Solar Energy 

Abstract: Based upon the data now available, this paper presents relationships permitting the determination on a horizontal surface of the instantaneous intensity of diffuse radiation on clear days, the long term average hourly and daily sums of diffuse radiation, and the daily sums of diffuse radiation for various categories of days of differing degrees of cloudiness. For these determinations, it is necessary to have, either from actual measurements or estimates, a knowledge of the total (direct plus diffuse) radiation on a horizontal surface-its measurement is now regularly made at 98 localities in the United States and Canada. For localities where only an estimate of the long term average total radiation is available, relationships presented in this paper can be utilized to determine the statistical distribution of the daily total radiation at these localities.

Abstract: A brief discussion is presented regarding the operating temperature of one-sun commercial grade silicon-based solar cells/modules and its effect upon the electrical performance of photovoltaic installations. Suitable tabulations are given for most of the known algebraic forms which express the temperature dependence of solar electrical efficiency and, equivalently, solar power. Finally, the thermal aspects of the major power/energy rating methods are briefly discussed.

Abstract: Manufacturers of photovoltaic panels typically provide electrical parameters at only one operating condition. Photovoltaic panels operate over a large range of conditions so the manufacturer’s information is not sufficient to determine their overall performance. Designers need a reliable tool to predict energy production from a photovoltaic panel under all conditions in order to make a sound decision on whether or not to incorporate this technology. A model to predict energy production has been developed by Sandia National Laboratory, but it requires input data that are normally not available from the manufacturer. The five-parameter model described in this paper uses data provided by the manufacturer, absorbed solar radiation and cell temperature together with semi-empirical equations, to predict the current–voltage curve. This paper indicates how the parameters of the five-parameter model are determined and compares predicted current–voltage curves with experimental data from a building integrated photovoltaic facility at the National Institute of Standards and Technology (NIST) for four different cell technologies (single crystalline, poly crystalline, silicon thin film, and triple-junction amorphous). The results obtained with the Sandia model are also shown. The predictions from the five-parameter model are shown to agree well with both the Sandia model results and the NIST measurements for all four cell types over a range of operating conditions. The five-parameter model is of interest because it requires only a small amount of input data available from the manufacturer and therefore it provides a valuable tool for energy prediction. The predictive capability could be improved if manufacturer’s data included information at two radiation levels.

Abstract: This paper presents the latest versions of several models developed by the authors to predict short time-step solar energy and daylight availability quantities needed by energy system modelers or building designers. The modeled quantities are global, direct and diffuse daylight illuminance, diffuse irradiance and illuminance impinging on tilted surfaces of arbitrary orientation, sky zenith luminance and sky luminance angular distribution. All models are original except for the last one which is extrapolated from current standards. All models share a common operating structure and a common set of input data: Hourly (or higher frequency) direct (or diffuse) and global irradiance plus surface dew point temperature. Key experimental observations leading to model development are briefly reviewed. Comprehensive validation results are presented. Model accuracy, assessed in terms of root-mean-square and mean bias errors, is analyzed both as a function of insolation conditions and site climatic environment.

Abstract: Elevated summertime temperatures in urban ‘heat islands’ increase cooling-energy use and accelerate the formation of urban smog. Except in the city’s core areas, summer heat islands are created mainly by the lack of vegetation and by the high solar radiation absorptance by urban surfaces. Analysis of temperature trends for the last 100 years in several large U.S. cities indicate that, since ∼1940, temperatures in urban areas have increased by about 0.5–3.0°C. Typically, electricity demand in cities increases by 2–4% for each 1°C increase in temperature. Hence, we estimate that 5–10% of the current urban electricity demand is spent to cool buildings just to compensate for the increased 0.5–3.0°C in urban temperatures. Downtown Los Angeles (L.A.), for example, is now 2.5°C warmer than in 1920, leading to an increase in electricity demand of 1500 MW. In L.A., smoggy episodes are absent below about 21°C, but smog becomes unacceptable by 32°C. Because of the heat-island effects, a rise in temperature can have significant impacts. Urban trees and high-albedo surfaces can offset or reverse the heat-island effect. Mitigation of urban heat islands can potentially reduce national energy use in air conditioning by 20% and save over $10B per year in energy use and improvement in urban air quality. The albedo of a city may be increased at minimal cost if high-albedo surfaces are chosen to replace darker materials during routine maintenance of roofs and roads. Incentive programs, product labeling, and standards could promote the use of high-albedo materials for buildings and roads. Similar incentive-based programs need to be developed for urban trees.