A typical meteorological day (TMD) approach for predicting the long-term performance of solar energy systems

A method for predicting the long-term performance of solar energy systems, based on the analysis of system performance for one particular day—the typical meteorological day (TMD)—is presented. The TMD is constructed from the cumulative time distribution of insolation values on the collector aperture. The TMD method requires little calculational effort and a small data base relative to standard yearly computer simulations. Good agreement is found between the predictions of the new method and the corresponding results of the -f-chart method. The TMD method is of particular value for cases that may often be treated inaccurately by simple calculational methods: (1) high threshold problems; (2) systems with short response times (e.g., due to small storage); and (3) systems in which collectors other than flat plates are used (the method is applicable to all solar collector types).     

Mira: A one-repetitive day method for predicting the long-term performance of solar energy systems

A new, one-repetitive day simulation method, named MIRA, has been developed for predicting the long-term performance of a wide variety of solar energy systems. Compared to detailed hourly computer simulations, MIRA requires little computational effort and climatic data bases, while offering comparable accuracy. In the MIRA simulation method, the daily solar radiation profile incorporates both random fluctuations and an inherent time-of-day dependence. Satisfactory agreement between the long-term system performance predictions of the new method and corresponding detailed hourly simulations is demonstrated. The range and magnitude of the predictive accuracy of MIRA and other one-repetitive day methods are illustrated. Their usefulness in sensitivity studies and comparative evaluations of different solar system configurations and control strategies is also discussed.     

Determining typical weather for use in solar energy simulations

Predicting the performance of a solar energy system by using simulation methods requires weather data input for the locality involved. The present paper describes a method of analyzing an optional number of years of weather data for a chosen month resulting in a “typical week” which is characterized in terms of solar radiation, ambient dry bulb temperature and wind speed. The “typical week” is allowed to vary in length between 5 and 10 days in the analysis in order to enable selection of a period that best represents a given month according to specified criteria.Verification of the method by comparative computer analysis was performed using two forms of weather data as inputs to the solar energy program “TRYNSYS”. The averaging method when compared to the “typical” weather method resulted in differences of less than 7 per cent.The use of “typical” weather appears to give results at least comparable with more established methods while at the same time providing a broad spectrum of the weather typical of an area. The use of “typical” weather can result in savings in computer time.     

A new method to develop typical weather years in different climates for building energy use studies

Principal component analysis of 30-year long-term meteorological variables was conducted. Typical principal component years (TPCYs) were determined for Harbin, Beijing, Shanghai, Kunming and Hong Kong representing the five major architectural climates across China: severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. In each climate zone, the TPCY was compared with the 30 individual years and the widely used typical meteorological year (TMY). The monthly principal component and the predicted total building energy consumption based on the TPCY and TMY were very close to the 30-year long-term mean estimation. TPCY for the 21st century in each of the five cities was also identified using predictions from general climate models. The TPCY approach is a good alternative to the TMY method. Firstly, predicted building energy use from TPCY is closer to the long-term estimation than that from the TMY in different climates. Secondly, because only monthly data are considered, the development of TPCY is much simpler and less time-consuming. This would have important applications in the regular updating of typical weather years for building energy studies and in the assessment of the impact of climate change on energy use in the built environment.     

A new look at the long-term performance of general solar thermal systems

This work addresses the problem of evaluating the long-term performance of solar thermal systems, which is quantified through the monthly or seasonal/annual solar fraction. It is shown that for a general solar system it may be expressed as a function of monthly utilizabilities, calculated for two different temperature (radiation) levels, which correspond to minimum and maximum operating temperatures. Both systems without storage and with storage are considered. Examples for solar cooling and solar cogeneration systems are shown.     

A simplification of weather data to evaluate daily and monthly energy needs of residential buildings

Hourly, daily, monthly and annual heating and cooling requirements of a residential building located in Ottawa, Ontario, Canada were estimated, employing ENERPASS as the energy simulation tool, and performing hour-by-hour energy analysis. The following weather data were employed:

1. (i) Ten years (1967–1976) of weather data. The ten-year average of the results is identified as TYA.

2. (ii) A typical meteorological year (TMY) generated using the same ten years of data.

3. (iii) Two different hourly ambient air temperature distributions (T1 and T2) for a typical day in each month. The solar radiation on each surface was estimated using the mean monthly clearness index.

The house use patterns, including heat generation and the thermostat setting, were taken the same when using TYA, TMY, T1 or T2. The analysis was carried out for the house as it is (well insulated and airtight), and for two modifications: one with larger infiltration rate and lower wall thermal resistance, and the other with larger south-facing window area and using super-windows. The results of this study show that the long-range hourly, daily, monthly and annual heating and cooling requirements of a residential building located in a cold climate can be predicted by employing mean daily maximum and minimum temperatures and the mean monthly clearness index for each month. This amounts to substantial savings in computational costs, in either using many years of weather data or generating a TMY for the site. For locations lacking detailed hourly weather data, the use of data and the procedure outlined in this study may be employed to predict the long-range thermal performance of simple residential buildings.     

A general design method for closed-loop solar energy systems

A general design method is presented for closed loop energy systems consisting of solar collectors, sensible energy storage and a closed-loop flow circuit in which thermal energy is supplied (through heat exchange) to a load above a specified minimum temperature. It is assumed that the energy supplied to the load is used at a constant thermal efficiency. Computer simulations were used to estimate the long-term thermal performance of these systems, and correlations between the system performance and the system design parameters, such as the collector characteristics, load size, climatic data, and the minimum useful temperature, are presented.     

A finite-difference method to evaluate the thermal performance of a solar water heater

The theoretical performance of a solar water heater operating under thermosiphon-flow conditions was evaluated using a finite-difference solution procedure. Tests were conducted on an experimental heater which incorporated a flat-plate collector design. Experimental water mass flow rates were measured at half-hour intervals using a dye-injection method while the temperature distribution of the system was monitored continuously. Some defects in the theory arising from inaccurate assumptions of the mean temperatures of the various components of the system are pointed out. Fortunately, these defects are significant only during the early and late periods of the day. Throughout the main insolation period, satisfactory qualitative and quantitative agreement can be obtained between experimental and theoretical results. A proposal for future study to investigate the reverse-flow phenomena is introduced.     

A simplified method to evaluate the seasonal energy performance of water chillers

The calculation or certification of the energy consumption of buildings equipped with refrigerating or heating units operating on vapour compression cycles requires an accurate evaluation of their performance at full and part load under different operating conditions. Refrigeration systems simulation models are normally useless because of the large amount of input data required for a full characterization.A simplified numerical method for the performance prediction of vapour compression heat pumps and chillers is here presented, based only on performance data at the nominal rating conditions. The proposed procedure was validated against experimental data of different packaged air-cooled water chillers, operating on scroll compressors. In chillers full load conditions approximately 89.5% and 92.1% of the predicted EER and cooling capacity values respectively are consistent with the measured data within a relative deviation of ±10%. Simulation results are in good agreement with the experimental ones also if the experimental seasonal energy efficiency ratio, SEER_on, described in the European standard draft prEN 14825, is considered. The deviations range from ?3.2% to +5.1%. The proposed mathematical model appears to be a reliable tool to be implemented into dynamic building-plant energy simulation codes or into building energy certification tools.     

A new method to evaluate the performance of slime water treatment

Slime water is used repeatedly and its treatment is very essential in coal preparation plants. A new method called fractal dimension is proposed to evaluate the performance of slime water treatment. According to settling experiments, the settling process of slime water can be divided into two phases. In the first phase, water hardness is less than 50 DH° and settling velocity is fast. In the second phase, the water hardness is over 50 DH° and settling velocity is slow. Under different water hardness levels, the variation trends of the luminosity of the supernatant liquor, settling velocity, and fractal dimensions are consistent.     

A method for predicting long-term average performance of photovoltaic systems

A method for predicting the long-term average conventional energy displaced by a photovoltaic system comprising of a photovoltaic array, a storage battery, some power conditioning equipment with maximum power tracking capability and an auxiliary power facility, is described. System simulation is done over the average day of the month. Average hourly energy flows are estimated from a knowledge of array test parameters, monthly average hourly ambient temperature and monthly average daily hemispherical radiation. The monthly average diffuse component of radiation can be predicted from the hemispherical radiation by the use of an appropriate empirical correlation relating the monthly average diffuse fraction to monthly average clearness index. Hourly average radiation values are estimated from daily values using a statistical model. The condition that there should be no net battery energy gain during the average day enables the correct setting of the battery energy level at the beginning of the day. For a given hourly load profile, for example a constant 24 h-per-day load, a chart relating annual solar fraction with array and storage battery size, for a given location and set of array test parameters, can be plotted as a basis for design and economic optimisation of the system.     

Probabilistic analysis of weather data for a hybrid solar/wind energy system

In this paper, a procedure for the probabilistic treatment of solar irradiance and wind speed data is reported as a method of evaluating, at a given site, the electric energy generated by both a photovoltaic system and a wind system. The aim of the proposed approach is twofold: first, to check if the real probability distribution functions (PDFs) of both clearness index and wind speed overlap with Hollands and Huget and Weibull PDFs, respectively; and then to find the parameters of these two distributions that best fit the real data. Further, using goodness‐of‐fit tests, these PDFs are compared with another set of very common PDFs, namely the Gordon and Reddy and Lognormal functions, respectively. The results inform the design of a pre‐processing stage for the input of an algorithm that probabilistically optimizes the design of hybrid solar wind power systems. In this paper, the validity of the proposed procedure was tested using long‐term meteorological data from Acireale (Italy). Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation and selection of energy storage systems for solar thermal applications

Energy storage is one of the key technologies for energy conservation and therefore is of great practical importance. One of its main advantages is that it is best suited for solar thermal applications. This study deals with a comprehensive discussion of the evaluation and the selection of sensible and latent heat storage technologies, systems and applications in the field of solar energy. Several issues relating to energy storage are examined from the current perspective. In addition, some criteria, techniques, recommendations, checklists on the selection, implementation and operation of energy storage systems are provided for the use of energy engineers, scientists and policy makers. Copyright © 1999 John Wiley & Sons, Ltd.     

A statistical method to evaluate urban energy needs

The statistical method proposed to evaluate urban energy needs, utilizes a numerical map to extend to the universe of the evaluation obtained from a probability stratified simple random sampling design with the optimum allocation of sample buildings to the strata. The strata considered refers to age of buildings. We checked two correlations over the real surveyed sample buildings and the numeric map sample buildings. The correlations are utilized to evaluate the energy needs of the urban universe of building. The proposed method can be useful for the territorial energy programming using energy needs maps of the urban settlements, as a tool for rational use and save of energy. © 1997 by John Wiley & Sons, Ltd.     

A new method for testing the performance of flat-plate solar collectors

In this study, a new method is proposed for determining the thermal performance parameters of a flat-plate water heating collector. A parametric identification principle is applied to a mathematical model of the collector operating in a real system. The advantages of the method are that it does not need a sophisticated testing system, it avoids the problem of regulating the inlet fluid temperature (which must be held constant during the tests in the standard procedures) and a cloudless sky is not essential. Solar radiation of 600 W m⁻² was chosen as a threshold to start experiments. Applied to a flat-plate collector with a single-glazed cover, the proposed method gave satisfactory results for the determination of its thermal performance coefficients. To verify the adequacy of the present method, it was used to predict the outlet fluid temperature. The results indicate a satisfactory agreement between predicted and measured values with a correlation coefficient of 0.99 and an error of 0.4%. We propose that performance results will be presented as a technical sheet showing collector features and accompanied with a curve giving the correlation between estimated and measured output temperature of the collector fluid.     

The level of complexity needed for weather data in models of solar system performance

Intuitively one decomposes climate variables such as solar irradiation and ambient temperature into their deterministic and stochastic components. The deterministic component comprises a sum of contributions at various frequencies, thereby defining the climate of the location. The stochastic component comprises the fluctuations about this component, giving the day-to-day weather variations. Boland (Solar Energy 60(6) (1997) 359) shows that on a day-to-day basis both components must be included in building thermal performance simulations to give sensible results. It is shown in this paper that on an hour-to-hour basis the stochastic component may be disregarded in building thermal, solar process heat and photovoltaic system performance without significantly affecting the results. Since the hourly stochastic component of the solar irradiation is very difficult to model, this result greatly simplifies the construction of synthetic climate data sets.     

A new method for estimating solar radiation from bright sunshine data

Daily values of H/H₀, the ratio of total horizontal radiation to that outside the atmosphere has been correlated with s/S, bright sunshine as a fraction of daylength for 3 yr measurements in Adana and Ankara, Turkey. Using a maximum-likelihood quadratic fit, we show that monthly averages s/S and its standard deviation σ_s/S can be used to estimate the monthly average H/H₀ as

H/H₀ = 0.204 + 0.758s/S − 0.250[s/S² + σ²_s/S.

Comparison of the estimations of the above equation with measurements from different regions of Turkey indicate that less than 5 per cent relative error is possible. A further correlation σ²_s/S with s/S makes it possible to estimate H/H₀ with just the knowledge of s/S.     

An approach to evaluate the energy advantage of two axes solar tracking systems in Spain

The present work shows an alterative method for determining the tracking energy advantage, defined as the additional electrical energy produced by two axes tracking systems respect to fixed devices, in order to analyze the economical profitability in Spain. For this purpose, 52 main cities of this country have been analyzed. The proposed methodology starts from irradiation data, combining diffuse models and daily–hourly relations. Different types of losses have been evaluated, and the electrical behavior of the systems has been incorporated. Final annual energetic results demonstrate that two axes devices show a relevant energy advantage (higher than 20%) for most of the national territory.     

A presentation of solar irradiation data suitable for solar energy application

Temporal global solar radiation patterns are discussed for two climatically different U.S. stations (Phoenix, Arizona and Geneseo, New York). A concept of the solar utilization season is developed along with methodology to assess the frequency of periods of consecutive days when solar irradiation values do not attain specified threshold values. This analysis is considered more appropriate in applications of solar energy than the common use of means and assumed Gaussian data properties that can be obtained from several compilations and summaries of national solar irradiation data.