Perez Model Research Articles

Enhancement of ultrasonic-assisted and agitation-assisted flaxseed oil extractions: Kinetic modeling and optimization

The flaxseed oil extraction process has been investigated and enhanced by applying Ultrasonic-Assisted Extraction (UAE), and Mixer-Assisted Extraction (MAE) methods in this study. Response Surface Methodology (RSM) was also utilized to find the optimal values of the extraction parameters. The optimal conditions for UAE were determined to be 42.7 min extraction time, 0.283 mm particle size, and 2.48 W/mL power intensity, achieving the oil yield of 94.56 %. For MAE, the optimal conditions were 54.5 min extraction time, 0.274 mm particle size, 21.1 °C temperature, and 0.74 W/mL agitation intensity, resulting in the oil yield of 96.73 %. RSM showed high reliability with R2 values above 0.99 for both methods. Gas Chromatography Flame Ionization Detector (GC-FID) analysis revealed that UAE and MAE resulted in higher unsaturated fatty acids concentrations (85.8 % and 86 %, respectively) compared to CPE (78.2 %). Kinetic studies indicated that UAE and MAE are more efficient in extracting unsaturated fatty acids, with MAE showing the highest double bond content. The Kinetic models demonstrated that extraction kinetics were controlled primarily by solid-phase resistance, with the washing coefficients being significantly higher than the diffusion coefficients. The Perez model calculated diffusion coefficients of 8.03 × 10⁻12 m2/s for UAE and 1.41 × 10⁻11 m2/s for MAE, activation energies of 16.44 kJ/mol for UAE and 15.64 kJ/mol for MAE.

Examining grid-forming inverters for power restoration using power-hardware in-the-loop and Digital Twins approaches with Real-time Digital Simulation

The current pursuit of ambitious decarbonization targets is driving a swift transformation of the power grid, marked by a surge in the production of renewable energy. The expansion on application of renewable energy hinges significantly on Distributed Energy Resources but system operators are grappling with challenges due to the opaque nature of DER operations. This opacity introduces considerable risks to grid stability, as the burgeoning volume of DERs may surpass the existing power network’s capacity. In response, the advent of Digital Twins (DT) technology offers a viable remedy by creating virtual counterparts of the physical grid infrastructure that necessitate transmitting minimal data. Digital Twins technology circumvents the hindrances associated with real-time data flows and bolsters the transparency of the system. To foster widespread implementation of DT within the sector, it is imperative to cultivate and validate its application through practical trials. To this end, Power Hardware-in-the-Loop (PHIL) experiments are employed to juxtapose the efficacy of actual power components against that of the DT models. The experiments involve connecting Grid-forming Inverter to a Real-time Digital Simulator (RTDS) for PHIL and DT testing, allowing for an in-depth analysis of the behaviour of photovoltaic inverter. This paper elucidates a platform engineered for immediate simulation tailored to DT and PHIL approaches. This platform is designed to prototype, exhibit, and evaluate grid-forming inverters under different scenarios that are critical for power restoration. With the help of simulation exchange, Perez Model is recommended to add in the DT model to increase the accuracy comparing with the PHIL model. The entire restoration process can therefore be comprehensively represented and analysed.

Effect of adjusting orientation for solar energy applications in multiple climatic zones

South-facing collectors are the optimum choice for solar applications in the northern hemisphere. However, obstacles may limit the feasibility of this orientation. Therefore, altering the orientation of the collector impacts solar insolation. In this study, the Perez model is utilized to evaluate incoming solar radiation on tilted surfaces for solar collectors in four climatic zones across Pakistan. The results are presented in contour plots to analyze the optimal tilt and orientation for solar applications. The findings of the study indicate substantial energy gains when collectors are placed at optimum angles. More specifically, Quetta leads with a 14.54% increase, followed by Karachi and Multan at 9.81% and 9.3%, respectively, compared to horizontally placed collectors. Analysis of vertical surfaces reveals a notable decrease in monthly solar radiation, especially in Peshawar (37.22%). Monthly adjustments in tilt angles outperform fixed positions, enhancing solar energy intensity. When comparing yearly adjustments with monthly adjustments, Quetta shows the maximum increase of 5.92%, followed by Karachi (4.86%), Multan (4.01%), and Peshawar (3.65%). It is also observed that ±15° azimuth angle change from the south ensures receiving up to 98% of insolation, regardless of the climatic region. Lastly, the validation against the NASA SSE database further highlights the reliability of our simulation model. Overall, the outcomes of the study will contribute to informed solar energy planning in the studied regions.

Viscoelastic-damageable behavior of sheet molding compound (SMC) composites

The variability of microstructures in the SMC composite induced by the manufacturing process is very important. The volumetric fraction and reinforcement orientation distribution significantly affect the material’s mechanical properties in both the elastic and nonlinear phases, associated with the development of damage phenomena. The distribution of local stresses between the reinforcements and the matrix is conditioned by the privileged orientation of the reinforcements. This, in turn, influences both the elastic mechanical properties and the degradation mechanisms, resulting in a degree of anisotropy. Additionally, SMC composites typically exhibit viscoelastic-damageable behavior. Therefore, it is necessary to characterize the microstructure accurately and comprehensively to effectively manage the mechanical behavior and damage of SMC structures. The research process involved investigating the viscoelastic behavior of randomly oriented Sheet Molding Compound (SMC) composites using Dynamic Mechanical Analysis (DMA) in the glass transition zone. By conducting a thorough analysis of the frequency and temperature-dependent behavior of the viscoelastic material, the experimental results obtained from the DMA test have been modeled. To demonstrate the effect of the matrix, two types of SMSs were utilized: standard SMC and Advanced SMC (A-SMC). The Cole-Cole experimental results fit well with the Perez model showing deformed semi-circles denoting the heterogeneity of the material system used in this study. The aim of this study is to link the WLF Law to the Perez model near the transition zone. The results demonstrated that dynamic properties can be plotted against temperature due to the strong correlation between the experimental and numerical data. Additionally, an increase in the strain rate results in a shift in the damage threshold and a reduction in damage kinetics. These effects are directly related to the damage thresholds and kinetics at the fiber-matrix interface.

Development of a hybrid timber and aluminum based unitized façade system resilient to the future weather conditions in Europe via monitoring campaigns and computational models

The StaticusCare project aims to develop a hybrid timber and aluminum unitized façade system (HUF) equipped with a predictive maintenance system (PMS) for Nordic climates, which will be based on the digital twin concept and fed by an Internet-of-Things system. The use of timber in the structure elements of the façade system aims to reduce the typical system's CO2 footprint by 70–75 %, and the non-renewable energy consumption by 53–56 %. Nonetheless, ensuring that this novel system is durable in the Nordic current and future climate conditions is necessary. For this purpose, the HUF system will be installed in a two-floor building, monitored by a multi-sensor campaign, and replicated computationally to assess the energy use and indoor environmental quality, as well as the hygrothermal performance of the building elements for contemporary climate and under various climate change scenarios. The maintenance of the buildings with the façade system installed will be based on a PMS that is backed by an open-source python heat, air, and moisture transport (HAM) software. This one-dimensional software will be validated using a commercial one. To analyze specific problems, such as air infiltration and moisture entrapment, a two-dimensional HAM model will also be developed. In addition, building energy simulations will be performed to test several parameters affecting the indoor climate quality and energy use. Finally, the current outdoor weather files for the HAM simulations will be built based on multi-year datasets following the ISO 15927-4 methodology and the Perez model, whilst the future weather files will be based on multi-year datasets following the same methodology for two future scenarios. This multi-step methodology will allow to thoroughly test and design the HUF façade system whilst minimizing the risk, e.g., mold growth, for current and future conditions.

High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning

Spatiotemporal assessment of solar potential is one of the most promising solutions to find suitable locations for future photovoltaic systems’ placement. However, accurate assessment of solar potential on large areas can be challenging due to missing data or computational complexity. In this paper, a fully convolutional neural network based method for high-resolution spatiotemporal assessment of solar potential by using remote sensing data is presented. The method is trained and validated on the area of 32 km2 of the Maribor city, Slovenia, and tested on the 6 different locations in Slovenia and Germany. The proposed method was tested against the simulation algorithm, which utilized isotropic Liu Jordan diffuse model or anisotropic Perez model with sky view factor based shading. On average, a normalized root mean square error (NRMSE) of 6.06% and mean absolute percentage error (MAPE) of 4.29% was achieved in test locations against the simulation based on Liu-Jordan model. When training the fully convolutional neural network models against the ground truth, generated with more advanced Perez diffuse model, the average NRMSE was 8.37% and MAPE of 10.90% was achieved across all test locations. Additionally, it was shown that the proposed method can assess solar potential in high-resolution from the input in lower resolution with higher accuracy than the simulation algorithm, while being up to 1500-times faster.

A continuous form of the Perez diffuse sky model for forward and reverse transposition

The Perez 1990 transposition model has emerged as the preferred choice for estimating global tilted irradiance, also known as plane-of-array irradiance. One notable drawback is the Perez model’s reliance on empirical coefficients assigned to discrete bins of the sky clearness parameter, resulting in discontinuities in the calculated tilted irradiance. In this study, we present a novel method to eliminate the discontinuities of the Perez model by replacing the empirical look-up table with a set of six quadratic splines. This is facilitated by transforming the unbounded sky clearness parameter (epsilon) to an equivalent bounded parameter (zeta).Transposition using the original Perez model and continuous Perez–Driesse model are compared for multiple orientations at two locations. The two models produce very similar deviation statistics, meaning the continuous version can be used as a plug-in replacement for the original. Reverse transposition is demonstrated using the Perez–Driesse model together with a new continuous version of the Erbs diffuse fraction model and a simple bisection solution search. This combination achieves a substantially higher success rate than the GTI-DIRINT algorithm in our tests.

Novel GPU-accelerated high-resolution solar potential estimation in urban areas by using a modified diffuse irradiance model

In the past years various methods have been developed to estimate high-resolution solar potential in urban areas, by simulating solar irradiance over surface models that originate from remote sensing data. In general, this requires discretisation of solar irradiance models that estimate direct, reflective, and diffuse irradiances. The latter is most accurately estimated by an anisotropic model, where the hemispherical sky dome from arbitrary surface’s viewpoint consists of the horizon, the circumsolar and sky regions. Such model can be modified to incorporate the effects of shadowing from obstruction with a view factor for each sky region. However, state-of-the-art using such models for estimating solar potential in urban areas, only considers the sky view factor, and not circumsolar view factor, due to high computational load. In this paper, a novel parallelisation of solar potential estimation is proposed by using General Purpose computing on Graphics Processing Units (GPGPU). Modified anisotropic Perez model is used by considering diffuse shadowing with all three sky view factors. Moreover, we provide validation based on sensitivity analysis of the method’s accuracy with independent meteorological measurements, by changing circumsolar sky region’s half-angle and resolution of the hemispherical sky dome. Finally, the presented method using GPPGU was compared to multithreaded Central Processing Unit (CPU) approach, where on average a 70x computational speedup was achieved. Finally, the proposed method was applied over a ∼21km2 urban area, obtained from Light Detection And Ranging (LiDAR) data, where the computation of solar potential was performed in a reasonable time.

A transferable turbidity estimation method for estimating clear-sky solar irradiance

A transferable turbidity estimation method is proposed for estimating the turbidity and clear-sky solar irradiance. Instead of using on-site irradiance measurements (i.e., the local model), a transferable model is developed involving stations with sufficient information, and then applied at locations with limited data availability. Compared with the local method, the transferable model yields results with slightly higher discrepancies regrading normalized root mean squared error (nRMSE, 2.80% vs 2.75%). When compared with the Ineichen–Perez (PVLIB) model, the nRMSE of clear-sky global horizontal irradiance (GHIcs) estimation is reduced from 4.99% to 2.44%, and the normalized mean bias error (nMBE) is improved from -3.37% to 0.57%. The GHIcs estimation is comparable with physical models (i.e., McClear and REST2), where the McClear produces a nRMSE of 3.32% and the nMBE is 2.10%, while the REST2 generates results with an nRMSE of 2.55% and an nMBE of 1.30%. We further compare aforementioned models for day-ahead GHIcs forecasts using a day persistent way. GHIcs forecast from the transferable method has slightly lower discrepancies of nRMSE and nMBE than the physical models. Considering the complexity of physical models, the transferable turbidity estimation method with comparable performance demonstrates valuable potential for solar resourcing and forecasting applications.

Evaluation of the technical and economic aspects of solar photovoltaic plants under different climate conditions and feed-in tariff

In order to meet the energy demand and reduce the environmental pollution, it is necessary utilize photovoltaic (PV) module to produce electrical energy. There are many factors such as solar radiation, PV module material, wind energy, soiling factor, shading effect, geographical location, cell temperature is affecting the performance of the PV module. In this context, the performance of the multi crystalline based two PV plants has been examined. In this work, test is carried out in two solar plants installed at Kastoria, Greece (500kW, ground mounted) and Kocaeli, Turkey (110kW, roof mounted) and the results are compared with PVSYST software simulation results. From the results, it is found that the temperature losses for Kastoria and Kocaeli plants are obtained as 7.9% and 7.6% respectively. This leads to increase the performance ratio of 79% and 72.2% for Kastoria and Kocaeli plants respectively. Similarly, the maximum energy output is obtained for PVGIS database for all three models (Liu Jordan model, Hay Davies model and Perez model). The Internal Rate of Return for Kocaeli plant is 7.08% and for Kastoria plant is 6.71%. In addition, the Net Present Value for Kastoria and Kocaeli plant is obtained as 821900€ and 174072€ respectively.

Evaluation of solar radiation models on vertical surface for building photovoltaic applications in Beijing

Building photovoltaic (PV) may provide a growing share of electricity for big cities. However, lack of measured radiation data on vertical surface remains a critical problem for building PV deployment. With the development of urbanization and industrialization, high aerosol load is altering the nature of solar radiation in Beijing. Hence, ten in-plane solar radiation models are reviewed to choose optimal model for calculating solar radiation on vertical surface in such high turbidity area. At the same time, the effect of atmospheric turbidity on the model accuracy is revealed for further understanding on the optimal model. To give general suggestion on model selection, the performance of the ten models for each weather type is tested based on new method of weather type classification. Finally, solar resource on vertical surface and output energy of building PV system are evaluated by the optimal model to guide building PV deployment. The results indicate that Perez model is suitable to calculate solar radiation on vertical surface in high turbidity area. High atmosphere turbidity will cause Perez model inaccurate. Model selection can be made by the status of atmospheric transmittance. It is feasible to apply building PV in Beijing with AC output energy of 630–971 kWh/kWp/year.

Design of wind and solar energy supply, to match energy demand

Renewable energy sources have an intermittent character that does not necessarily match energy demand. Such imbalances tend to increase system cost as they require mitigation measures and this is undesirable when available resources should be focused on increasing renewable energy supply. Matching supply and demand should therefore be inherent to early stages of system design, to avoid mismatch costs to the greatest extent possible and we need guidelines for that. This paper delivers such guidelines by exploring design of hybrid wind and solar energy and unusual large solar installation angles. The hybrid wind and solar energy supply and energy demand is studied with an analytical analysis of average monthly energy yields in The Netherlands, Spain and Britain, capacity factor statistics and a dynamic energy supply simulation. The analytical focus in this paper differs from that found in literature, where analyses entirely rely on simulations. Additionally, the seasonal energy yield profile of solar energy at large installation angles is studied with the web application PVGIS and an hourly simulation of the energy yield, based on the Perez model. In Europe, the energy yield of solar PV peaks during the summer months and the energy yield of wind turbines is highest during the winter months. As a consequence, three basic hybrid supply profiles, based on three different mix ratios of wind to solar PV, can be differentiated: a heating profile with high monthly energy yield during the winter months, a flat or baseload profile and a cooling profile with high monthly energy yield during the summer months. It is shown that the baseload profile in The Netherlands is achieved at a ratio of wind to solar energy yield and power of respectively E w / E s = 1.7 and P w / P s = 0.6 . The baseload ratio for Spain and Britain is comparable because of similar seasonal weather patterns, so that this baseload ratio is likely comparable for other European countries too. In addition to the seasonal benefits, the hybrid mix is also ideal for the short-term as wind and solar PV adds up to a total that has fewer energy supply flaws and peaks than with each energy source individually and it is shown that they are seldom (3%) both at rated power. This allows them to share one cable, allowing “cable pooling”, with curtailment to -for example-manage cable capacity. A dynamic simulation with the baseload mix supply and a flat demand reveals that a 100% and 75% yearly energy match cause a curtailment loss of respectively 6% and 1%. Curtailment losses of the baseload mix are thereby shown to be small. Tuning of the energy supply of solar panels separately is also possible. Compared to standard 40° slope in The Netherlands, facade panels have smaller yield during the summer months, but almost equal yield during the rest of the year, so that the total yield adds up to 72% of standard 40° slope panels. Additionally, an hourly energy yield simulation reveals that: façade (90°) and 60° slope panels with an inverter rated at respectively 50% and 65% Wp, produce 95% of the maximum energy yield at that slope. The flatter seasonal yield profile of “large slope panels” together with decreased peak power fits Dutch demand and grid capacity more effectively.

Benchmarking clear sky and transposition models for solar irradiance estimation on vertical planes to facilitate glazed facade design

The present study aims to benchmark the models utilized for estimating the solar irradiance on vertical planes that can facilitate the determination of critical conditions, which are utilized in the glazed facade design. Accordingly, in the first part of the study, the performance of PVGIS databases for Europe for estimating the solar irradiance components on the horizontal surfaces is compared with the on-site measurements at Bolzano airport (Italy). It is demonstrated that PVGIS-SARAH estimates both the global and diffuse solar irradiance components, compared to on-site measurements, with an acceptable error range (± 2–5%). The accuracy of isotropic and anisotropic transposition models is then compared for the same location, which demonstrates that the isotropic model tends to underestimate the global vertical incident irradiance by 6–12% of the daily peak value, while an agreement between the estimations of the anisotropic Perez model and the measurements is observed.Next, the performance of Ineichen, Solis and SPECMAGIC clear sky models, transposed with anisotropic Perez model, have been assessed utilizing field measurements on vertical facades at four different locations in Europe. The broadband version of Solis clear sky model, transposed with anisotropic Perez model, demonstrates R2 scores between 0.85 to 0.95 for the considered locations, indicating that this approach can be utilized as an alternative to open-source/commercially available data sources to estimate the solar irradiance on vertical facades. Finally, for the case study of a triple glazing system, comparing the surface temperatures obtained employing the latter approach with those determined using other commonly utilized irradiance data sources shows a discrepancy of up to 7 °C.

Diffuse irradiance on tilted planes in urban environments: Evaluation of models modified with sky and circumsolar view factors

Numerous studies have analyzed existing irradiance models for estimating sky diffuse irradiance on tilted planes. However, few have evaluated the suitability of these models for estimating irradiance in obstructed environments, specifically considering the effects of obstacles. In this study, three irradiance models —one of them with five variants— for estimating diffuse irradiance on tilted planes located in urban environments were evaluated. All models have been adapted to consider the effect of an urban canyon on the diffuse irradiance received on a tilted plane through the sky view factor and the circumsolar view factor. All the models were evaluated against the diffuse irradiance values obtained by the ISO 15469:2004(E)/CIE S 011/E:2003 angular distribution model. Therefore, it was necessary to determine the standard sky type corresponding to each record of the measurements performed by a sky scanner at the radiometric station of UPNA (Spain). A total of 4,864 scenarios were considered to occur from the combination of different orientations and inclinations of the plane, and different orientations and aspect ratios of the urban canyon. The results revealed that the Perez model considering a 35° half-angle circumsolar region has the best performance, followed by the Perez model considering a 45° half-angle circumsolar region.

Proposal to Refine Solar Radiation of Typical Meteorological Year Database and Evaluation on the Influence of Air-Conditioning Load

The Typical meteorological year (TMY) database is often used to calculate air-conditioning loads, and it directly affects the building energy savings design. Among four kinds of TMY databases in China—including Chinese Typical Year Weather (CTYW), International Weather for Energy Calculations (IWEC), Solar Wind Energy Resource Assessment (SWERA) and Chinese Standard Weather Data (CSWD)—only CSWD is measures solar radiation, and it is most used in China. However, the solar radiation of CSWD is a measured daily value, and its hourly value is separated by models. It is found that the cloud ratio (diffuse solar radiation divided by global solar radiation) of CSWD is not realistic in months of May, June and July while compared to the other sets of TMY databases. In order to obtain a more accurate cloud ratio of CSWD for air-conditioning load calculation, this study aims to propose a method of refining the cloud ratio of CSWD in Shanghai, China, using observed solar radiation and the Perez model which is a separation model of high accuracy. In addition, the impact of cloud ratio on air-conditioning load has also been discussed in this paper. It is shown that the cloud ratio can yield a significant impact on the air conditioning load.

Estimation of daylight availability in Kolkata and approximation of indoor daylight levels for different daylighting methods

ABSTRACT This work estimated the daylight availability and luminous efficacy of solar illuminance and approximated indoor daylight levels for various indoor daylighting methods for Kolkata, a major city in eastern India having tropical savanna climate, by applying two computational methods: the Perez model and the IESNA recommended calculation procedure. It was found that hourly horizontal diffuse and global illuminance, horizontal sky and total daylight illuminance values remained mostly over 10 klx throughout the year, and global and diffuse luminous efficacies mostly remained around 95–120 and 110–150 lm/W, respectively. The linear correlation between solar irradiation and estimated illuminance was stronger for Perez model. Thus, the application of Perez model was considered the better choice to appraise the daylighting potential of Kolkata.

Estimation of Solar Radiation on Tilted Surface by Using Regression Analysis at Different Locations in India

This study is to find the regression model for estimation of monthly meanhourly global solar radiation on tilted surface at different locations of India.This study is quite precious due to lack of solar radiation data availability onthe tilted surface. Firstly, we have selected some locations having differentclimatic conditions such as New Delhi, Mumbai, Kolkata, Lucknow andJaipur to find the solar radiation on tilted surface using Liu and Jordan model,HDKR model and Perez model. The mean values of these models are plottedalong with the daytime. Based on regression techniques, four empiricalmodels are developed which are tested to compute the solar radiation ontilted surface for three new stations Ahmadabad, Bangalore and Chennai.The estimated solar radiation by these four developed models are comparedwith the estimated values using existing models Lie & Jordan, HDKR andPerez based on mean bias error (MBE) and root mean square error (RMSE).It has been found that developed Model-3 has minimum error and the valuesestimated this model is comparable to existing models. The maximum values of RMSE in Model-3 in tested stations are 2.01% with Liu and Jordan, 2.63%with HDKR and 2.10% with Perez. Similarly, maximum values of MBE are−1.79% with Liu and Jordan, −2.27% with HDKR and −1.89% with Perez.Now the Model-3 finally selected to determine the solar radiation on Bhopal,Bhubneshwar, Dehradun, Guwahati and Trivendrum (Thiruvananthapuram).

Rotational Molding of Polyamide-12 Nanocomposites: Modeling of the Viscoelastic Behavior

Nowadays, polyamide 12 (PA-12) is considered as an interesting polymer in the rotomolding process to manufacture different pieces like the liner part in the storage hydrogen tank (type IV). In this study, the pure polyamide-12 and PA12 pieces, incorporated with 0.5%, 1% and 3% wt Nano Carbon Black (NCB), were manufactured by the rotomolding process. Different rotomolding parameters such as heating temperature, time of heating, and cooling rate have been optimized to obtain the ideal piece. The effect of volume fraction of NCB in terms of physicochemical and mechanical properties has been studied. Afterward, the optimal volume fraction of NCB is revealed using different characterization methods. The tensile results specified the addition of NCBs until 0.5% improved the tensile behavior. The addition of NCBs more than 0.5% decreases the mechanical properties in terms of failure stress and strain, while it has no significant effect on the elastic modulus of PA-12. The bi-parabolic the Perez model has been used to study the viscoelastic behavior of PA-12 using the Cole-Cole method. The constants of the Perez model indicate a good correlation between viscoelastic experimental results and the model used.

Choice of clear-sky model in solar forecasting

This paper is concerned with the choice of clear-sky model in solar forecasting. This issue is discussed from three perspectives: (1) accessibility, (2) forecast performance, and (3) statistical properties. Accessibility refers to the time and effort involved in obtaining clear-sky irradiance through a clear-sky model. Forecast performance is analyzed through a new concept called “mean square error (MSE) scaling,” which allows one to decompose the MSE of reference irradiance forecasts into three terms, each carrying a notion of predictability. The decomposition, however, resides on the assumption that the clear-sky index time series is stationary. In this regard, the stationarity assumption is investigated using statistical hypotheses. It is found that even the best clear-sky models, such as the REST2 model, are not able to produce a stationary clear-sky index time series. Instead, the time series is only local stationary, which, in the present context, means that its statistical properties change slowly with the value of clear-sky irradiance. Contrary to the common belief that a better clear-sky model leads to better forecasts, no evidence suggests that the more intricate REST2 has an advantage over the simpler Ineichen–Perez model, in terms of forecast performance. In that, accessibility becomes the primary concern when opting a clear-sky model for forecasting purposes. At this point, the McClear model, available as a web service for worldwide locations at 1-, 15-, and 60-min resolutions, is highly recommended.

Calibrating Perez Model Coefficients Using Subset Simulation

The Perez sky diffuse model has been validated in many locations, however, studies have shown that the precision of estimation can be improved through localization of the model coefficients. This paper studies the effect of tuning Perez irradiance coefficients based on local information for estimating the incident solar radiation on tilted surfaces. The added value of a calibrated Perez model is highlighted by evaluating the heating and cooling energy needs of an office building. Calibration is performed by using Subset Simulation, i.e. a sampling technique based on Markov Chain Monte Carlo. The versatility of the Subset Simulation technique allows for handling multivariant calibration problems and is therefore suitable for finetuning Perez irradiance coefficients. Measurements of global horizontal, direct normal and diffuse horizontal solar irradiation, as well as the global solar irradiation on 90°, 30° and 15° tilted surfaces form the basis of the calibration. It is found that in the studied location, the default Perez model overestimates the incident solar radiation on vertical surfaces facing south. The calibrated coefficients are then embedded in the source code of EnergyPlus. Simulations with a reference office show that the effect of calibrating Perez coefficients can be significant, because it leads to approximately 12% difference in predicted annual cooling energy use and 9% difference in peak cooling loads, respectively.