?la, respectively. For the other locations, this parameter deviates between 0.02%–2.11%. The highest RER was 18.6% for Mersin.     

气象参数对成都地区办公建筑能耗的影响及预测

气象参数是影响建筑热环境和供暖空调能耗的主要因素之一。基于成都地区1971—2000年共30a的历史观测数据,生成了建筑能耗模拟软件EnergyPlus所需要的逐时气象数据文件。比较分析了该地区30a干球温度、太阳辐射等各气象参数月均值的变化,模拟分析了该地区建筑的采暖、制冷及总能耗,利用多元回归建立了建筑能耗与气象参数之间的关系式,并检验了该关系式的准确性。结果表明:成都地区办公建筑能耗变化与各气象参数没有呈现明显的规律性;建筑月总能耗与各气象参数呈纯二次多项式关系,月采暖能耗、月制冷能耗与各气象参数呈交叉二项式关系;建筑月能耗回归模型能够较准确地预测建筑月能耗与各气象参数的关系,且月采暖能耗和月制冷能耗回归模型预测的准确性优于月总能耗模型。     

Estimation of horizontal diffuse solar radiation from common meteorological parameters: a case study for Jeddah,Saudi Arabia

The measured data of global and diffuse solar radiation on a horizontal surface, number of sunshine hours, mean daily ambient temperature, maximum and minimum ambient temperatures, relative humidity and amount of cloud cover, for Jeddah (latitude 21° 42′ 37″ N, longitude 39° 11′ 12″ E), Saudi Arabia for the period (1996–2006) are analysed. The data are employed to develop empirical correlations between the monthly average daily diffuse fraction (H _d /H) or diffuse transmittance (H _d /H ₀) and various meteorological parameters such as relative number of sunshine hours (s/s ₀), ambient temperature T, relative humidity R _h and amount of cloud cover c _w. The derived correlations are evaluated by making comparisons between measured and calculated values of monthly average daily diffuse radiation H _d. All the proposed correlations are found to be able to predict the monthly and annual averages daily diffuse radiation with excellent accuracy. It is also inferred that, if the data of the monthly average daily global radiation H and number of bright sunshine hours s are not available, the values of H _d for the hot-humid zone of Saudi Arabia can be estimated with a reasonable accuracy from the correlations between H _d /H ₀ and the mean daily ambient temperature T.     

Estimation of direct solar irradiance intercepted by a solar concentrator in different modes of tracking (case study: Algeria)

While reasonably accurate knowledge of solar radiation data at the location of interest is necessary for the design of any solar energy conversion system, the use of concentrating solar collectors implies that these systems only work with the direct solar irradiance. In the present study, by using a methodology based on simple equations, the total hourly, daily, monthly and annual direct radiations incident on four different oriented solar concentrators were calculated only from the recorded data of monthly mean daily global and diffuse horizontal solar irradiance for three different Algerian sites, in order to choose the best mode of tracking for concentrating solar thermal power systems and concentrating solar photovoltaic power systems applications. The model predictions were found to be consistent with ground measurements and prior studies of Kalogirou. It was found that the greatest energy gains were achieved by using full tracking. Furthermore, the model can be included for application to other Algerian and worldwide locations for estimating direct solar irradiance intercepted by a solar concentrator in different modes of tracking.     

Development of the typical meteorological database for Chinese locations

The typical meteorological database for 57 Chinese locations was developed for building simulations and air-conditioning design. The database consists of three parts: the typical meteorological years (TMY), the typical meteorological days (TMD) and the design temperature and humidity (DTH). The typical meteorological year (TMY) is the main part of the database. Because there are not data on solar radiation in the observations, a method to estimate solar radiation with dry bulb temperature difference, relative humidity, total cloud cover and wind speed was developed. Methodologies of interpolations were developed to produce 1 h data with the 3 h data. The global solar radiation on the horizontal surface was separated into direct and diffuse components with the Gompertz function. The typical meteorological day (TMD) consists of the monthly average values of dry bulb temperature, solar radiation, relative humidity, etc. for each hour of the day. The design temperature and humidity (DTH) was developed for the purpose of air-conditioning design. The frequencies of 2.5% and 5.0% were selected to decide the design temperature and humidity for the 57 Chinese locations.     

Multi-step-ahead forecasting of daily solar radiation components in the Saharan climate

ABSTRACT

Accurate estimation of renewable energy sources plays an important role in their integration into the grid. An unexpected atmospheric change can produce a range of problems related to various solar plant components affecting the electricity generation system. Global solar radiation (GSR) assessment has been increased in the past decade due to its important use in photovoltaic application. In this paper, we propose the use of machine learning-based models for daily global and direct solar radiation forecasting in a semi-arid climate, using a combination set of meteorological parameters on a horizontal surface in the Ghardaïa region. The models are presented and implemented on 3-year measured meteorological data at Applied Research Unit for Renewable Energies (URAER) at Ghardaïa city between 2014 and 2016. The results show that both MLP and RBF models perform well for three-step-ahead forecasting with a slight improvement in MLP models in terms of statistical metrics.     

铅垂面上太阳辐射计算方法探讨

在建筑物的太阳能利用中常涉及铅垂面上太阳辐射量的计算问题，其理论计算方法中，Perez模型计算较准确但是较繁杂，Hay模型较为简明实用。在工程应用中，通过计算铅垂面上日平均辐射量而计算月总辐射量，其中Hay模型较准确。     

A comparison of luminous efficacy models based on data from Vienna, Austria

To support building design in view of daylight quality, computational (simulation) tools can provide effective support. To perform detailed daylight analysis via simulation, appropriate sky models are needed. In the past, various sky luminance distribution models have been developed. Such models, however, require illuminance data for the relevant location. As measured external illuminance levels are not available for many locations, the more widely available irradiance measurements can be translated, using proper luminance efficacy functions, into illuminance values. The present paper compares five global luminous efficacy models based on a database of measured illuminance and irradiance data from Vienna, Austria. These models typically involve mathematical formulations with multiple coefficients, whose values are derived for a specific location. The results suggest that these models performed rather poorly, once tested against Vienna data. However, the models’ performance improved significantly, once the respective coefficients were modified (calibrated) using the Viennese database.     

Soft computing for solar radiation potential assessment in Algeria

ABSTRACT

Precise estimation of solar radiation is a highly required parameter for the design and assessment of solar energy applications. Over the past years, many machine learning techniques have been proposed in order to improve the forecasting performance using different input attributes. The aim of this study is the forecasting of one day ahead of horizontal global solar radiation using a set of meteorological and geographical inputs. In this respect, the Gaussian process regression methodology (GPR) and least-square support vector machine (LS-SVM) with different kernels are evaluated in order to select the most appropriate forecasting model. In order to assess the proposed models, the southern Algerian city, Ghardaia regions, was selected for this study. A historical data of five years (2013–2017) of meteorological data collected at Renewable Energies (URAER) in Ghardaia city are used. The achieved results demonstrate that all the proposed models give approximately similar results in terms of statistical indicators. In term of processing time, all the models showed acceptable computational efficiency with less computational costs of the GPR model among all machine learning models.     

Performance assessment of empirical models for prediction of daily and monthly average global solar radiation: the case study of Ibadan,Nigeria

In this study, the performance assessment of empirical models for modelling global solar radiation in Ibadan is presented. The empirical models are derived from the three basic models: Angstrom–Prescott model, Garcia model and Hargreaves–Sammani model. The data used in the analysis consist of daily average global solar radiation, daily average sunshine hours, daily average maximum temperature and daily average minimum temperature collected over a period of nine years (2000–2008). Regression constants are determined for each of the model for each months of the year. The study reveals that Garcia Quadratic model puts up the best overall performance. The model can predict the daily average global solar irradiation with Mean Absolute Error of 1.86?MJ?m^?2?day^?1, Root Mean Square Error of 2.7?MJ?m^?2?day^?1, Mean Absolute Percentage Error 9.34% and Coefficient of Determination (R²) of 0.68.     

Modelling the performance of rainwater collection systems: towards a generalised approach

The collection of rainwater from roofs, its storage and subsequent use make a significant saving in the use of potable water. This paper investigates how spatial and temporal fluctuations in rainfall can be incorporated into behavioural models, which simulate the performance of rainwater collectors. Temporal variations are considered at two different time scales, that is daily and monthly intervals. The first model uses a daily time interval to model system performance. A set of rainwater collector performance curves for five geographic locations is developed. From the location-specific curves, a set of average curves is determined which is shown to be sufficiently accurate for estimating rainwater collector performance. The second model uses a larger time interval of one month. The effect of daily fluctuations in rainfall is incorporated into this model using a storage operating parameter. Values of the parameter were determined by matching the output from the daily model with that of the monthly model. Generally the rainwater collector performance predicted by the monthly model using average values of the storage operating parameter is shown to correlate well with the corresponding values determined using a daily time interval model. The monthly model provides a simple and versatile method of modelling the performance of rainwater collectors.     

Generation of typical weather data using the ISO Test Reference Year (TRY) method for major cities of South Korea

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. Simulation often requires hourly weather data. Such data sets are the Test Reference Years (TRYs), Typical Meteorological Year (TMY) and Weather Year for Energy Calculations (WYEC). Typical weather data consists of 8760 values of various selected meteorological parameters such as ambient temperature, solar radiation, relative humidity and wind velocity and are originally derived from long-term data. This paper discusses methods of selecting typical weather data, the possibility of using the cloud cover data instead of daily global radiation and describes the selection of ISO Test Reference Year (TRY) for major cities of South Korea. The ISO-15927 procedure and algorithms are explained in detail and the Finkelstein–Schafer statistic, the basic selector statistic explained. ISO TRYs for the major cities of South Korea are derived from 20 years of meteorological data recorded during the period 1986–2005. A comparison is made between the 7 sites demonstrating the link between dry-bulb temperature, solar radiation and latitude.     

Hybrid models for global solar radiation prediction: a case study

ABSTRACT

This paper presents a comparison between different prediction models for solar radiation application. The present study assessed the performance of multi-layer perceptron (MLP) as well as boosted decision tree, and used a new combinition of these models with linear regression for the prediction of daily global solar irradiation (DGSR). The performance of the studied models was validated using a real dataset measured at the Applied Research Unit for Renewable Energies (URAER) situated in the south of Algeria. Different input combinations have been analysed in order to select the relevant input parameters for DGSR prediction. The results acheived show that the MLP model perfoms better than the others models in terms of statistical indicators: normalised root mean square error (0.033) and R² (97.7%).     

Calibration of low-rise multifamily residential simulation models using regressed estimations of transmission losses

In this study, we evaluated a proposed calibration (PC) approach for whole-building energy simulation models. This approach was based on a regression analysis of measured data collected during a time period when the global solar radiation was the lowest. The proposed approach was compared with a more conventional calibration approach with different degrees of complexity, starting from design stage (DS) assumptions, through audits, and lastly by refining the model with detailed measurements and numerical calculations. The evaluation was performed using measured data from two multifamily buildings located in Umeå, Sweden, and the IDA-ICE 4.61 simulation software. The best agreement between simulated and measured data was obtained with the PC approach. The monthly normalized mean bias error and the coefficient of variation were less than 5.0% and 6.0%, respectively. For the conventional calibration approach, detailed measurements and time-consuming numerical calculations were required to reach similar results.     

建筑节能分析太阳总辐射模型研究综述

太阳辐射是建筑节能分析的重要基础气象参数,实测数据远远不能满足需求,理论计算是目前获取辐射数据的主要途径。将常用水平面太阳总辐射模型归纳为气象参数、空间插值和基于DEM三类,详述了各自的原理和计算方法。对三类模型在建筑节能分析中的适用性进行了分析,展望了建筑节能分析用太阳辐射模型的发展趋势:气象参数模型与DEM模型的融合。     

逐时温度变化对混凝土夹心板的温度作用

混凝土夹心板外叶往往较薄,逐时气温变化和太阳辐射对混凝土夹心板的温度作用明显。为了解决我国GB 50009—2012《建筑结构荷载规范》中缺乏逐时温度变化对混凝土夹心板温度作用的取值方法问题,根据1980—2010年长沙市气象观测资料,得到了50年一遇最高温度月(七月)和最低温度月(一月)的标准日逐时空气温度。考虑逐时太阳辐射的强度、朝向、颜色等影响,建立了标准日室外逐时温度模型,并将其分解为稳态温度(年温度)和谐波热(日温度)。推导了在日温度作用下夹心板温度场和平均日温度的解析表达式,分析了不同外叶厚度对夹心板平均日温度的影响。结果表明,夹心板外叶平均日温度幅值随外叶厚度的增加而减小。采用外叶平均日温度相等的方法,得到了按稳态温度场计算日温度作用的等效室外日温度,提出了混凝土夹心板的室外基本气温增加值计算公式,可用于考虑外叶厚度对基本气温增加值的影响。     

住宅小区天然气供暖用气指标的研究

以北京使用天然气供热锅炉房为热源的住宅小区为例,通过数理统计方法得到北京市住宅小区供暖期供暖用气指标,分析了供暖用气的月、日用气规律。探讨了气象条件对供暖日用气负荷的影响,日用气负荷与室外日平均温度、日平均风速、日总辐射量关系密切,与日平均相对湿度、降水量关系不密切。建立了数学模型,得出了日用气负荷与室外日平均温度、日平均风速、日总辐射量的关系。     

Principal component analysis of electricity use in office buildings

Principal component analysis was conducted on five major climatic variables—dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed. Twenty-eight year (1996–2000) long-term measured weather data were considered. A two-component solution was obtained, which could explain 80% of the variance in the original weather data. Monthly electricity consumption data recorded during a 5-year period (1979–2006) were gathered from 20 fully air-conditioned office buildings with centralised HVAC systems in subtropical Hong Kong. Electricity use per unit gross floor area ranged from 163 to 389 kWh/m². These consumption data were correlated with the corresponding principal components using linear multiple regression techniques. The coefficient of determination (R²) varied from 0.76 to 0.95 indicating reasonably strong correlation. It was found that the regression models developed could give a reasonably good indication (mostly within 3%) of the annual electricity use, but the monthly estimates might differ from the actual consumption by up to 9%. Attempt was also made to develop a general regression model for the 20 buildings, which had an R² of 0.84 with a maximum mean-biased error of 18.6% and a maximum root-mean-square error of 21.4%.     

Assessment of ozone variations and meteorological effects in an urban area in the Mediterranean Coast

Ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of both ozone and its precursors. For this purpose, the influence of meteorological variables is a confusing factor. This study presents an analysis of a year of ozone concentrations measured in a coastal Spanish city. Firstly, the aim of this study was to perceive the daily, monthly and seasonal variation patterns of ozone concentrations. Diurnal cycles are presented by season and the fit of the data to a normal distribution is tested. In order to assess ozone behaviour under temperate weather conditions, local meteorological variables (wind direction and speed, temperature, relative humidity, pressure and rainfall) were monitored together with ozone concentrations. The main relationships we could observe in these analyses were then used to obtain a regression equation linking diurnal ozone concentrations in summer with meteorological parameters.