Solar Load Ratio Research Articles

A Methodology to Assess the Suitability of Typical Meteorological Year Weather Data for Simulating the Performance of Buildings Conditioned Entirely by Ambient Energy

Abstract This study evaluates for the first time the suitability of typical meteorological year (TMY) weather data for simulating the performance of buildings that are entirely conditioned by ambient energy. A home in Durango, CO, was simulated with TMY data, with real data for 1998–2020 and with extreme meteorological year (XMY) data. For this climate, the indoor temperature in the house designed with TMY data drops below the range of comfortable indoor temperature (20–25 °C) for 16 of 23 years, including as low as 13 °C during 2008. With the thermal time constant of the house adjusted for each data set to maintain comfort, the required time constants for the real data ranged from 1.178 to 7.56 days with a mean of 3.14 and a median of 2.38, while the TMY value was 1.862 for a percentile rank of 0.318. XMY data did not produce significantly better results. The correlation of the time constant to weather parameters showed that the maximum interval during which the 24-h average solar load ratio remains below 1 is a promising index for identifying the most challenging year. Until more representative TMY and XMY weightings are developed for ambient-conditioned buildings across other climates, it is advisable that current TMY data are used only for preliminary design and that multi-year simulations are conducted for final design.

Hourly Electricity Price Prediction for Electricity Market with High Proportion of Wind and Solar Power

In an open electricity market, increased accuracy and real-time availability of electricity price forecasts can help market parties participate effectively in market operations and management. As the penetration of clean energy increases, it brings new challenges to electricity price forecasting. An electricity price forecasting model is constructed in this paper for markets containing a high proportion of wind and solar power, where the scenario with a high coefficient of variation (COV) caused by the high frequency of low electricity prices is particularly concerned. The deep extreme learning machine optimized by the sparrow search algorithm (SSA-DELM) is proposed to make predictions on the model. The results show that wind–load ratio and solar–load ratio are the key input variables for forecasting in power markets with high proportions of wind and solar energy. The SSA-DELM possesses better electricity price forecasting performance in the scenario with a high COV and is more suitable for disordered time series models, which can be confirmed in comparison with LSTM.

A Calibration of the Solar Load Ratio Method to Determine the Heat Gain in PV-Trombe Walls

The Trombe wall is a passive system used in buildings that indirectly transfers thermal energy to the adjacent environment by radiation and convection, and directly by the thermo-circulation that arises in the air cavity delimited between a transparent and an absorbing surface. Nevertheless, the latter is painted black to increase the energy gains, but this produces a negative visual impact and promotes the overheating risk in summer. To mitigate these aspects, a hybrid Trombe wall equipped with PV panels can be employed. The PV installation results in a more pleasing wall appearance and the overheating risk reduces because part of the absorbed solar radiation is transformed into electricity. To determine the actual performance of a such system, transient simulation tools are required to consider properly the wall thermal storage features, variation of the optical properties, air thermo-circulation, and PV power production. Alternatively, regarding the traditional Trombe wall, the literature provides a simplified empirical method based on the dimensionless parameter solar load ratio (SLR) that allows for preliminary evaluations and design. In this paper, the SLR method was calibrated to determine the monthly auxiliary energy to be supplied in buildings equipped with PV-Trombe walls in heating applications. The SLR method was tuned by a multiple linear regression by data provided by TRNSYS simulation that allowed to obtain the energy performances in actual conditions of PV-Trombe walls installed on the same building but located in different localities. The comparison between the TRNSYS results and the calibrated SLR method determined average errors ranging between 0.7% and 1.4%, demonstrating the validity of the proposed methodology.

Passive Cooling Load Ratio method

The method Passive Cooling Load Ratio (PCLR) is an innovative simplified method which calculates the monthly cooling energy needs of a thermal zone where passive cooling systems are installed using the variables: cooling energy load and passive cooling potential. This new method is based on the Solar Load Ratio (SLR) that was previously developed for solar heating systems. Although, PCLR was theoretically developed for any passive cooling system, here it is applied to passive cooling based on ventilation strategies. In addition, this paper presents its application to an office room ventilation using: (i) forced cooled air from an earth-to-air heat exchanger (EAHE) and (ii) natural induced air by a solar chimney from the EAHE. Correlations were obtained for those systems, using the parameters that describe the local climate, the system type and its dimensions. The numerical model used to obtain the correlation functions when one of the systems is installed, associates previously developed numerical models with 5R1C model of ISO 13790. However, the PCLR method can be used to accurately estimate the cooling energy needs without using complex models for simulation. The error for all systems does not overcomes 5.2%, which is an acceptable variation for a simplified method.

Solar Load Ratio and ISO 13790 methodologies: Indirect gains from sunspaces

This paper reviews and analyzes the compatibility of the simplified empirical method based on the dimensionless parameter of Solar Load Ratio (SLR) and the monthly procedure of the standard ISO 13790 for indirect gains, specifically for unconditioned zones adjacent to a conditioned zone, but separated from it by a partition wall (sunspaces).The main contribution of the work presented here is the new formulation to account SLR correlations in ISO 13790, obtained for sunspaces, but generalizable for other solar systems with known SLR functions.Simulation models are used to perform a sensitivity analysis of internal gains and heat transfer through solar collector surfaces, both issues that distinguishes ISO 13790 from Load Ratio methods. The analysis shows that internal gains can be added to the heat source term or subtracted to heat transfer term without influencing the utilization factor dependence with the gain-to-loss ratio. On the other hand, the SLR assumption that solar collector surfaces are neutral elements and, therefore, not added to the heat transfer term, results in large inconsistencies between SLR and ISO 13790 methods.The detailed monthly methodology of ISO 13790 fairly reproduces results obtained by simulation. However, predictions from the simplified monthly methodology of ISO 13790 fail in mid season months and coldest months.

Electrical energy saving in a passive-solar-heated residence using a direct gain attached sunspace

This paper deals with the thermal analysis and the auxiliary electrical energy saving in a passive-solar-heated residence. The particular residence is using an attached sunspace of inclined walls and roof and an electrically heated thermal storage floor as backup to satisfy the heating requirements. The thermal analysis and the corresponding electrical energy saving are determined using three different methods which are applied for thermostatically controlled temperature regime. The first is a simplified method based on three parameters: (1) the solar/load ratio (SLR), (2) the building thermal inertia and (3) the monthly unutilizability (UU). The other methods are, namely: the UU method and the SLR method.

Solar Heating Systems Design Procedure for Greenhouse With Internal Collection and Sensible Heat Storage

A simplified design procedure for solar heating systems for greenhouses is presented. Computer modeling and simulations were carried out to analyze the effects of design variations in greenhouse construction and storage characteristics on long-term average system thermal performance. The key performance indices were defined in terms of the total solar contribution and solar heating fraction. The results of many simulations were transformed into correlations between monthly solar load ratio and the performance indices. Knowing monthly average meteorological data, designers and engineers can readily extract the necessary technical information for subsequent economic analysis to select the most cost-effective solution for a given design problem.

A linear model for passive solar calculations: Evaluation of performance

A simple linear model for passive solar evaluations is presented, which is based on the equations for the dynamic behaviour of building elements and two thermal balance equations, one for the day and one for the night. For direct gain systems, the results of the model are shown to be in good agreement with the results of a comprehensive computer model. The influence of the distribution of solar load ratio is discussed and it is shown that if, in place of monthly temperature and radiation averages, seasonal averages of characteristic days are used, the accuracy of the calculation can be improved while the simplicity of the monthly method is retained.

Scaling relations for the performance of passive systems

From the correlation curves of the monthly solar heating fraction (SHF) as a function of monthly solar load ratio (SLR) for six different passive systems, it is empirically demonstrated that the annual SHF is well correlated with January SHF; this correlation is essentially independent of the passive type but dependent on location (climate). It is then shown mathematically that this is equivalent to the following scaling relation: the monthly SHF as a function of the monthly SLR is the same for all passive systems up to a scale factor of SLR. This scale factor depends on the passive system and has important physical relevance. The approximate validity of this scaling law is discussed. The simplification of performance prediction resulting from such a scaling law, as well as from the correlation of annual versus January performances, is pointed out.

Analytic model for passively-heated solar houses—1. Theory

A simple analytic method for the prediction of the long-term thermal performance of passively-heated solar houses is presented. The treatment includes a new coarse method for “energy bookkeeping” and the use of a distribution function which represents the frequency of occurrence of different values of the solar load ratio. Due to its generality, this formalism is applicable to any passive heating element. As specific examples, the cases of direct gain and water wall houses are treated in detail. Relative to the parameterization of computer simulation results, this method offers the user a design tool that can be used to predict, in closed form, the thermal effect on the house of different building and climatic parameters and is not restricted to a “reference” building. Agreement with published numerical simulation results in satisfactory. The presentation is divided into two separate papers: a users guide for the reader who may not be interested in the details of derivation and validation, and the present paper, in which the theory is presented in detail.

Prediction of direct gain solar heating sytem performance

General design methods for building-integrated (passive) solar heating systems are needed to evaluate the effects of design parameters on building energy needs. The solar Load Ratio Method[1] for direct gain systems is limited in the scope of system parameters which can be considered; it does not allow an examination of the effects of house capacitance, allowable room temperature swing, or alternative high and low room thermostat set point temperatures. In this paper, we present a more general design method for direct gain systems.

Correspondence between solar load ratio method for passive water wall systems and f-Chart performance estimates

A simple correspondence is demonstrated between passive solar system performance and active system f-Chart estimates. The equations describing a thermal network model of a passive water wall solar system are compared term by term with similar equations governing the heat balance in an active solar heating system, making possible an identification of appropriate passive system parameters with active system parameters comprising inputs to the f-Chart procedure. Comparisons of f-Chart predictions and results using the Solar Load Ratio method are made for sample cities in sixteen climatic zones. Results indicate a discrepancy of at most about 9 per cent solar fraction between the two methods in the cases studied.