Assessment Of Solar Potential Research Articles

Global solar radiation on tilted surfaces in Tunisia: Measurement, estimation and gained energy assessments

A very important factor in the assessment of solar potential for the installation of photovoltaic plants is the availability of global irradiation data measurements. Such data must be collected over a period of time longer than 11 years and must be accurate. In some countries, it is difficult to have databases of these measures. To overcome this problem, we propose, the use of numerical models to estimate the monthly, seasonally and annually solar energy irradiation (global diffuse and direct solar radiation), especially on tilted surface.The results obtained from the numerical models are compared to the data collected from three regions on Tunisia: Bizerte (in the north), Nabeul (near to the north east) and Djerba (in the south).The actual measurements taken from the meteorological stations and the measurements generated by the numerical models are very close.After the validation of the numerical models, we tried to calculate the best tilt angle for each period of the year to position a photovoltaic panel, in a given region, to reach maximum energy recovery.The practical validation, of the optimal tilt angle search and the adequate period, was conducted at the Research and Technology Center of Energy of Borj Cedria. The obtained results are satisfactory and prove the reliability of the constructed numerical models.

Assessment of global solar radiation to examine the best locations to install a PV system in Tunisia

The study of the solar radiation is the starting point of any investigation for a new energy, to study and search the best location to install a PV system. A very important factor in the assessment of solar potential is the availability of data for global solar radiation that must be coherent and of high quality. In this paper, we analyze the estimation result of the monthly global solar radiation for three different locations, Bizerte in Northern Tunisia, Kairouan in Middle Eastern Tunisia, and Tozeur in Southern Tunisia, measured on the surface by the National Institute of Meteorology and the meteorological year irradiation based on satellite imagery result PVGIS radiation databases. To get the right measurements with minimum error, we propose a numerical model used to calculate the global solar radiation in the indicated three sites. The results show that the model can estimate the global solar radiation (kWh/m²) at a specific station and over most area of Tunisia. The model gives a good estimation for solar radiation where error between the measured values and those calculated are negligible.

A hybrid solar radiation modeling approach using wavelet multiresolution analysis and artificial neural networks

Assessment of solar potential over a location of interest is an important step towards the successful planning of renewable energy projects. However, solar data are not available for every point of interest due to the absence of meteorological stations and sophisticated solar sensors, so solar radiation has to be estimated using models. This paper presents a hybrid technique to improve the performance of a widely used modeling technique i.e. artificial neural network (ANN). Four different architectures of ANN, namely: multilayer perceptron (MLP), Adaptive neuro-fuzzy inference system (ANFIS), Nonlinear autoregressive recurrent exogenous neural network (NARX), and generalized regression neural networks (GRNN), are used in this study. A wavelet multiresolution analysis is applied to decompose the complex meteorological signals into relatively simple parts, wavelet sub-series, using discrete wavelet transformation (DWT) algorithm. The wavelet sub-series are modeled by the ANN models and reconstructed to estimate the original signal. Hence, enhancing the learning process of these models. Four meteorological parameters, namely: temperature (T), relative humidity (RH), wind speed (WS), and sunshine duration (SSD), are used to mode the global horizontal irradiation (GHI) over Abu Dhabi, the United Arab Emirates. The proposed approach is compared to standalone ANN models and validated using well-known statistical validation metrics including coefficient of determination (R2), root mean square error (RMSE), mean bias error (MBE), mean absolute percentage error (MAPE), and t-statistics. In addition, wavelet cross spectrum (WCS) is used as a visual indicator of the model performance in time, frequency, and phase domains. The results show that using the proposed strategy considerably improves the modeling performance of the ANN with a maximum improvement of 6.84% in R2 for MLP. In addition, minimum RMSE of 2.78% is observed for GRNN.

Development of ANN Based Model for Solar Potential Assessment Using Various Meteorological Parameters

Abstract Solar potential assessment is very useful for various applications like solar heating, agriculture, solar lighting system and solar power plant erection etc. The objective of the current study is to identify theoretical potential of solar radiation for solar energy applications in hilly state Himachal Pradesh. Artificial Neural Network (ANN) is used to predict solar radiation using site specific measured data of Hamirpur for training and testing. The input variables used are temperature, rainfall, sunshine hours, humidity &barometric pressure to predict solar radiations. To identify the effect of various input parameters on solar radiations three ANN based models have been developed represented by ANN-I5, ANN-I4& ANN-I3.To obtain best prediction result, the number of input parameters of the input layer have been varied between 3 to 5 and hidden layer neuron have also been varied between 10 to 20. The best mean absolute percentage error (MAPE) calculated for these models (ANN-I5, ANN-I4 & ANN-I3) are 16.45%, 18.77% and 19.39% respectively. The ANN-I5 (temperature, humidity, barometric pressure, rainfall and sun shine hours), model has shown good prediction accuracy as compared to other two models. This study shows that various numbers of meteorological parameters mostly affect the forecasting of solar radiation. The method in this paper can also be used to identify the solar energy potential of any location worldwide where it is not possible to install direct measuring instrument.

Solar potential assessment and performance indices analysis of photovoltaic generator for isolated Lakshadweep island of India

Lakshadweep island is located in the Arabian Sea (8° and 12°13′ North Latitude, 71° and 74° East Longitude) of India where the island inhabitant depends upon the power generation from diesel generator because of inaccessibility to the grid power due to its location hinder. As an alternative viable option for this island, inhabitant is to use photovoltaic power generation. This paper presents the normalized performance results obtained from photovoltaic (PV) system and the solar potential assessment for four islands of Lakshadweep, mainly, Andrott, Kavaratti, Kiltan and Minicoy. The monthly average and annual average normalized performance parameters such as array yield, reference yield, array capture losses, system losses and performance ratio of 10kWp photovoltaic system is calculated. Besides, the monthly average and annual average capacity factor and cell temperature are also obtained. It is found that the obtained results for annual average performance ratio and capacity factor vary in the range of 64.22–65.83% and 15.51–16.09%, respectively. The annual average array yield, reference yield, final yield, array capture losses and system losses for the considered islands are found to be 4.13–4.29h/d (symbolized as h/d), 5.78–5.88h/d, 3.72–3.86h/d, 1.58–1.66h/d and 0.41–0.43h/d, respectively.

An Assessment of the Solar Potential of Roofs within a Web-based Solar Cadastre

Solar technologies offer clean and sustainable energy production at an affordable cost. Therefore, their use is rapidly growing, and private users as well as local authorities demonstrate wide interest in identifying areas suitable for mounting solar modules. The recent improvements of remote sensing techniques such as LIDAR (Light Detection and Ranging), are very attractive and suitable for solar potential assessment; however, it is of paramount importance to transfer the knowledge to the public. The proposed solution includes the development of an interactive tool, Solar WebGIS, which can analyse and visualize solar potential characteristics. Furthermore, the article discusses the data preparation, integration, and visualization issue related to the WebGIS.

Solar Potential in the Himalayan Landscape

Estimation of solar energy reaching the earth’s surface is essential for solar potential assessment. Solar radiation data based on satellites provide higher spatial and temporal coverage of regions compared to surface based measurements. Solar potential of the Indian hill state of Himachal Pradesh has been assessed using reliable satellite based global horizontal insolation (GHI) datasets validated based on its complex terrain. Solar maps representing regional and temporal resource availability in the state have been generated using geographical information systems (GIS). Spatial analyses show that the state receives annual average GHI above 4.5 kWh/m2/day and a total of 99530395 million kWh (or million units, MU). The regional availability of GHI in Himachal Pradesh is influenced by its eclectic topography, seasons as well as microclimate. The lower and middle elevation zone (<3500 m) with tropical to wet-temperate climate receives higher GHI (>5 kWh/m2/day) for a major part of the year compared to the higher elevation zone (>3500 m) with dry-temperate to alpine climate (4–4.5 kWh/m2/day). Results show that Himachal Pradesh receives an average insolation of 5.86 ± 1.02–5.99 ± 0.91 kWh/m2/day in the warm summer months; 5.69 ± 0.65–5.89 ± 0.65 kWh/m2/day in the wet monsoon months; 3.73 ± 0.91–3.94 ± 0.78 kWh/m2/day in the colder winter months.

The method of assessment of solar potential for selected area with use Geographical Information Systems

This paper describes a method for analyse the spatial distribution of solar energy potential based on calculated solar irradiation with use of GIS (Geographical Information System). Program GIS GRASS gives opportunity to create spatial distribution of solar radiation which is taking into account such important elements like: terrain, atmosphere, pollutants, water and aerosol in atmosphere, clouds. The use of GIS GRASS module – named r.sun gives opportunity to generate spatial distribution of solar radiation on Lower Silesia (south – west part of Poland). In this work the analyse of solar potential to obtain hot water in the individual household were done. This analyse was based on the amount of total solar radiation monthly sums generated by r.sun module. Spatial distribution of solar potential was used to classify the Lower Silesia region in terms of work efficiency solar installations. It is very usefully because it gives people information about the date of the return of the funds invested in the purchase of the solar collectors.

Extraction of Vertical Walls from Mobile Laser Scanning Data for Solar Potential Assessment

In recent years there has been an increasing demand among home owners for cost effective sustainable energy production such as solar energy to provide heating and electricity. A lot of research has focused on the assessment of the incoming solar radiation on roof planes acquired by, e.g., Airborne Laser Scanning (ALS). However, solar panels can also be mounted on building facades in order to increase renewable energy supply. Due to limited reflections of points from vertical walls, ALS data is not suitable to perform solar potential assessment of vertical building facades. This paper focuses on a new method for automatic solar radiation modeling of facades acquired by Mobile Laser Scanning (MLS) and uses the full 3D information of the point cloud for both the extraction of vertical walls covered by the survey and solar potential analysis. Furthermore, a new method isintroduced determining the interior and exterior face, respectively, of each detected wall in order to calculate its slope and aspect angles that are of crucial importance for solar potential assessment. Shadowing effects of nearby objects are considered by computing the 3D horizon of each point of a facade segment within the 3D point cloud.

Automatic Roof Plane Detection and Analysis in Airborne Lidar Point Clouds for Solar Potential Assessment

A relative height threshold is defined to separate potential roof points from the point cloud, followed by a segmentation of these points into homogeneous areas fulfilling the defined constraints of roof planes. The normal vector of each laser point is an excellent feature to decompose the point cloud into segments describing planar patches. An object-based error assessment is performed to determine the accuracy of the presented classification. It results in 94.4% completeness and 88.4% correctness. Once all roof planes are detected in the 3D point cloud, solar potential analysis is performed for each point. Shadowing effects of nearby objects are taken into account by calculating the horizon of each point within the point cloud. Effects of cloud cover are also considered by using data from a nearby meteorological station. As a result the annual sum of the direct and diffuse radiation for each roof plane is derived. The presented method uses the full 3D information for both feature extraction and solar potential analysis, which offers a number of new applications in fields where natural processes are influenced by the incoming solar radiation (e.g., evapotranspiration, distribution of permafrost). The presented method detected fully automatically a subset of 809 out of 1,071 roof planes where the arithmetic mean of the annual incoming solar radiation is more than 700 kWh/m2.