Empirical Evaluation of Fixed and Single-Axis Tracking Photovoltaic System: Case of ASHRAE Solar Radiation Modelling for Medina, Saudi Arabia

The main problem in studying the feasibility of solar systems is the enormous gap between theory and experimental radiation intensity, so to get accurate results there is a need for studying energy production in the site of the system empirically. In this study, the energy production of both fixed PV panel system and the system with single-axis tracking were empirically evaluated in Medina, Saudi Arabia. The two systems had the same 270 Wp PV panel. The fixed system was tilted by 23.5 degrees, and the single-axis tracker was tilted by 26 degrees. Both systems had an azimuth angle of zero degrees. A closedloop three-points controller was used to control the tracker with 120 degrees rotation range. The two systems operated simultaneously in July, and the data were collected for 14 days. The empirical results showed that the tracker increased the generated energy by 48.5% during the testing period. As a comparing method, a modified ASHRAE model was used to estimate the increase in the panel's energy output with and without the single-axis tracker, and RMSE and MBE were calculated. It's been found that the experimental energy generation is 10%, 5% less than the estimation of the modified model for the fixed system and the tracking system, respectively. Finally, based on the analysis, it's been estimated that the singleaxis tracker will increase the generated energy by 22.5% yearly in Medina.

Improvement of radiation modelling during cloudy sky days using in-situ and satellite measurements.

<p>Solar radiation modelling is important for the evaluation and deployment of solar renewable energy systems. The amount of solar radiation reaching the ground is influenced by geographical parameters (seasons, latitude and local characteristics of the site) and meteorological and atmospheric parameters (like humidity, clouds or particles). Those parameters have important spatio-temporal variations that make solar radiation hard to model. </p><p>Various radiation models exist in literature. Among them, the 1D radiation model part of the computational fluid dynamics software “Code_Saturne” estimates the global and direct solar irradiances at the ground. It takes into account the impact of meteorology, atmospheric gas, particles and clouds whose influence is represented using the two-stream approximation. </p><p>The model showed satisfactory results during clear-sky days  but not during cloudy-sky days. It is a common problem in solar radiation modelling, because of the complexity to accurately represent  clouds, which are extremely variable in space and time and have a strong influence on the depletion of solar irradiance.  </p><p>In the current study, the estimation of radiation during cloudy-sky days is improved by coupling the 1D radiation model of Code_Saturne with on-site and satellite measurements of the cloud optical properties. Meteorological data are obtained from the Weather Research and Forecasting (WRF) model, aerosol’s concentrations from the air-quality modelling platform Polyphemus, and on-site measurements from the SIRTA observational site (close to Paris). Two periods are simulated: 'august 2009' and 'year 2014'. It is shown that the introduction of the measured cloud properties in the computation of the surface radiation fluxes leads to a strong reduction of the simulated errors, compared to the case where these properties are derived from the WRF model.                    </p><p>A sensitivity analysis on the parameters representing clouds in the model is conducted. It enabled us to identify the most influencing parameters - cloud optical thickness (COD) and cloud fraction - and instruments that are sufficient and mandatory for a good description of solar radiation during cloudy-sky days. A fitted model is developed to deduce the COD from liquid water path measurements. Satellite and radiometric measurements could both be used, although satellite measurements are not always available.  For the estimation of cloud fraction, the best results are obtained from shortwave radiometric measurements or from a sky imager. Moreover, large error cases in hourly values of solar fluxes are examined to understand their origin. For a large part of these error cases, there is a high variation within the hour of satellite or in situ measurements, or the presence of low clouds (in more than 50% of these cases in august 2009). </p><p> </p>

A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data

This paper focuses on quantifying the uncertainty in the specific absorption rate values of the brain induced by the uncertain positions of the electroencephalography electrodes placed on the patient’s scalp. To avoid running a large number of simulations, an artificial neural network architecture for uncertainty quantification involving high-dimensional data is proposed in this paper. The proposed method is demonstrated to be an attractive alternative to conventional uncertainty quantification methods because of its considerable advantage in the computational expense and speed.

Evaluation of Solar Radiation Transposition Models for Passive Energy Management and Building Integrated Photovoltaics

Incident solar radiation modelling has become of vital importance not only in architectural design considerations, but also in the estimation of the energy production of photovoltaic systems. This is particularly true in the case of buildings with integrated photovoltaics (PV) systems having a wide range of orientations and inclinations defined by the skin of the building. Since solar radiation data at the plane of interest is hardly ever available, this study presents the analysis of two of the most representative transposition models used to obtain the in-plane irradiance using as input data the global and diffuse irradiation on the horizontal plane, which can be obtained by satellite-based models or ground measurements. Both transposition models are validated with experimental measurements taken in Murcia (southeast of Spain) and datasets provided by the photovoltaic geographical information system (PVGIS) and the National Renewable Energy Laboratory (NREL) for vertical surfaces facing the four cardinal points. For the validation, the mean bias deviation, root mean square error and forecasted skill were used as indicators. Results show that the error rate decreases slightly for clear days. Better results are also obtained by dismissing data with low solar elevation angles so as to avoid shadowing effects from the surroundings in the early and late hours of the day, which affects mainly the performance of the transposition models for west and east surfaces. The results highlight the potential of equator-facing façades in winter time when the received irradiation can be twice as much as the one collected by the horizontal plane. It is also noteworthy that the operating conditions of all façades are mainly low irradiance and medium temperature at these locations.