Saman Nadizadeh Shorabeh; Najmeh Neisany Samany; Yaghob Abdali
Abstract
Extended Abstract Introduction There is a huge potential in the usage of renewable energy sources because these natural resources are inexpensive and harmless to the environment. Solar, wind, and geothermal energies are among the renewable energies. Solar photovoltaic (PV) technology is one of the fastest ...
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Extended Abstract Introduction There is a huge potential in the usage of renewable energy sources because these natural resources are inexpensive and harmless to the environment. Solar, wind, and geothermal energies are among the renewable energies. Solar photovoltaic (PV) technology is one of the fastest growing renewable energy technologies across the world. Solar energy is a practical and suitable technology, especially in arid areas with high solar energy potential. The first step in using renewable energy in Iran was in 1994, and since then, much attention has been paid to this type of energy in the society and the government. In Iran, 850 million tons of greenhouse gases are produced annually. Consequently, renewable energy sources such as solar energy can have a significant impact on reducing the greenhouse gas emissions. The integration of GIS and MCDA helps the decision maker to perform decision analysis functions such as ranking the options to select a suitable location so that the GIS is used as a powerful and integrated tool for storing, manipulating and analyzing the solar energy criteria. The use of the MCDA method can facilitate the evaluation and selection of the most appropriate location (s), taking into account the key criteria in the decision-making process. In this study, the optimal areas for the construction of the solar power plants have been identified in five highly optimistic, optimistic, moderate, pessimistic, and highly pessimistic levels using the spatial criteria and the OWA model. One of the most prominent features of this research in relation to the other articles is the inclusion of the concept of risk into the solar power plant site selection process to determine the optimum areas for the construction of solar power plants using the OWA model. Materials and methods The primary data used in this study include the Digital Elevation Model (DEM) derived from the Aster satellite data for the extraction of solar radiation and the region slope, the extraction of the mean land surface temperature for 2017 using the Terra Sensor MOD11A1, the preparation of the average map of the vegetation for 2017 using MODRA13A2 Terra sensor, the 1.250000 fault map prepared by the geological organization, the statistics and data of the rainfall prepared by the Meteorological Organization of Chahar mahal-o-Bakhtiari province, shapefile of road network prepared by the Organization of Roads and Urban Development, the climaticshapefile of the country prepared by the Iran Meteorological Organization, the shapefile of urban areas generated by the National Cartographic Center (NCC).The proposed methodology works by employing AHP to obtain the appropriate weights for each criterion, and utilizing OWA to extract suitable locations to varying degrees of risk. Sensitivity analysis for the criteria weights were conducted by virtue of the OAT method. Results and discussion The northern sectors of Razavi Khorasan province are endowed with cold temperatures and cold mountainous climate, which has had a substantial contribution to the increased cloudy and rainy days as well as the relatively extensive vegetation cover in this area. In this light, with respect to all ‘ORness’s, the target areas fall within the ‘very unsuitable’ and ‘unsuitable’ classes for construction of solar power plants. Moreover, the high slope factor in these areas has contributed to high levels of surface radiation, albeit, as the slope criterion is considered a constraint, the target areas are, in fact, not suitable for the construction of solar power plants. Moving southwards, the suitability of the regions, in terms of construction of solar power plants, tends to shift in the positive direction (very suitable class), which is most likely the result of the low rainfall and vegetation cover in conjunction with high surface temperatures in these areas, as opposed to their counterparts in the north. Areas falling within the very suitable class for construction of solar power plants in Razavi Khorasan can be realized by dint of calculating the percentage of area attributed to each class at ORness = 0.5 per city. The findings show that cities located towards the south and southwest of the province contribute to the highest area in the suitable class, while counties in the northern regions have the lowest share of area in the very suitable class. The highest sensitivity in locating suitable areas in Razavi Khorasan province were observed among the factors of slope, road, and urban criteria. Alterations in the weights assigned to these criteria would entail a significantly strong impact on the extent of the very suitable class. This highlights the significance of accurately determining the weights for these three criteria in Razavi Khorasan Province. Based on the findings, the rate of change in weight assigned to the of fault criteria ranges from 0 to 0.2, which in turn causes substantial change in the area of regions in the very suitable class extent. However, setting the criteria weight at between 0.2 and 1 appears to have no significant effects in the area of this class. Conclusion The results of this research indicate that the northern parts of Razavi Khorasan province are highly unsuitable and unsuitable for all of ‘ORness’ values, while a significant extent of the highly suitable class for the construction of solar power plants is comprised of sectors of the southern regions. Areas within the very suitable class corresponding to an ORness=1 comprise 5% of the class, whereas those with an ORness=0 have a 74% share. The three cities of Ferdows, Bardaskan, and Gonabad, had the highest share of the area attributed to the very suitable class (0.8-1), as maintained by a per city analysis of the area for each class. However, the cities of Dergas, Quchan, Mashhad, and Kalat had no share of the areas within the very suitable class. This most probably stems from the high geographic latitudes of said regions, which has engendered unsuitable climatic conditions in these areas. Finally, results from sensitivity analysis of the criteria showed that increases in the weights assigned to the factors of slope, road, and urban criteria, would cause a further increase in the area of the very suitable class. Stated differently, the selection of suitable locations for the establishment of solar power plants is highly sensitive to these criteria. Changes in the weight of the surface temperature criterion had no considerable effect on the area of the very suitable class. Moreover, shifts in the weight allotted to solar radiation and precipitation in the province, ranging from 0 and 0.6, brought about substantial changes in the area of the very suitable class. Whereas, shifts within the 0.6–1 range had no significant effects on the area of the very suitable class.
Ali Asghar Abdollahi
Abstract
Extended Abstract Introduction Most of the energy consumed in the world comes from fossil fuels. Combustion of fossil fuels enters a huge amount of sulfur and nitrogen oxides, carbon monoxide and carbon dioxide in the atmosphere. Continuous increases in greenhouse gas emissions and rising fuel prices ...
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Extended Abstract Introduction Most of the energy consumed in the world comes from fossil fuels. Combustion of fossil fuels enters a huge amount of sulfur and nitrogen oxides, carbon monoxide and carbon dioxide in the atmosphere. Continuous increases in greenhouse gas emissions and rising fuel prices are key drivers behind more effective efforts to use renewable energy sources. Renewable energies include diverse sources of natural and accessible energy. Given that these energies are not ideal, their use reduces the consumption of oil products and creates jobs and reduces the amount of environmental pollution. The prospect of using this energy in Iran, as well as other developed countries, has become significant in the way that the government has made the necessary planning in the fifth development plan. Therefore, considering the global policies of developing these energies in our country, in order to solve problems and create employment, will be inevitable. Studies in this regard suggest that the development of the use of new energy can play a significant role in increasing the security of the country's energy system. Due to low latitudes, Iran has more capability to receive this energy. To exploit this energy, there is a need to build solar power plants. Solar panels used in solar power plants are converters of solar radiation into electrical energy. One of the most important issues in using solar energy is determining where to use it, which has a great impact on the efficiency of solar power equipment. Therefore, taking advantage of the potential of the climate can have a positive effect on the conservation of energy resources. In this regard, it is important to identify appropriate and prone areas where solar energy is sufficient and able to replace current energies. Materials & Methods The required data in this study was collected from the ‘Iran’s Meteorological Organization’ for 30 years and was entered into the Excel environment and analyzed. In the Arc GIS software environment, the locations of the stations, according to their geographical coordinates, were added to the digital map of the area and the database was formed. To prepare the map of the climatic parameters, the layer for each parameter was first prepared using the IDW interpolation method in the Geo-statistical Analyst field in the ARCGIS software environment, and then, using the AHP method, an intra-layer weight was defined. By using the ‘Reclassify’ command in the ARCGIS software, each layer was classified into several classes and each class was classified according to its importance and mapped to it. Then, to obtain a final map representing potential regions, the interlayer weight was applied according to the importance and effectiveness of each layer. Then, by overlapping the weighted layers, using the ‘Fuzzy overlay’ command in the ‘Spatial Analyst’ section, a map of all-potential regions that represents the areas with high potential for the construction of the power plant was obtained. Discussion and Results In order to quantitatively evaluate the climate of solar power plants in the study area, the layers obtained from the sunshine, cloudy, dust, relative humidity, altitude and precipitation have been weighted. For this purpose, the weight of the effective indices has been obtained using the AHP model. Then, using the ‘Raster calculator’ command in the ARCGIS software, weighted difference maps were obtained, and finally, using the ‘Fuzzy overlay’ command in the same software, the final map which is a combination of overlapping of the harmonious layers, has been obtained. At last, the final map was made up of a combination of overlapping harmonious layers and the selection of the regions with the highest capacity for the construction of solar power plants. Conclusion The method used in this study is important in determining the effective indices in locating solar stations as overlapping of the harmonious layers. This method is achieved by taking into account the relative importance of all the effective indices in the final layer, which can be more credible than other methods, because this algorithm, using degree weights, gives the power to decision- makers to place more important factors which in his view affect the problem more, in the problem with the same importance and due to this superiority, the results of this method has a better resolution.. Accordingly, the results show that Fars province has a high potential in terms of solar electrical energy which in the study area, the cities of Neyriz, Estahban and Fasa are more indicative in this regard and have higher potential. It can also be concluded that the total relative weight of all indices has a greater effect on locating and cannot be determined only by one or more of the indices.
