PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation
Highlights
► GIS-based spatial multi-criteria approach to assess land suitability for PV farms in Oman. ► 0.5% of the total land area demonstrate a high suitability level. ► Highly suitable land exploited for CPV can produce 45.5 times the present total power demand in Oman.
Introduction
Despite the cascade effects of the financial crisis that have affected every sector, in varying degree and geography, the investment in renewable energy continues growing with a sustainable trend. According to the new report of the UNEP (United Nation Environment Programme) [1], the investment in renewable energy rose 5% in 2008 proving definitely the establishment of new methods of electric power generation and confirms that this sector represents now a mainstream energy investment [2]. The climate of the good health of renewable energy is the fruit of the interactions of the governmental and societal engagement towards tangible actions to mitigate climate change by reducing Green House Gases (GHG), reducing their dependency on fossil fuel supply and making energy security a strategic priority. Certainly, the current financial and economical crisis may have slowed down the demand on the fossil fuel energy and driven down prices. But, the world opinion is still convinced, that is only a temporary pause. It seems that there is a latent threat form energy crisis, and will constitute a good stimulus for the emergence of the renewable energy era.
To face this threat from resources depletion, solar energy is recognized as a robust alternative to unsustainable energy use in developed and developing countries. During the last two decades, the rhythm of the implementation of solar farm using Photovoltaic (PV) panels or Concentrated Solar Power (CSP) technologies has accelerated in the countries situated in the solar energy belt, despite their prohibitive costs.
According to the International Energy Agency (IEA) solar electricity will grow up to 20–25% by 2050 [1]. The IEA has also foreseen that, by 2050, the PV and CSP systems will be able to generate 9000 TWh of electricity and reduce the yearly CO2 emissions by almost 6 billion tones [3].
Comparing the CSP and PV technologies, the CSP necessitate larger amounts of water for cooling and mirror washing than the PV. Therefore, for arid countries with scarce fresh water resources, the PV technology is more suitable, environment friendly, and economical. Besides, the implementation of PV plants is much faster than the CSP ones, which gives it more flexibility to cope easily with the development of the grid system. To enable the development of the PV solar technologies long-term oriented strategies with predictable incentives are needed to ensure the successful deployment of PV systems to competitiveness in the most suitable locations and times.
The Geographical Information System (GIS) reached a high level of maturity and emerged as a powerful tool to build solar energy strategies and to integrate large amounts of PV into flexible, efficient and smart grid. GIS is able to handle, processing, analyzing a large quantities of spatial data and underpinning decision-making for the spatial deployment of PV. Using GIS and Multi-Criteria Analysis (MCA) together provide a fine lens for the optimal site selection for plants. GIS-based MCA is commonly used to solve the conflicts of location suitability and harmonizing the tradeoffs and risks related to various experts’ judgment engaged in the implementation of different applications [4], [5], [6]. However, very little was published on solar applications.
This paper presents a study that aimed at developing the first geographical mapping models to locate the most appropriate sites for different PV technologies in Oman using MCA.
Section snippets
Overview of multi-criteria analysis
The principal of the MCA is to condense complex problems with multiple criteria into finest ranking of the best scenarios from which an option is selected [7], [8], [9], [10]. In GIS-based MCA and for solar energy purpose, this might include a set of geographically defined criteria, such as solar radiation, Digital Elevation Model (DEM), residential area, sensitive area, transmission lines, load demand, road accessibility etc. Weights can be attributed to the criteria according to the
PV site suitability
Solar energy resource assessment and site suitability for large PV farms implementations is affected by different factors which can be classified in three main categories: Technical, Economical and Environmental. These factors depend on the geographical location, biophysical attributes and socio-economical infrastructure of the country under study.
For a country like Oman, which is situated astride the tropic of cancer and characterized by an arid and very hot climate, the typical parameters
Study-case implementation & results
To find out the most appropriate locations for PV farms in Oman, an important data base was collected from different sources to shape factors affecting optimal locations for large PV farms in Oman as stated in III. Five steps compose the achievement of the spatial distribution of the land suitability level:
Step 1: the collected geo-referenced data base was converted from vector files to raster format with a pixel of 40 m in order to keep uniformity with the Digital Elevation Model (DEM) of Oman.
Discussions
The annual electric power generation potential for the selected areas can be estimated based on the calculated average annual solar radiation per unit surface, the total suitable area, and the efficiency of the PV technology. Eq. (1) can be used to estimate the yearly solar electric power generation potential [28].where:
GP Electric power generation potential per year (GWh/year).
SR Annual solar radiation received per unit horizontal area (GWh/km2/year).
CA Calculated total area of
Conclusion
This paper has demonstrated the application of a GIS-based spatial multi-criteria evaluation approach, in terms of the FLOWA module to assess the land suitability for large PV farms implementation in Oman. The FLOWA module applies fuzzy quantifiers within ArcGIS environment. It incorporates uncertainty of expert opinions on the criteria and their weights, and provides a mechanism for guiding the decision-making through the multi-criteria combination procedures.
Land suitability analysis for
Acknowledgment
Authors would like to acknowledge Sultan Qaboos University and The Research Council in Oman for providing the financial support to conduct this research study.
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