Scientists used geographical information systems and analytical hierarchy process methods to identify the most suitable areas of Iran for PV water pump systems. They found 43.2% of the country unsuitable, with the province of Ardabil the most favorable.
Researchers from the German RWTH Aachen University and Iran’s University of Tehran have proposed a new method to identify suitable locations for the implementation of PV water pump systems (PVWPS). The methodology uses a geographical information system (GIS) and an analytical hierarchy process (AHP) and was demonstrated in the case of Iran.
“Our study introduces a new integration of spatial multi-criteria decision analysis (SMCDA) with PV-water pump systems to optimize underground water,” said researcher Amirali Mahjoob said PV -Magazine. “This interdisciplinary approach combines geospatial analysis with solutions for renewable energy, which offers an extensive framework for sustainable water sources, especially in dry and semi-arid regions.”
The academic group has established three categories that influence the viability of solar pumps: hydrological, solar and land data. The hydrological category included three subcategories – water extraction flow, pump work hours and average well depth. The solar category consisted of six subcategories – Global Horizontal Ariciance (GHI), Direct Normal Araliance (DNI), diffuse horizontal radiation (DHI), lace, wind speed and ambient temperature.
The land -specific category contained three subcategories: limited areas, land fitness and technical suitability. Limited areas were further subdivided into schedules, military land use, protected areas, rivers and lakes and airports. Suitability in the country includes errors, distance to roads, land use, type of agriculture and soil type. Technical suitability covered height, slope and aspect.
The team has made maps for every subcategory using GIS software and applied fuzzy membership functions to convert unprocessed data into usability scales. With the help of an analytical hierarchy process (AHP) informed by a survey of four university professors, two experts in the field of water sources, two power engineers, one danger expert and a student for renewable energy, the group assessed the relative importance of each card. They have verified the weights by sensitivity analysis.
Image: RWTH Achen, Remote applications: Society and Environment, CC by 4.0
In general, the PV and hydrological categories were given a combined weight of 0.596, the country of the country was assigned 0.346 and the technical suitability was good for 0.058. To integrate the different data strokes with their respective weights, the researchers applied the weighted linear combination (WLC) method. The resulting card classified areas in four categories of usability.
“The first category is the areas that fall into the ‘unsuitable’ category. These areas cannot be used to implement these systems. Iran has a desert and semi-desert climate, so a large part of the bottom of the country is unsuitable for urban and rural development,” the researchers explained. “The second category, ‘moderate’, is not recommended for the use of these systems. The costs of the system in these areas are not economic under normal circumstances. These systems can only be used in exceptional cases, such as lack of access to the grid and the impossibility of its development.”
They classified the third category as ‘good’, where solar pump systems are cost-effective with a good design and are suitable for use outside the grid. The highest category, “excellent”, is considered suitable to replace other energy sources for water extraction due to several benefits.
The results show that 2.5% of Iran is excellent, 12.1% good, 32.6% moderate, 43.2% unsuitable and 9.3% limited. Areas with excellent and good suitability for PV -Water pump systems are mainly in the northwestern and southwestern regions, while moderate suitability appears in central and northeastern regions. The province of Ardabil is the most suitable for PVWPS, with Yazd and South Khorasan provinces the least suitable.
“Building on our current findings, we intend to explore the scalability of this integrated approach in various geographical regions and climatic conditions,” said Mahjoob. “Moreover, we are interested in recording real-time data analyzes and machine learning algorithms to improve the predictive possibilities of our model, aimed at dynamic decision-making aids that can adapt to changing environmental factors.”
The scientists presented their results in “Spatial multi-criteria decision analysis on harvesting underground water using PV-water pump system“Which was recently published in Remote applications: society and the environment.
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