استفاده از سیستم اطلاعات مکانی و روش‌های تصمیم‌گیری چندمعیارۀ سوارا، ایداس و تاپسیس به‌منظور مکان‌یابی نیروگاه خورشیدی در استان فارس

بهره‌برداری از انرژی خورشیدی و احداث نیروگاه خورشیدی برای تولید برق به یکی از حوزه‌های مهم انرژی جهان تبدیل شده است. کشور ایران به‌دلیل شرایط جغرافیایی و آب‌‌هوایی ویژه پتانسیل بالایی در‌زمینۀ احداث نیروگاه‌های خورشیدی و تولید برق دارد. محققان در پژوهش حاضر با توجه به اهمیت مکان احداث نیروگاه خورشیدی در عملکرد و میزان برق تولیدی آن و با هدف مکان‌یابی بهینۀ نیروگاه خورشیدی در استان فارس از یک رویکرد ترکیبی تصمیم‌گیری چند‌معیاره مبتنی بر سیستم اطلاعات مکانی استفاده کرده‌اند. در این مطالعه براساس پژوهش‌های پیشین تعداد 9 معیار موثر بر مکان‌یابی نیروگاه خورشیدی انتخاب و لایۀ فضایی هر معیار با استفاده از سیستم اطلاعات مکانی تهیه و سپس وزن معیارها با استفاده از روش وزن‌دهی سوارا محاسبه شده است. براساس نتایج روش وزن‌دهی ترتیب اهمیت معیارها به‌صورت پتانسیل فتوولتائیک (0.172)، دما (0.137)، بارش (0.119)، فاصله از مراکز شهری (0.116)، شیب (0.111)، فاصله از راه‌ها (0.092)، فاصله از گسل‌ها (0.088)، فاصله از مناطق حفاظت‌شده (0.086) و ارتفاع (0.077) بوده است. در این مطالعه برای تهیۀ نقشۀ تناسب اراضی از دو روش تاپسیس و ایداس استفاده شده است. براساس نتایج روش تاپسیس و ایداس به‌ترتیب 21 درصد و 9 درصد از استان فارس تناسب بسیار بالایی برای احداث نیروگاه خورشیدی دارند. محققان در پژوهش حاضر شهرستان‌های استان فارس را ازنظر تناسب برای احداث نیروگاه خورشیدی اولویت‌بندی کرده‌اند. براساس نتایج دو روش تاپسیس و ایداس شهرستان‌های آباده، خرمبید و بوانات در اولویت اول تا سوم بوده است.

utilizing gis with swara, edas, and topsis multi-criteria decision-making (mcdm) methods for solar power plant site selection in fars province

abstractutilization of solar energy through construction of solar power plants has become a pivotal sector in the global energy landscape. iran, with its advantageous geographical and climatic conditions, possesses substantial potential for the development of solar power facilities and electricity generation. this study employed a geographic information system (gis)-based multi-criteria decision-making (mcdm) approach to identify optimal sites for solar power plants in fars province. 9 critical criteria identified through prior research were mapped using gis. the swara method was utilized to assign weights to these criteria, establishing a hierarchy of importance with photovoltaic potential ranked highest and altitude ranked lowest. the topsis and edas methods were then applied to produce a land suitability map, indicating that 21 and 9% of fars province were highly suitable for the construction of solar power plants, respectively. this research prioritized the counties of fars province for the establishment of solar energy facilities. keywords: solar power plant site selection, multi-criteria decision-making (mcdm), geospatial information system (gis). introductionthe demand for renewable energy as a substitute for fossil fuels has been rising in recent years. solar energy, one of the most prevalent forms of renewable energy, has garnered significant attention in developing countries due to its potential for sustainable, cost-effective, and environmentally friendly energy production. iran, a major oil and gas producer, primarily generates electricity from fossil fuel power plants, with solar energy representing only a minor portion of its electricity generation. despite having high solar radiation levels and numerous sunny days throughout the year, iran has yet to fully capitalize on its solar power potential. determining the optimal location for a solar power plant is a complex task influenced by environmental, climatic, and topographical factors, requiring scientific approaches. site selection involves evaluating potential areas and prioritizing locations that ensure high efficiency in electricity generation. by integrating multi-criteria decision-making (mcdm) methods with geographic information systems (gis), it becomes possible to effectively manage spatial information, analyze various locations, and assess their suitability for solar power plant establishment.this study employed an integrated mcdm approach based on gis for site selection of a solar power plant in fars province. gis was utilized to manage and prepare spatial data, while mcdm methods facilitated criteria weighting and development of a land suitability map. the swara method was applied to assign weights to the criteria and two mcdm techniques, topsis and edas, were used to integrate the spatial layers. materials & methodsin this study, geographic information system (gis) technology was employed for the collection, management, and visualization of spatial data, while multi-criteria decision-making (mcdm) techniques were utilized for weighting and integrating the decision-making criteria. initially, a comprehensive review of existing literature on solar power plant site selection identified 9 key criteria: photovoltaic potential, distance from protected areas, temperature, precipitation, elevation, slope, distance from urban centers, distance from roads, and distance from fault lines. subsequently, expert opinions were gathered and the swara method was applied to establish the weights of the decision-making criteria. relevant spatial data were collected and spatial layers for each criterion were generated through appropriate analyses within the gis environment. these spatial layers were then integrated based on the calculated weights using two mcdm methods: topsis and edas. the findings were analyzed, conclusions drawn, and results compared with previous studies to identify priority counties for solar power plant establishment.the swara method enhanced decision-making accuracy and efficiency compared to traditional methods like ahp by minimizing the number of pairwise comparisons. in this approach, experts ranked the criteria according to their importance and a reduction coefficient was applied to derive the weights. for generating the land suitability map, the topsis method was employed, evaluating each location based on its proximity to an ideal solution (best conditions) and its distance from a negative ideal solution (worst conditions). the site closest to the ideal solution and farthest from the negative solution was deemed the most suitable. additionally, the edas method was utilized to prioritize sites based on their distance from the average value, incorporating two key measures: positive distance from average (pda) and negative distance from average (nda). the site with the highest pda and the lowest nda was ranked as the optimal choice. research findingsthe results obtained from the swara method indicated that photovoltaic potential was the most critical criterion, while elevation was deemed the least significant. for land suitability mapping, both the topsis and edas methods were employed. topsis, a widely recognized method for solar power plant site selection, demonstrated high efficiency, while the edas method, being relatively newer and less explored, also yielded effective results. the findings from both methods were consistent, showing that the northern and northeastern regions of fars province were more suitable for solar power plant development. according to the topsis method, classification of land suitability for fars province was as follows: very high suitability (21%), high suitability (45%), moderate suitability (24%), low suitability (8%), and very low suitability (2%). in contrast, the edas method classified the province as follows: very high suitability (9%), high suitability (27%), moderate suitability (34%), low suitability (22%), and very low suitability (8%). additionally, the study prioritized counties in fars province for solar power plant development. both topsis and edas methods identified abadeh, khorrambid, and bavanat as the top three priority counties, while rostam, mohr, kuhchenar, kazerun, and farashband were ranked as the least suitable locations. discussion of results & conclusionthis study aimed to identify suitable locations for the establishment of solar power plants in fars province. the results demonstrated the effectiveness of integrating multi-criteria decision-making (mcdm) methods with geographic information systems (gis) for spatial decision-making. both the topsis and edas methods were employed to analyze and prioritize potential sites. the findings revealed a strong correlation between the results of these two methods, indicating that the northern and northeastern regions of fars province were more suitable for solar power plants, while the southern and southwestern areas were less favorable. additionally, this study highlighted the edas method as a more robust and stable alternative to topsis, suggesting that edas provides greater decision-making stability and reinforcing its potential for future applications. given the favorable solar conditions in fars province, application of these methodologies could significantly contribute to the development of sustainable energy and enhance energy efficiency in iran. the comprehensive framework utilized in this study—including problem identification, criteria selection, weighting, and decision-making—can be effectively adapted for solar power plant site selection in other provinces.