Site suitability analysis of Solar PV Power generation in South Gonder, Amhara Region

Currently, Ethiopian government looked towards renewable energy resources to generate electrical power for the country needs. 85% of the total population of the country live in rural areas and use wood and fossil fuel for their domestic uses. Using wood and fossil fuel is danger for users and the environment. And the government of Ethiopia planned to electrify 85% rural community with abundantly available renewable resources around the community. Therefore, identifying potential locations for solar Photovoltaic with geographic information system is a decision support tool for proposing the suitable sites to stakeholder. The solar Photovoltaic suitability analysis provides optimal locations to solar Photovoltaic power plant installations. To find suitable locations for Solar Photovoltaic , factors that affect the suitability were identified and weighted by using Analytical Hierarchy processes. Then the weighted values and reclassified values were multiplied together to produce the final suitability map to solar Photovoltaic. Due to site unsuitability, solar Photovoltaic the efficiency drops and may malfunction. By identifying the most suitable locations, solar PV power plant was optimally located. Therefore, the objective of this study was to find the most suitable sites in South Gonder Zone for generating power from solar Photovoltaic . The suitability of the study area for solar Photovoltaic power plant was 86.5%. Eighty six (86%) of the criteria considered in the study area was found to fulfill all the criteria to be suitable for solar Photovoltaic power plant. Most of the suitable areas were found in the western part of the zone. Nature topography is a key factor in generating solar energy; it affects the solar irradiance coming to the solar Photovoltaic panel surface.


Introduction
Renewable Energy is derived from natural process constantly. It is economically feasible, easy to use, less pollution, and abundant in nature. Therefore, renewable energy is more important than none renewable sources of energy. Using renewable energy maintains the environment and does not contribute to global warming [1,2]. In the context of Ethiopia, it is not good condition, since most of the families use wood and fossil fuel for their domestic uses. This will affect development of country and health of community. The development of country depends on exploiting renewable energy resources, and to use it optimally. Ethiopia is blessed with an abundance renewable energy resource like solar, wind, hydro, and others. Amahara is the region, where these renewable energies are available throughout the year [3,4].
Ethiopia has a higher potential to exploit renewable energies for domestic applications.
This vast renewable energy resources potential is not exploited sufficiently in the country, primarily due to the lack of scientific and methodological know-how in regards of planning, site selection, and technical implementation. A further constraint prohibiting their utilization is that the real potential of these resources locations are not well-known, because of the lack of research emphasis [3,4].
Even though the government of Ethiopia recently, took steps towards renewable energy resources, there is problem in identifying the exact resources locations. The efforts were not organized and this is due low number of researches to explore locations in Ethiopia .Therefore, the aim of this study was to find suitable locations for solar PV in four districts (Dera,Estie, Farta,and Foger) of South Gonder Zone Amhara region, Ethiopia ( Fig. 1).

Study Area And Data Settings
A suitability analysis for solar power installation was conducted in South Gonder Zone, Amhara region. Amhara region is located the north-western parts of Ethiopia between 9 0 20ꞌ and 14 0 20ꞌ North latitude 36 0 20ꞌ and 40 0 20ꞌ East longitude. Its area is estimated about 170000 square kilometres [5]. The region has twelve zones, and there was no more electricity access to town and the surrounding community in these zones.
In locating suitable areas for solar power plants ArcGIS10.4.1 was used. To analysis site suitability, none suitable sites were excluded like towns, water bodies, schools/protected areas and the weight of criteria was formulated for decision making [6][7][8]. Data set rasterizing and reclassifying have been conducted on vectors and raster layers like solar irradiance, distance from roads, towns, soil, slope, land use land cover, forest, stream and distance from school areas respectively. Finally, reclassified data were combined by using ArcGIS overlay tool [9][10][11].
The datasets were obtained from different sources in vector formats and then vector data were converted to raster with conventional tool of ArcGIS10.4.1. Thus the raster outputs of data sets were reclassified and finally overweighed to show results for finding suitable sites [12][13][14].
There are three tasks, in finding the suitable areas for solar power plant installations.

1.
Data preparation and criteria formulation as the nature of the study areas, then insert the data into ArcGIS10.4.1 software as layers.
Overlaid the reclassified data 2.1 Analytic Hierarchy Process (AHP) for criteria Evaluation Analytic Hierarchy Process (AHP) is one of multi criteria decision making method. Thus a pairwise comparison method was used to make complex decision problems in this paper.
The input was obtained from subjective opinion like satisfaction feelings and preference.
The pairwise comparison of the attributes makes it easy to decisions for complex problems. It compares the importance of the two the attributes at one time (Table 1). Table 1 Fundamental Scale for Pairwise Comparisons [13,15] Degree importance Definition Explanation 1 Equal importance Criteria equally important to the objective 3 Moderate importance One criteria slightly importance over another 5 Strong importance One criteria strongly importance than another 7 Very strong importance One criteria very strongly importance than another 9 Extreme importance One criteria extreme importance than another 2,4, 6,8 Intermediate values A compromise is needed

Selecting criteria for solar Photovoltaic installation
In finding the potential sites for solar power plant, site selection is depending on the weights of each layer. Opinions of experts were used to determine each site selection criterion for locating solar PV [10,11,16]. Solar Irradiance, roads, town, soil, slope, land use, land cover, forest, stream and schools were used to create a model to identify suitable locations for solar PV as per nature of the study area (Table 2). The normalized decision matrix of solar PV power plant was obtained by summing up the column and divides it to each cell value ( Table 3). The normalized values were calculated from the decision making matrix (A ij ) as: Where N is normalize value J is the column of the matrix C is the values of column of the decision In identify the potential sites for solar PV power plant; site selection was depending on the weights of each layer ( Table 4). The weights of the criteria were calculated from normalized matrix (A nm ) as: Where W is weights of the criteria n is the row values of normalized matrix x is the number of criteria for suitability analysis Table 3 Normalized decision matrix of solar PV power plant

2.3.1Solar irradiance reclassification
The solar irradiance was the most dominance factors to find the most suitable location for solar power plant. The solar irradiance dataset was taken from National aeronautics and space (NASA) surface metrology which represents the average of daily totals of global horizontal solar irradiance in kWh/m 2 [7,[19][20][21].
The Twenty years, yearly average solar irradiance layer was downloaded from NASA.
As the national renewable energy laboratory report [22]. Areas with 3.56Kwh/m 2 solar irradiance per day are economically feasible. Therefore, areas less than 3.56Kwh/m 2 solar irradiance per day was considered as unsuitable in the study ( Table 5). The raster solar irradiance was reclassified to unsuitable (< 5), moderately suitable (5-5.5), suitable (5.5-6), and highly suitable (> 6) Kwh/m 2 per day respectively (Fig. 2). Transportation cost was the dominant factor for any power plant installations. Thus the areas far from roads are economically infeasible and unsuitable. Therefore, areas less distance than 500 m was selected as highly suitable sites for solar [12,21,23]. Areas with distance (500-1000m) suitable, (1000-5000m) moderately suitable and greater (1500 m) unsuitable were prioritized respectively (Fig. 3).
The Euclidean distance was used for road data reclassifications in ArcGIS tool and the Euclidean distance were reclassified as below ( Table 6).

Reclassification of slope
The surface of the earth was an important factor in finding suitable locations for solar power plant. The earth gradient affects the receiving radiation from the sun. Thus, flat areas receive the most radiation and produce more energy from solar PV [5,6,24].
Areas less than 3% gradient were reclassified as highly suitable and greater than 10% gradient was unsuitable (Fig. 4). The slope reclassification data sets were shown that the Western part of the zone was more flat (Table 7). On the other hand eastern part was higher slope areas.

Land use, land cover
Land use, land cover was a key factor in finding optimal location solar PV power plant.
Cultivate/agricultural areas, forest areas, urban areas area were excluded in this study [5,14]. The open areas were considered as highly suitable areas for solar power plant installations (Fig. 5).

Distance from town
Distance from towns was another important factor in finding suitable sites for solar PV power plant [5,25]. The farthest distance from town was considered as highly suitable and the shortest was considered as unsuitable for solar PV in this study (Table 8). The town dataset was reclassified to highly suitable (> 6 km), suitable (4-6Km), moderately suitable (2-4Km), and unsuitable (< 2 Km) (Fig. 6).

Distance from schools
Historical paces, recreation areas and Schools were excluded in indicating optimal locations for solar PV power plant [2,17,26]. Based on the nature of the study area, the distances from school were reclassified into four categories, i.e less than 300 m, 300-400m, 400-1000 and greater than 1000 m ( Table 9). The farthest distance from schools were considered as highly suitable areas and the shortest distances were considered as the unsuitable sites for solar PV power plant (Fig. 7).

Distance from stream
The solar power plant locations were affected by the streams and water bodies. The most far locations were the most suitable locations [11,27,28]. The streams were reclassified into four main categories depending on the distance from the sites. The more far locations were taken as more suitable and the nearest locations were taken as unsuitable (Fig. 8).
The distance greater than (2000 m) highly suitable, (1000-2000m) Suitable, (500-1000) moderately suitable, and less than 500 m was unsuitable respectively (Table 10). The solar radiation is highly affected by forest shadow [1,19,29]. Thus farther the distance from the forest was considered as the most suitable and the nearest distance was considered as unsuitable locations (Table 11). Forest dataset was reclassified into four classes in this paper, greater than (120 m) highly suitable, (80-100) suitable, (30-60m) moderately suitable, and less than (30 m) unsuitable ( Fig. 9).

Soil reclassifications
Soil was also an important factor in finding optimal location solar PV power plant. The support erection of the solar PV is influenced by the type's soil. Thus luvisol was considered as the most suitable for support erection of solar PV and laptosol was considered as unsuitable for support erections [5,30].
The based on the nature of study area soil type was reclassified into four main categories, these were (luvisol) highly suitable,(fluvisol)suitable,(vertisol)moderately suitable, and (laptosol) unsuitable (Fig. 10).

Weighted overlays of Solar Photovoltaic suitability analysis
All weights of the criteria were combined by using the ArcGIS10.4.1 weight overlay tool.
The reclassified data set of the criteria which includes solar irradiance, distance from roads, distance from schools, and distance from town, slope, and distance from forest, soil type, and land use land cover were overlaid to the aggregate base on its weight [9,18,21,31].
The final map of suitability was obtained by multiplying each reclassified value with each weight value and summing up all layer products. The range of solar PV suitability was from one to four. Thus study area was separated into four main categories and highly suitable areas for placing solar PV Value was one (Table 12).

Result And Discussion
The Western and South-West part of South Gonder were suitable for solar PV from the candidate locations. This, mainly, due to high solar irradiance, low slope, short distance from roads, far from town, and far from forest, and far from stream. The North-Western areas were also suitable in addition to Western and South-Western parts of South Gonder and there were some solar potential areas in the South-East of the Zone. The most unsuitable areas were found in North-East parts of Zone due to near to the forest and Gumara stream (Fig. 11).  Figure 1 The Map of Amhara Region and the study area Suitable slopes for solar Photovoltaic  Suitable town distance for solar Photovoltaic Suitable school distance for solar Photovoltaic Suitable stream distance for solar Photovoltaic Suitable forest distance for solar Photovoltaic Figure 10 Suitable soils for solar Photovoltaic Figure 11 Suitability map of solar Photovoltaic