Solar Power Plant Site Research Articles

Solar power plant site selection using fuzzy inference system: a case study in Iran

Solar power plant site selection using fuzzy inference system: a case study in Iran

Enhancing Solar Power Plant Location Selection Through Multicriteria Decision-Making with the Analytic Hierarchy Process

Renewable energy, particularly solar power, is clean, cost-effective, and virtually limitless, making it an essential source of energy for developing countries. In the Kurdistan region, however, dependence on fossil fuels remains high, with 85 percent of electricity generated from these sources, whereas solar power contributes less than 1 percent. This study addresses this disparity by employing Boolean logical analytical hierarchy process techniques and a comprehensive set of criteria encompassing technical, ecological, and economic factors to identify suitable sites for solar power plants in Duhok Governorate. The results indicate that 68.5 percent of the governorate’s area is deemed suitable for solar power station construction, with the most promising zone comprising 132.2 km2 and capable of generating more than 8,000 megawatts of solar energy. Notably, most suitable areas are concentrated in the south and southwest, particularly in the districts of Bardarash, Shekhan, and Semel. This study paves the way for a significant shift toward renewable energy in northern Iraq. Identifying vast suitable areas for solar power plants offers a practical roadmap to reduce dependence on fossil fuels, provide a clean energy source, and enable a large-scale solar power project. This study empowers policymakers, energy companies, and investors to make informed decisions toward realizing this renewable energy potential, ultimately transforming the energy landscape in northern Iraq.

Developing a GIS-based multicriteria evaluation system for selecting suitable sites for solar energy power plants in Anambra state Nigeria

The increasing demand for clean energy in society raises concerns about alternative energy sources, making it difficult to rely solely on one or two sources of electricity generation. This study aims to develop a GIS-based multicriteria evaluation system for identifying suitable solar energy power plants in Anambra State, Nigeria. Key criteria include solar irradiation, land use, proximity to transmission lines, accessibility, slope, and environmental constraints. GIS tools and satellite imagery data are used to analyze and visualize these criteria, enabling an efficient decision-making process. The methodology includes data collection, selecting and determining criteria for suitable site selection, constructing a hierarchical structure of site selection procedure, data acquisition, classification of acceptable criteria and factors into rank of suitability, determining the relative importance of each criterion using AHP (Analytical Hierarchy Process) based on pair-wise comparisons, assessing the consistency of judgments through a pair-wise comparisons method, and producing the final evaluation map. The results provide valuable insights into identifying suitable sites for solar power plants in Anambra State and are advised for use in other parts of the country. The GIS-based multicriteria evaluation system facilitates location decisions and increases efficiency in dealing with solar energy power plant siting. The study workflow model is suggested for smooth and quick appropriateness analysis and easy export as a python script.

Suitability analysis of PV solar power plant sites in Gandaki province: Application of GIS and Remote sensing

The escalating global demand for energy has triggered a shift towards cleaner alternatives due to mounting environmental concerns. Emerging as a viable substitute, solar power has gained prominence as fossil fuels' adverse impact becomes evident. Historically reliant on hydropower, Nepal is exploring alternative energy sources to mitigate seasonal output variations. Despite abundant renewable resources like biomass, wind, and solar energy, Nepal's energy sector faces funding and technical expertise challenges. Solar energy presents significant promise as a primary renewable source in Nepal, boasting ample sunlight due to its location. However, the current solar capacity remains limited at around 54.6 MW, comprising less than 2.5% of the total installed capacity. The critical factor is the identification of suitable sites for solar power plants. Geographical Information System (GIS) and Multi-Criteria Decision-Making (MCDM) methods have been employed for suitability analysis. This study employs the Analytic Hierarchy Process (AHP), a robust MCDM technique, to assess site suitability. The research is carried out in the Gandaki province, Nepal, encompassing the Himalayan, Hilly, and Terai regions. Criteria like solar radiation, slope, aspect, land use/land cover, proximity to roads, and substations are considered. These criteria are reclassified into suitability categories based on expert opinions and guidelines. The results indicate areas highly suitable for solar power generation, covering 12.40 km2 (5.64% of the study area), followed by regions least suitable, spanning 7681 km2 (34.93% of the province's area). This research contributes to the effective deployment of solar power by identifying optimal locations for solar power plant construction, thus advancing Nepal's renewable energy goals.

GIS-Based Multi Criteria Analysis for Solar Power Plant Site Selection Support in Mecca

One of the major sources of renewable energy, particularly electricity generation and water desalination, is solar energy. The National Initiative to produce Water and Electricity started when the electricity consumption in Saudi Arabia begun to increase by about 5% per year. The current investigation aims to use a multicriteria GIS technique to identify the best spatial location for solar energy collection in the Mecca Administrative District. The best locations for solar power plant construction were determined with the use of a set of factors and criteria, including planning and environmental criteria, and terrain calibrator. These criteria were defined through a thorough literature review. This information was then used to create a digital geographic database, which was incorporated into an integrated GIS to produce a spatial fit model. According to the suitability data, most of Mecca region is ideal for solar energy projects, with an applicability percentage ranging between 30% and 80%. These findings are encouraging and promising for Mecca's renewable energy industry and they should be considered. It was discovered by examining these spatial locations and the level of suitability to the specifications that the lands with a sufficient share of more than 80% form an area of around 4000km2 and makeup 3% of all suitable lands. The governorates of the Mecca Administrative Area are home to most of these exceptionally suited locations. The Taif governorate takes first place with 35% of the total area and the two governorates of Turbah are placed second and third with 24% and 14%. In the Mecca Administrative Area, the appropriate lands for solar energy projects are distributed spatially according to a digital map. The study proposes incorporating the findings into the Saudi national plan for renewable energy sources.

Site Selection of Solar Power Plants Using Hybrid MCDM Models: A Case Study in Indonesia

Among developing countries in Asia, Indonesia has realized the importance of transitioning from fossil fuels to renewable energy sources such as solar power. Careful consideration must be given to the strategic placement of solar power installations to fully leverage the benefits of solar energy. This study proposes a methodology to optimize the site selection of solar power plants in Indonesia by integrating Data Envelopment Analysis (DEA), Fuzzy Analytic Hierarchy Process (F-AHP), and Fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (F-MARCOS) models. The proposed methodology considers quantitative and qualitative criteria to evaluate potential locations for solar power plants. In the first stage, DEA is used to identify the most efficient locations based on quantitative measures such as solar radiation, land availability, and grid connectivity. In the second stage, qualitative factors such as technological, economic, environmental, and socio-political aspects are evaluated using F-AHP to prioritize the most important criteria for site selection. Finally, F-MARCOS ranks potential locations based on the selected criteria. The methodology was tested using data from Indonesia as a case study. The results show that the proposed hybrid model optimizes Indonesia’s solar power plant site selection. The optimal locations can contribute to a cost-effective long-term renewable energy supply nationwide. The findings from this study are relevant to policymakers, industry stakeholders, and researchers interested in renewable energy development and site selection. However, to promote sustainable solar energy development, governments and local authorities must also enact supportive policies and mechanisms that encourage the adoption and growth of renewable energy technologies in Indonesia.

Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province

The applicability of a combined fuzzy best-worst method (FBWM) and geographic information system (GIS) was investigated to find the optimal location of a solar power plant site in Guilan province, which has a temperate and humid climate. Fifteen criteria were determined based on the guidelines and performance of photovoltaic (PV) systems and divided into four main categories: environmental, economic, technical, and social. The data were achieved from satellite images and organisations. The FBWM was applied to weight the criteria based on the opinion of the decision-maker, and then spatial analysis was done by GIS to find the potential sites for the solar power plant. The result of this study indicates that among the total area of Guilan province, about 0.74% is “the most suitable” region for solar power plants and 0.46, 0.54, 0.53, and 97.73% are in the class of “suitable”, “relatively suitable”, “least suitable” and “limited”. Four alternatives of A1, A2, A3 and A4 with an area of larger than 60,638 m2 which is the required area for a 10 MW solar power plant and a distance from power lines of less than 2 km, were selected. The techno-economic aspects were conducted among the four alternatives, which show that about a 35% increase of the feed-in tariff is necessary to decrease the payback period of the most economical site (A3) from 6.7 to 5 y, which encourages the investors of a PV power plant. Also, the greenhouse gas (GHG) emission analysis indicates that the construction of a 10 MW power plant on A3 could prevent the release of 10,113 t of GHG into the atmosphere annually.

A new interactive method based on multi-criteria preference degree functions for solar power plant site selection

Solar power energy is renewable and clean energy, widely used to produce electricity. Its unique properties have led to increasing demands in many countries. In this regard, the importance of Multi-Criteria Decision-Making (MCDM) in solar power plants, especially site selection problems, is increasingly on the rise. Thus, this study presents a new approach suited to the nature of this problem when the amount of the required investment is a critical aspect. As managers naturally cannot rely on methods that behave as a black box, this study renders a new approach that redefines the linear relations of Interactive Simple Additive Weighting (ISAW) by multi-criteria preference degree functions of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). In the proposed approach, an initial order of alternatives is gradually improved by swapping the order of a pair of alternatives until the decision-maker becomes satisfied. To validate the proposed method, we consider a case study of site selection for solar farms.

Application of choosing by advantages to determine the optimal site for solar power plants

Solar energy is a critical component of the energy development strategy. The site selection for solar power plants has a significant impact on the cost of energy production. A favorable situation would result in significant cost savings and increased electricity generation efficiency. California is located in the southwest region of the United States of America and is blessed with an abundance of sunlight. In recent years, the state's economy and population have expanded quickly, resulting in an increased need for power. This study examines the south of California as a possibly well-suited site for the constructing large solar power plants to meet the local electricity needs. To begin, this article imposed some limits on the selection of three potential sites for constructing solar power plants (S1, S2, and S3). Then, a systematic approach for solar power plant site selection was presented, focusing on five major factors (economic, technological, social, geographical, and environmental). This is the first time that the choosing by advantages (CBA) method has been used to determine the optimal sites for solar power plant construction, with the possible sites ranked as S2 > S1 > S3. The results were then compared with traditional methods such as the multi-criteria decision-making method. The findings of this study suggest that the CBA method not only streamlines the solar power plant site selection process but also closely aligns with the objectives and desires of the investors.

Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study

Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals.

GIS BASED SOLAR POWER PLANTS SITE SELECTION USING ANALYTIC HIERARCHY PROCESS (AHP) IN ISTANBUL, TURKEY

Abstract. Today, countries are shifting their energy policies towards to renewable energy sources. The main reasons for this can be summarized as the reduction of fossil fuel resources, resulting in cost increase and their harmful effect on the ecological balance. Since renewable energy sources are both economical and eco-friendly, for countries which have high solar energy potential such as Turkey, it is reasonable to direct their energy policies to solar energy which is a renewable energy source.In this study, the development of renewable energy legislation in Turkey, from past to present has been examined and implementation steps for the licenced and unlicensed generation of electricity from solar energy have been introduced. Ten impact factors have been identified as the first step for the implementation of the solar power plant site selection in Istanbul, which was determined as the pilot region. Impact factors weighted using Analytical Hierarchy Process (AHP) method. Concurrently, the weights of these determined impact factors were compared with the weights obtained by evaluating the results of the “Evaluation of Solar Energy Power Plant Site Selection Factors” survey conducted during the study. After obtaining the weights, the relevant data were collected and the necessary analyses were performed with the help of the GIS software and the most suitable places were provided for the solar power plant for Istanbul.

A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran

Identifying potential locations for installation of solar power plants is a critical step in utilizing sustainable energy resources. In this study, a GIS-based Multi-Criteria Decision Analysis (GIS-MCDA) technique is used to generate maps that represent potential areas for solar power plants in four provinces with different climate conditions in Iran. The concept of risk is included in the GIS-MCDA process using the Ordered Weighted Averaging (OWA) model. The OWA model can provide various risk-taking (optimistic) and risk-aversion (pessimistic) scenarios to determine the suitable power plant areas. The results of this study indicate that provinces located in an arid climate such as Yazd contain a more suitable area for the solar power plants compared to wet climate provinces (e.g., Mazandaran). The sensitivity analysis of results show that the criterion “fault” has the minimum effect while the criteria “slope” and “road network” have the maximum effects on the area of the highly desirable class.

Spatial Site Selection for Solar Power Plants Using a GIS-Based Boolean-Fuzzy Logic Model: A Case Study of Markazi Province, Iran

Selection of suitable sites for solar power plants requires spatial evaluation taking technical, economic, and environmental considerations into account. This research has applied a fuzzy logic model to carry out spatial site selection for solar power plants in Markazi Province of Iran. Geographical Information System (GIS) capabilities have been used for spatial analysis and visualization of the research results. The suitable areas for solar power plants installation were identified by employing Boolean logic and defining a range of selection criteria all of which were evaluated by fuzzy functions. The raster layers of Boolean and fuzzy logic have been combined to come up with suitable sites with solar energy potential. The results identified some areas in the vicinity of Mahalat and Zarandineh cities as suitable for solar energy utilization. The research also validated the employed combined method as a suitable site selection approach for solar power plants.

Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia

Site selection for solar power plants is a critical issue for utility-size projects due to the significance of weather factors, proximity to facilities, and the presence of environmental protected areas. The primary goal of this research is to evaluate and select the best location for utility-scale solar PV projects using geographical information systems (GIS) and a multi-criteria decision-making (MCDM) technique. The model considers different aspects, such as economic and technical factors, with the goal of assuring maximum power achievement while minimizing project cost. An analytical hierarchy process (AHP) is applied to weigh the criteria and compute a land suitability index (LSI) to evaluate potential sites. The LSI model groups sites into five categories: “least suitable,” “marginally suitable,” “moderately suitable,” “highly suitable” and “most suitable.” A case study for Saudi Arabia is provided. Real climatology and legislation data, such as roads, mountains, and protected areas, are utilized in the model. The solar analyst tool in ArcGIS software is employed to calculate the solar insolation across the entire study area using actual atmospheric parameters. The air temperature map was created from real dispersed monitoring sensors across Saudi Arabia using interpolation. The overlaid result map showed that 16% (300,000 km2) of the study area is promising and suitable for deploying utility-size PV power plants while the most suitable areas to be in the north and northwest of the Saudi Arabia. It has been found that suitable lands are following the pattern of the approximate range of the proximity to main roads, transmission lines, and urban cities. More than 80% of the suitable areas had a moderate to high LSI. The integration of the GIS with MCDM methods has emerged as a highly useful technique to systematically deal with rich geographical information data and vast area as well as manipulate criteria importance towards introducing the best sites for solar power plants.

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.