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The unique properties of solar energy have led to increasing demands in various countries. In order to use solar energy effectively, environmental and geographical circumstances related to solar intensity must be considered. Different factors may affect the selection of suitable locations for solar plants. These factors must be considered concurren...
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... The DEA approach has also been used to evaluate the best location for solar PV panels in Japan [36], in Turkey [37] and in Iran [38]. [39] compare 25 cities in Iran based on a combination of DEA, Principal Component Analysis (PCA) and Numerical Taxonomy (NT) to determine the optimal site for solar PV installation. ...
... Scope Methodology Time period [39] 25 cities in Iran DEA, PCA and NT Unspecified [40] 150 solar plant units in Iran ANN and FDEA Unspecified [20] 8 solar cell industries in Taiwan DEA 2010-2011 [22] 32 solar firms in Taiwan DEA and AHP Unspecified [21] 12 solar cell companies DEA 2011 in Taiwan [36] 16 cities in Japan DEA Unspecified [23] 160 PV power stations DEA 2012 in Germany and in US [37] 30 cities in Turkey DEA 2010 [41] 15 solar plant sites DEA and FDEA Unspecified in Taiwan [25] 40 PV companies in China SBM 2009-2013 and in US [24] 160 PV power stations DEA 2012 in Germany and in US [27] 855 commercial rooftop PV DEA 2008-2012 systems in the USA [28] 855 commercial rooftop PV DEA 2008-2012 systems in US [26] Photovoltaic power generation SE-DEA 2005-2015 in China [29] 70 solar PV power plants Three-stage DEA 2010 in the USA [30] 84 solar panel sectors DEA 2014 in South Africa [31] Crystalline silicon and DEA Unspecified thin-film PV solar cell industries in Iran [32] 16 Solar PV panels in India DEA and Shannon's entropy Unspecified [42] 46 potential sites in Vietnam DEA, FAHP and TOPSIS Unspecified [33] 42 photovoltaic poverty Three-phase DEA Unspecified alleviation projects in China [34] 118 PV plants in China DEA 2012-2016 [38] 44 sites in Iran DEA Unspecified [43] 20 cities in Taiwan DEA and AHP Unspecified [35] 21 solar mini-grids DEA and AHP 2010-2019 in Bangladesh [44] 27 locations in Vietnam DEA, G-AHP and G-TOPSIS Unspecified efficiency, there are no studies that focus on predicting the efficiencies estimated by DEA. This is however necessary to support the decisions of policy makers. ...
Solar photovoltaic (PV) energy has emerged as a potential alternative to carbon-based energies to meet the Paris agreement commitment. This study investigates the effect of environmental variables on the efficiency of solar PV panels. Data Envelopment Analysis (DEA) is used to estimate efficiencies of 91 solar PV panels located in Australia during the time period 2010–2020. The effects of environmental variables on the estimated efficiencies are quantified using the truncated regression model. Random forest is then used to predict efficiency of solar PV panel in every city of Australia. The results allow to determine the most suitable location and regions for solar PV energy production in Australia. This study provides an interesting and easily interpretable tool for policy decision makers.
... A research study performed in a rural district of Germany involved the use of a GIS-based AHP approach to find the best location for a wind farm [12]. Another study conducted by Sozen et al. involved the use of data envelopment analysis and the TOPSIS method to evaluate 30 cities in multiple regions of Turkey in order to find the best city for the location of solar power plants [13]. Because solar energy is the most abundant source of sustainable energy, various MCDM methodologies have been used to find the best location for solar power plants. ...
Turkey is one of the most suitable countries for solar power plants, owing to its ideal location in terms of receiving solar radiation; accordingly, plans are in place to expand its solar power plant system to fulfill the increasing energy demand. In this study, a combination of multicriteria decision-making and fuzzy logic was used to evaluate potential locations (cities in southern Turkey) to install new solar power plants subject to different criteria of an uncertain nature. The proposed methodology has several attractive features, which are described throughout this study. The criteria were selected based on the literature and the opinions of experts. In addition, a new criterion (capacity of existing solar power plants) was added to achieve more precise results. Ten criteria and eighteen cities were selected to form the decision matrix for the problem. First, the weight of each criterion was computed by stepwise weight assessment ratio analysis (SWARA). Then, the TOPSIS approach was extended to the Pythagorean fuzzy form in ranking the locations of the decision matrix as a new solution procedure. The results show that the best candidate city to install a new solar power plant is Antalya, followed by Karaman and Malatya as the second and third best candidates, respectively. Finally, to measure the impact of the changes in the weight of the criteria, a sensitivity analysis was conducted. Multiple scenarios were considered, and the results indicated that Antalya was the best alternative in most of the scenarios.
... Asakereh et al. (2014) developed a Geographical Information System (GIS)-based fuzzy AHP model for selecting solar energy sites in Shodirwan region in Iran. Sozen et al. (2015) applied the TOPSIS method for the selection of the best location for solar plants in Turkey. Sindhu et al. (2017) used a hybrid combination of AHP and TOPSIS to select an appropriate site in India. ...
Dual hesitant fuzzy set (DHFS) is an encyclopedic set that comprises fuzzy set, intuitionistic fuzzy set, and hesitant fuzzy set as its particular cases. Knowledge and accuracy measures in various vague environments are useful to study the problems in decision-making and pattern analysis. In this paper, we first propose a knowledge and accuracy measure based on DHFSs and contrast their performance with some existing measures in the dual-hesitant fuzzy environment. We also show the application of our proposed information measures (knowledge measure and accuracy measure) in solving the problem of site selection for the installation of a solar power plant. In the site selection problem in context of our proposed measures, we also investigate the suitability of an appropriate multiple criteria decision-making method. Finally, we show the application of our proposed dual-hesitant fuzzy accuracy measure in pattern recognition, where we show how our proposed accuracy measure is better than some exiting distance and similarity measures of DHFSs.
... Another method commonly used in performance evaluation is the TOPSIS method. The TOPSIS method, one of the MCDM methods, is applied in many fields such as production, finance, aviation, location selection, equipment selection, energy, technology and education [Seçme et al., 2009;Sozen et al., 2015;Mardani et al., 2015;Rouyendegh et al., 2018;Wang, Pham, 2019;Kumar, Anbanandam, 2019;Akçetin, Kamacı, 2020;Ersoy, 2021]. The EDAS method is another MCDM method used in performance evaluation. ...
Globalisation, international trade, tourism, and economic and technological
advances have contributed to the development of the aviation industry. In a globally competitive
environment, airports need to use their resources efficiently and evaluate their
performance to compete with their rivals. Data Envelopment Analysis (DEA) is a widely
used method in the performance evaluation of airports. This study was aimed to measure
the performance and ranking of selected major international airports in 2019 and the first
quarter of 2020 using the DEA method, the Technique for Order Preference by Similarity
to Ideal Solutions (TOPSIS) method, and the Evaluation Based on Distance from Average
Solution (EDAS) method. Efficiency analysis has been carried out using CCR-DEA models.
Later, performance evaluation of the alternatives was made according to the TOPSIS
and EDAS methods. In this study, the ranking of the airports has been compiled according
to the results of the DEA, TOPSIS and EDAS methods. The study found that the use
of the DEA method together with Multi-Criteria Decision-Making (MCDM) methods such
as TOPSIS and EDAS for the performance evaluation of airports allows a full and clear
ranking of decision-making units (DMUs).
... Another widely used method in performance measurement is the TOPSIS method, which is one of the multi-criteria decision-making (MCDM) methods [17][18][19][20][21]. TOPSIS technique has many application areas such as finance, education, manufacturing, evaluation of technology investments, location selection, information technology and energy [17,18,[22][23][24]. ...
... Sozen et al. [22] were used the DEA and TOPSIS methods together to choose the best place for the solar plants in 30 different cities in Turkey. The study was carried out in 12 months of 2010. ...
Depending on the global world conditions and technological developments, the education and job status of people are constantly changing. In the competitive environment of today, as in many other sectors, it has become necessary to compete with the competitors in the education sector and to open up to new markets. Universities are the most important education centers where qualified human resources are trained. Universities offer different types of education along with people's lifestyles and technology. Distance education has become increasingly widespread in recent years as it can meet human needs. It has become necessary for universities to evaluate their performance to compete with their competitors in distance education. In recent years, data envelopment analysis (DEA) and technique for order preference by similarity to ideal solutions (TOPSIS) are widely used in performance evaluation. In this study, it has been aimed at performance evaluation of distance education departments of public universities in Turkey for the 2018-2019 academic year by using the DEA method and the TOPSIS method. In the study, it has been also aimed to compare and rank the efficient decision-making units as a result of efficiency measurement among themselves. The study has been carried out using 6 input and 4 output variables. As a result of the efficiency analysis using the CCR-DEA model, 7 universities were efficient and 49 universities not. Later, the efficient universities have been ranked using the super efficiency CCR-DEA model and TOPSIS method.
... Amy H. I. Lee et al. [14] integrated MCDM model to set the assurance region (AR) of the quantitative factors, and the AR is incorporated into data envelopment analysis (DEA), additionally adopting a fuzzy analytic hierarchy process (FAHP) for the location of a PV solar plant. Adnan Sozen et al. [15] presented an approach for the location of solar plants by data envelopment analysis (DEA). Ali Azadeh et al. [16] presented an integrated fuzzy DEA model for decision making on wind plant locations. ...
Following the recent development trend in the struggle for cleaning the earth’s environment, solar is the one of most promising area that can partially be used as a replaceable energy from non-renewable fuel sources. As such, it plays a significant role in protecting the environment from global warming. As solar power does not emit harmful gases into the atmosphere, its production, distribution, setup, and operation are vital should the production remain constant. Even solar energy waste emissions are small; when compared to current energy sources, the amount of harmful gases is negligible. This paper presented an integrated approach for site of solar plants by using data envelopment analysis (DEA) and Fuzzy Analytical Network Process (FANP). Furthermore, these integrated methodologies, incorporated with the most relevant parameters of requirements for solar plants, are introduced. First, the paper considers an integrated hierarchical DEA and FANP model for the optimal geographical location of solar plants in Mekong Delta Region, Vietnam. Using the proposed model for implementation would allow the renewable energy policy makers to select and control the optimal location for allocating and constructing a solar energy power plant in Vietnam. This is the preferred strategy for location optimization problems associated with solar plant units in Vietnam and around the world.
... For these models nine factors as inputs and one factor as output were used. These factors have been discussed by Sözen et al. (2015) as important parameters in selecting location of solar plants. As can be seen in Table 4 and Table 5 the results from CCR, BCC, KAM models by the SFA models are different. ...
Exponential development of solar photovoltaic projects during the past decades has vastly relied on findings from location identification analyses. This article draws upon the most important site selection factors in order to identify optimum locations for development of solar plants in Turkey from a subset of thirty selected Turkish cities. This study applies CCR, BCC, stochastic frontier analysis (SFA) and Kourosh and Arash Model (KAM) methods in decision-making. KAM method is a new powerful technique in measuring efficiency of firms (DMUs) and has obtained an important role in economy and managements. It also benefits from the novelty of using copula technique in the SFA methods which has been only recently presented to the literature.
... applied a fuzzy analytical hierarchy process (AHP) with a GIS-based approach to locate appropriate solar energy sites in Iran [10]. Sozen et al. utilized a data envelopment analysis and TOPSIS to select suitable sites for solar plants in Turkey [11]. Lee et al. located a photovoltaic solar plant in Taiwan using integrated fuzzy ANP and Višekriterijumsko Kompromisno Rangiranje (VIKOR) [12]. ...
Cement-based materials are primary resources used in construction. The increase in requests for and consumption of cement products, especially in Iran, indicates that more cement plants should be equipped. This study developed a geographical information system using pairwise comparison based on grey numbers to identify potential sites in which to set up cement plants. A group of five experts compared the effective criteria using the data for South Khorasan province. After filtering numerous sites, an area with potential locations for construction of a cement plant was identified. The selection of the potential area considered the distance to mines, access roads, gas source, and faults. Classification maps were surveyed for land use, pedology, and topography. The potential area was resulted in the north of the province based on the importance weights of 0.307, 0.301, 0.17, 0.087, 0.082, 0.04, and 0.032 for the criteria of land use, proximity to mines, proximity to access roads, proximity to gas substations, topography, pedology, and proximity to faults, respectively.
... Cannistraro, et al. [27] shows some examples of a smart island that proposes the use of RES for sustainable development. Sozen et al. [28] used TOPSIS technique for solar plant location by planting analysis. Akkas, et al. [29] proposed an AHP approach to select suitable sites for solar power plants. ...
In Turkey, current energy generations are not sufficient for the existing energy needs and besides, energy demand is expected to increase by 4–6 percent annually until 2023. Therefore, the government aims to increase the ratio of renewable energy resources (RES) in total installed capacity to 30 percent by 2023. By this date, total energy investments are expected to be approximately $110 billion. Turkey is the fastest growing energy market among the OECD countries. Therefore, Turkey is an attractive market for energy companies and investors. At this stage, site selection and deciding appropriate RES are the most important feasibility parameters for investment. In this study, “Site Selection in Turkey” issue for RES (solar, wind, hydroelectric, geothermal, biomass) is evaluated by the ELECTRE which is one of the Multi Criteria Decision Making (MCDM) methods. In addition, the reasons for choosing this method are explained according to the literature. The study emphasizes the importance of energy generation from renewable and sustainable sources and is concerned with improving the position of the country. The Turkish government offers many purchasing guarantees and high incentives, especially in the renewable energy sector. As a result of the analysis, the most suitable energy sources are presented according to the geography and energy potential of the regions. The study aims to inform energy firms and everyone related with RES about Turkey’s RES opportunities.
... Choudhary and Shankar used fuzzy TOPSIS AHP to select a thermal power plant site in India [16]. Mousavi [20]. Singh developed an extent fuzzy AHP based approach to select the best geographical locations of facilities under a real time process [21]. ...
Accurate site selection of a processing plant could result in decreasing total mining costs. The site selection problem could be solved by multi-criteria decision-making (MCDM) methods. This paper introduces a new approach by integrating fuzzy AHP and gray MCDM methods to solve all decision-making problems. The approach is applied in case of a copper mine area. The critical criteria are considered as adjacency to the crusher, adjacency to tailing dam, adjacency to a power source, distance from blasting sources, sufficient land availability, and safety against floods. After studying the mine map, six feasible alternatives are prioritized using the integrated approach. The results indicated that sites A, B, and E take the first three ranks. The separate results of fuzzy AHP and gray MCDM confirm that alternatives A and B have the first two ranks. Moreover, field investigations approved the results obtained by the applied approach.
