Solar Energy Resource Assessment Using R.SUN In GRASS GIS And Site Suitability Analysis Using AHP For Groundmounted Solar Photovoltaic (PV) Farm In The Central Luzon Region (Region 3), Philippines

In the study, the solar energy resource in the Central Luzon Region (Region 3), Philippines was determined using r.sun – a topography-based solar radiation model implemented in GRASS GIS – and suitable sites for the installation of ground-mounted solar photovoltaic (PV) farms were identified using the Analytic Hierarchy Process (AHP) to determine the weights of different physical, environmental, socio-economic, risk, and constraint criteria. For the resource assessment, the inputs to r.sun used in the study consisted of freely available data that include: an SRTM (90m resolution) Digital Elevation Model (DEM) and monthly average Linke turbidity coefficients available from the SoDA (Solar Radiation Database) webservice (www.soda-is.com). Daily solar radiation data from eight (8) measuring stations throughout the region were gathered. Readings from six (6) stations were used to interpolate monthly clear-sky index rasters while the readings from the remaining two (2) stations were used to validate the modelled monthly average Global Horizontal Irradiation (GHI) computed by r.sun. For the site suitability analysis, different criteria rasters were created and combined using weighted overlay to generate a suitability map for ground-mounted solar PV farms in the region. From the results, the monthly average GHI in the region computed by r.sun ranged from 3706.8 Wh/m2 - day in December to 6021.0 Wh/m2 -day in May with an annual average GHI of 4727.12 Wh/m2 -day indicating a good amount of resource potential. High GHI values were observed for the summer months of March to May (Mean: 5640.26 Wh/m2 -day) while the cold and rainy season ranging from July to December showed relatively lower values (Mean: 4298.98 Wh/m2 -day). The Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) between the measured and modelled GHI were 352.88 Wh/m2 -day and 8.53%, respectively, with the lowest error in March (73.94 Wh/m2 -day, 1.44%) and the highest in August (844.01 Wh/m2 -day, 21.65%). In fact, the model performed well for the months of January to June (MAE: 192.18 Wh/m2 -day, MAPE: 3.83%) and slightly poorer for July to December (MAE: 512.824 Wh/m2 -day, MAPE: 13.22%). For further study, other data sources and inputs can be looked into to improve the accuracy of the resource assessment and site suitability analysis. Aside from this, the use of more solar radiation recording stations for validation is preferred in order to better validate the results of r.sun and its applicability for solar energy resource assessment in the Philippines

Setting intelligent city tiling strategies for urban shading simulations

Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements. In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500 m width and 200 m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300 m width and 100 m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations

Modeling physical and chemical climate of the northeastern United States for a geographic information system

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from regional data bases were combined with a digital elevation model of the region to generate digital coverages of each variable

Case study 2. Model validation using existing data from PV generation on selected New Zealand schools

Solar energy is abundant, free and non-polluting. Solar energy can offset the consumption of fossil fuels, greenhouse gas emission reduction targets and contribute to meeting the fast-growing energy demands. The use of solar energy for electricity generation from photovoltaic (PV) panels has increased but is still not a widely utilised technology in New Zealand. This research approximated the potential solar energy that could be harvested from the rooftops of existing residential buildings in a case study city. This research is divided into two work strands, each involving a case study. The first strand investigated if a model could be developed, using existing data sources to determine the solar harvesting potential from the rooftops of existing residential buildings. The second strand involved the validation of the solar PV prediction model proposed in the first strand of the research, to test the reliability of the modelling outcomes. Invercargill City was selected as the study city for case study 1. Invercargill is the southernmost city in New Zealand so represents a worst case scenario. The method involved merging computer-simulation of solar energy produced from PV modelling and mapping incoming solar radiation data from north facing residential rooftop area. The work utilised New Zealand statistical census map of population and dwelling data, as well as digital aerial map to quantify the efficient roof surface area available for PV installations. The solar PV potential was calculated using existing formulas to investigate the contribution of roof area to the solar PV potential in buildings using roof area and population relationship. The estimated solar PV potential was 82,947,315 kWh per year generated from the total solar efficient roof surface area of 740,504 m². This equates to approximately 60.8% of the residential electricity used in Invercargill’s urban area, based on the 7,700 kWh typical annual electricity consumptions per household. The result represents an immense opportunity to harvest sustainable energy from Invercargill’s residential rooftops. To verify the accuracy of the developed method for predicting the PV outputs, the model was applied to actual generation data from grid-connected solar photovoltaic (PV) systems that are installed in New Zealand schools under the Schoolgen programme (Case Study 2). A total of 66 Schoolgen PV rooftop models were incorporated in the analysis. At this stage, the actual system parameters including size, panel type and efficiency were included in the analysis. The performance prediction and analysis outcome showed the parameters and operating conditions that affect the amount of energy generated by the PV systems. This part of the research showed the area where the PV model can be improved. The predicted generation from the model was found to be lower than the actual generation data. Schoolgen systems operating at over 0.75 performance ratio were found to be underestimated. This indicated that most Schoolgen PV systems were operating at higher capacities than predicted by the default value of system losses. The analysis demonstrated the effects of PV technology type, site orientation, direction and tilted angle of the panels on the ability to generate expected amount of potential capacity based on solar resource availability in different site scenarios. This in turn has provided more in depth analysis of the research and served to expand the area for improvements in the design of the model

Monthly average daily global and diffuse solar radiation based on sunshine duration and clearness index for Brasov, Romania

The main objective of this study is to develop single location appropriate models for the estimation of the monthly average daily global and diffuse horizontal solar radiation for Brasov, Romania. The study focuses particularly on models based on the sunshine duration and clearness index. The data used for the calibration of the models were collected during a period of 4 yr, between November 2008 and October 2012, at the Transilvania University of Brasov. The testing and validation of the models was carried out using data from the online SoDa database for Brasov for the year 2005. Different statistical error tests were applied to evaluate the accuracy of the models. The predicted values are also compared with values from three other known models concerning the global and diffuse solar radiation. A new mixed model was developed for the estimation of monthly average daily global horizontal solar radiation. The data processing was performed by means of a real-time interface developed with LabVIEW graphical programming language. The parameters taken into account were the relative sunshine, the clearness index, the extraterrestrial radiation, the latitude and the longitude. The methodology is simple and effective and may be applied for any region. Its effectiveness was proven through comparison with global models

Assessment of the photovoltaic potential at urban level based on 3D city models: A case study and new methodological approach

The use of 3D city models combined with simulation functionalities allows to quantify energy demand and renewable generation for a very large set of buildings. The scope of this paper is to determine the solar photovoltaic potential at an urban and regional scale using CityGML geometry descriptions of every building. An innovative urban simulation platform is used to calculate the PV potential of the Ludwigsburg County in south-west Germany, in which every building was simulated by using 3D city models. Both technical and economic potential (considering roof area and insolation thresholds) are investigated, as well as two different PV efficiency scenarios. In this way, it was possible to determine the fraction of the electricity demand that can be covered in each municipality and the whole region, deciding the best strategy, the profitability of the investments and determining optimal locations. Additionally, another important contribution is a literature review regarding the different methods of PV potential estimation and the available roof area reduction coefficients. An economic analysis and emission assessment has also been developed. The results of the study show that it is possible to achieve high annual rates of covered electricity demand in several municipalities for some of the considered scenarios, reaching even more than 100% in some cases. The use of all available roof space (technical potential) could cover 77% of the region’s electricity consumption and 56% as an economic potential with only high irradiance roofs considered. The proposed methodological approach should contribute valuably in helping policy-making processes and communicating the advantages of distributed generation and PV systems in buildings to regulators, researchers and the general public

A solar irradiation GIS as decision support tool for the Province of Salta, Argentina

The province of Salta is characterized by its solar energy high potential. The use of solar resource would improve living conditions in the area, diversify the energy matrix, promote more sustainable production systems and reduce greenhouse gases emissions. However, there are only a few studies that describe in high spatial resolution the variability of the solar resource in Argentina. Multidimensional tools, that consider the environment and the socio-economic situation, have to be considered for adequate support decision-making, such as solar collector location assessment and photovoltaic potential. In this sense, a deep evaluation of the solar resource is needed first, as solar irradiation is an essential input variable for the design and evaluation of solar application systems. In this paper, we detail the methodology used to elaborate a GIS tool to support decisions related to renewable energy policies and solar technology design. A comparison between global solar irradiation measurements in situ, empirical models, and data provided by Land Surface Analysis Satellite Applications Facility (LSA-SAF), is performed in daily, monthly and annual basis for a seven-year period. This analysis validates the use of this satellite data for the determination of solar irradiation in the region.Fil: Sarmiento Barbieri, Nilsa Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Belmonte, Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Dellicompagni, Pablo Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Franco, Ada Judith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Escalante, Karina Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Sarmiento Barbieri, Joaquín Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; Argentin

Identifying and Viewing Rooftop Solar Potential: A Case Study for the City of Redlands, California

Increasingly scarce resources pose new challenges to human development in the twenty-first century. As a result of the shifting focus to renewable energy in order to meet the different needs of sustainable development, human society will inevitably experience numerous transformations on a variety of scales. Solar radiation plays a key role in achieving the objectives of sustainable development. Due to the potential variation over space and time, efficient utilization of solar energy requires that people understand the diverse spatial and temporal patterns of incoming solar radiation. This project was aimed at developing a Web-based solar map for the City of Redlands using DEMs generated from high resolution LiDAR data. This online solar map will provide the means to inform people of the latest updates regarding solar radiation, and also support their decision-making process in identifying ideal locations of solar panels for maximizing their benefits