Optimal Location of Solar Photovoltaic Plants Using Geographic Information Systems and Multi-Criteria Analysis

By inergency On Mar 30, 2024

[ad_1]

1. Introduction

Energy is one of the most important vectors for social development, economic growth, and human well-being [1]. Thus, the seventh goal of the United Nations Sustainable Development Goals seeks to “Ensure access to affordable, secure, sustainable and modern energy”, one of the main targets of which is to “Increase significantly the share of renewable energy in the energy mix”.

The alternative lies in the exploration of renewable sources such as solar, wind, geothermal, biomass, and hydropower. The use of solar energy is one of the most popular renewable energies at present, along with wind energy. This is due to the fact that it is a naturally abundant resource, widely available and economical [2]. Solar and wind energy supply 90% of the renewable energy generated, accounting for 60% and 30% of total renewable energy production, respectively [3].

Solar energy is defined as the production of energy from irradiation from the Sun [4]. Given that it is a resource that can be easily harnessed almost everywhere on the planet, this was the renewable energy with the greatest increase in installed production capacity worldwide in 2021 [5], making it one of the best options for meeting future energy demands in a sustainable manner [6], as a consequence of the need to reduce greenhouse gas emissions [3].

Solar energy has two possible ways of generating energy, photovoltaic solar energy, and solar thermal energy [7]:

In the first alternative, the transformation of solar energy into electricity is carried out by photovoltaic panels, in which solar radiation excites electrons in a semiconductor device by generating a small potential difference by a photo-electrical process [8]. The electrons are able to transform and become part of a current in an electrical circuit [9].
In the second one, energy from the Sun’s rays is harnessed to generate heat in a clean and environmentally friendly way [10]. Electrical energy is produced when the heat drives a heat engine connected to a generator.

Solar photovoltaic technology has been the fastest growing renewable energy source in recent years as a result of the increased efficiency of photovoltaic cells, reduced manufacturing costs, ease of installation, and applicability in different environments [11]. According to the data, the installed capacity of solar photovoltaic energy has grown from 70 GW in 2011 to 942 GW by 2021 [12]. As a result of its simplicity of installation, low cost of service, low maintenance, reliable and silent investments, it accounts for most of the investments for the construction of large-scale photovoltaic power plants. The first photovoltaic installations were limited to 1 MW, however, as a result of the development of photovoltaic technology, it is now possible to build extremely large plants with a capacity of more than 100 MW [13].

The determination of the optimal site selection for photovoltaic plants is a fundamental process since this type of installation depends on environmental, technological, economic, and social factors that determine the economic, energetic, and constructive viability of a sustainable energy project [14]. In this type of spatial decision research, the most popular methodology for the determination of optimal site selection for photovoltaic plants is based on the combination of Multi-Criteria Decision Analysis (MCDA) or Multi-Criteria Analysis (MCA) and Geographic Information System (GIS) with the objective of evaluating the most suitable locations [15]. In general terms, the method is based on the determination of meteorological, climatic, topographical, economic, or social criteria [16], determining aspects that affect the solar resources and the condition of the terrain to house a photovoltaic installation, and then carrying out a multi-criteria analysis with geospatial information [17]. Multi-Criteria Analysis allows the assignment of weights to the criteria in order to analyze the relevance of some criteria over others by means of different methodologies such as Analytic Hierarchy Process (AHP), Network Analysis Process (NAP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to compare and evaluate the different site selection alternatives [18]. The criteria selected and the number of them are very variable from one research to another [15,19]. The energy criteria are those that refer to the energy production or photovoltaic power generation potential (PVOUT), which depends on environmental factors such as radiation, temperature, luminosity, humidity, or cloudiness, factors that vary rapidly, changing and conditioning the production of the photovoltaic panels [20]. Previous investigations consider these criteria by evaluating their average value over time, such as annual average temperature or humidity [21,22]. In contrast to the general conception, the present research proposes a typification of these criteria based on the measurement of the variables at three key points along the day to establish a representative average value that allows the selection of the optimal location. Similarly, this work proposes a methodology for the quantification of relevant qualitative criteria so that these can be taken into account in the multi-criteria analysis.

This research designs the procedure for carrying out a multi-criteria analysis, which allows the optimal location of photovoltaic solar plants to be sought while optimizing their energy production. The final result is a map in which the territory is classified according to its suitability for the implementation of this type of installation. At present, there are other studies with the same objective, which justifies the interest of this type of research, although the main difference is that this research focuses on the choice and quantitative treatment of the chosen criteria, as well as the weighting of these criteria in an objective, logical, and statistically consistent manner.

2. Classical Methodological Approach

The production of solar photovoltaic energy depends mainly on the solar radiation available on the Earth’s surface [23], which does not affect all regions of the world equally. Latitude is the main factor that determines the solar photovoltaic potential of a territory [24].

Based on this information, there are maps of photovoltaic potential in terms of the kWh that could be generated per m² [25]. These maps usually classify the Earth’s surface into zones where solar photovoltaic energy production can be most efficient.

The most relevant issue is that considering solar radiation as the most relevant factor, circumstances can change this situation:

Insufficient land area to make a significant difference in solar radiation.
Accumulation of factors that can modify solar radiation conditions independently (relief, orientation, etc.).
Criteria that, while affecting the performance of the installation, are not directly related to solar radiation (temperature, cloud cover, etc.).

Using this single criterion would lead to overly simplistic results. One of the main factors influencing energy production is climate. Nowadays, data are available to simulate multiple criteria to model the behavior of an installation in a way that is very close to reality, making it possible to find the optimum location, achieve high efficiency in generation, and optimize the use of the resource [26].

This research is justified on the basis of the current need for a procedure that allows a multi-criteria analysis applicable to large areas of territory, determining the optimal location of a solar photovoltaic plant. This research varies substantially from traditional procedures based on subjective weightings to determine the best location. This methodology proposes a novel combination and weighting, using a statistical procedure to evaluate the consistency of the weighting.

When performing a multi-criteria analysis for the optimal location of solar photovoltaic plants, one of the main problems is to consider various environmental, social, and technological criteria simultaneously, in order to decide where to install the photovoltaic panels. Geographic Information Systems (GIS) allow geospatial multi-criteria analyses to be carried out almost automatically over large areas of territory, by making decisions in a logical, objective, and rational manner [27,28], helping to determine the optimal location of solar plants, geothermal farms, wind farms [29], or the solution of conflicts in territorial planning processes [30].

2.1. Classification of Classical Criteria

Currently, there are several studies that apply multi-criteria analysis for the selection of the best location for solar photovoltaic plants [31,32,33,34]. The difference between all of them is the choice of criteria to be considered to determine the optimal location. However, certain criteria are decisive and common to most of the existing research in this field [35]. Most scientific research classifies the criteria into the following three main groups.

2.1.1. Energy Criteria

The energy criteria make it possible to determine the most suitable geographical areas solely on the basis of the amount of energy that the photovoltaic solar panels are capable of generating. There may be other socio-economic or environmental reasons, but if the solar plant is not energetically viable, the project will not be interesting. The most commonly considered energy criteria are:

Solar radiation. Defined as the amount of solar energy received by a point on the Earth’s surface (kWh/m²), it is one of the most important factors in determining solar energy potential. Since the intensity of solar radiation depends on its inclination on the Earth’s surface, it depends mainly on latitude. Several authors use this criterion to establish the optimal location for such installations [30,31,33,36]. However, it may be of little significance in small territorial analyses, with small latitude variations [37].
The temperature in the study area can be a key criterion for analyzing the optimal location [38]. Some authors consider areas with average temperatures between 10 and 20 °C to be suitable in terms of energy production [33]. The difficulty lies in choosing the representative temperature or parameter to use to assess this criterion [39].
The hours of sunshine per day are a decisive factor: the more hours of sunshine, the more energy production. Possibly for this reason, many authors consider this criterion to be one of the most important ones [33,40]. However, it presents the same problem as solar radiation for small areas of territory, as it depends mainly on latitude.
Orientation. This criterion determines the incidence of solar radiation, depending on the shaded areas due to the orientation of the terrain and its influence on generation [41]. South or southeast orientations are best suited to maximize electricity production [33,40].
Humidity. This criterion conditions energy production: solar radiation is absorbed by humidity, decreasing the incident radiation on the solar panel [34], and therefore energy production. Different authors qualify this criterion as fundamental in multi-criteria analysis [34,36], generally considering the number of rainy or cloudy days.

2.1.2. Geographical Criteria

This set of criteria aims to take into account a series of infrastructures that, although they do not allow for an improvement in energy production, facilitate the investment necessary to start up this type of installation. Among the criteria most commonly used in previous research, the following can be considered:

The slope of the terrain. This is one of the criteria that can have the greatest influence on the location of any installation of this type. An increase in the slope of the land can make the construction and installation of the photovoltaic plant unfeasible, as it increases the costs of construction and transport of materials. Various studies [32,34] include this criterion to be taken into account in multi-criteria analyses [42].
Grid connection. This is a necessary infrastructure that must be considered when analyzing the distance between the territory under analysis and the nearest electricity grid for a good location for the installation [43].
Accessibility. Proximity to transport/communication routes is essential to guarantee the viability of the photovoltaic plant [44], as they are necessary for the construction of the installation and subsequent access for operators [45]. This is one of the main geographical criteria and the most repeated in research of this type [31,33].
Classification and use of the land. The urban classification in the land use plan may make the location suitable if it is indicated for its use, or restrictive if it is on specially protected rural land [46,47].
Proximity to population settlements. This criterion has two aspects, given that the proximity of the plant to energy-demanding population centers reduces energy transport costs and energy dissipation, but the territorial organization restricts the location of generation plants within urban centers or cities [36].

2.1.3. Environmental Criteria

The third type of criteria used by most authors are environmental ones of a restrictive nature, considering areas that due to their features preclude the development of a project of this type [48]. There are certain areas of the territory that, given their high ecological value and vulnerability to certain external agents, are protected, preventing any activity from being carried out there [49]. These areas include the following:

Special Protection Areas;
Natura 2000 Network;
Areas of cultural and scenic interest;
National and Natural Parks;
River banks.

There may be many other criteria to be taken into account in an analysis for the optimal location of a solar photovoltaic plant, but the ones listed here are the ones currently used by different researchers in similar works and can be considered the most significant.

2.2. Weighting of Classical Criteria

Selecting the criteria whose analysis is most convenient to find the optimal location is the first step to carrying out a correct study using GIS. However, developing a multi-criteria analysis involves weighting the criteria appropriately, which is equally or more important than the selection of criteria itself [35].

In these cases, it is common to employ certain methods for weighting based on the use of weighted averages with generally random assignment of weights [50]. Examples of these methodologies are the Analytic Hierarchy Process, Network Analysis Process, Technique for Order of Preference by Similarity to Ideal Solution [18], Direct Ranking Method [51], Weighted Linear Combination [52], Linear Interpolation [53] or Inverse Variance Method [54]. There are also other methods that have fallen into disuse because they are considered less accurate, subjective, and unproven, such as the Multi-Attribute Utility Method (MAUT) [55] or the Outranking Approach Method [56].

5. Discussion

Like all research, its own development involves the achievement of a series of milestones, some fully developed and others partially. This implies a series of strengths and weaknesses of the research itself. In this sense, the main strengths of the research are as follows:

One of the main weaknesses of the methodology is the difficulty of having a good cartographic base. The DTM that allows obtaining the orientation and slope map is fundamental, as well as the map of roads, power lines, protected areas, etc.
Another weakness is the difficulty in obtaining information related to climate. In general, there are few meteorological stations; in the case of Cantabria (5300 Km²), there are 18 automated meteorological stations. Not all of them collect the type of data required in this research, especially cloudiness, and the historical data in this type of station are very small compared to the 30-year series recommended for the use of meteorological data.
The lack of coincidence of the administrative boundary of the region and the perimeter of the enclosure of the points corresponding to the locations of the meteorological stations used in the climate modeling produces interferences in the results in these areas. In order to correct them, other meteorological stations of bordering regions should be taken. In the case of Cantabria, there are 18 weather stations that do not coincide in the perimeter of Cantabria and three bordering regions with their respective meteorological centers, so it was decided to work only with the weather stations of Cantabria, being aware that there are such interferences at the edges of the map.
The results obtained by applying the proposed criteria are based on their treatment by applying the AHP method, which is the most common and widely used method [15,18]. However, the result may vary when using other methods such as those previously mentioned, such as the Network Analysis Process, Technique for Order of Preference by Similarity to Ideal Solution, Inverse Variance Method or Outranking Approach Method.
The methodology proposed to typify the criteria referring to energy, climate, or environmental parameters dependent on the time variable, such as radiation, temperature, cloudiness, humidity, etc., can be extrapolated to other site selection studies for other renewable energies such as wind power. However, modifications must be made. The proposal is oriented towards weighting and valuing these factors during daylight hours, which are those in which it is possible to take advantage of solar radiation. If other sources of energy were considered, e.g., wind energy, the selection of the timeframe should consider those hours in which optimal wind conditions are more likely to exist.
The selection of criteria is one of the fundamental phases of this research. However, when considering previous works from other authors, many discrepancies can be observed from one proposal to another, and there is no consensus regarding the minimum or maximum number of criteria to be used. Software development makes it possible to implement a greater number of criteria and therefore to carry out a more complete analysis. Nevertheless, the weight of all the criteria evaluated and their incidence must be taken into account, in order to avoid evaluating criteria that are not quite relevant. In the same way, other criteria that have not been considered in this proposal and are outside of the performance of the installation, such as social acceptance or economic costs, could be included.
The proposed methodology is based on the analysis of the optimal location of photovoltaic power plants based mainly on energy, geographic, and environmental criteria. These criteria focus to a large extent on the performance and energy production of the installation, by addressing issues related to energy efficiency and current regulations with the aim of establishing the most sustainable plant possible. However, it is also possible to consider other aspects discussed in the Life Cycle Analysis (LCA), such as social, environmental, or landscape impact, as well as the final phase of decommissioning and environmental rehabilitation. The inclusion of potential new criteria may allow a richer analysis, requiring modifications in the classical assignment of weights to the criteria by means of the Analytic Hierarchy Process.

The application to a territory of reduced extension such as Cantabria has favored the rigor of the study by being able to detail the final results to a greater extent, in addition to the possibility of being analyzed with greater knowledge of the area. In addition to this, obtaining the information has been simpler as a single autonomous community has been considered for administrative reasons, and due to the knowledge of the databases to be used to search for this information. The interpretation of the results shows that there is a very interesting area located in the geographical center of Cantabria, which obviously responds to the main groups of criteria: energy, geographic, and environmental aspects. It is a well-communicated area with a different climate from that in the south of Cantabria, where sunshine is undoubtedly higher, but temperatures are much more extreme, both in winter and summer. This goes against the simplistic thinking that the further south the better the area to locate solar plants, and fully validates the methodology developed.

6. Conclusions

Multi-Criteria Analysis using Geographic Information Systems is a fundamental tool for determining the optimal location of a solar photovoltaic plant since it allows the analysis and interpretation of georeferenced data, solving complex planning and land management problems. Thus, if a methodology can be established to determine optimal locations for renewable generation plants, in this case, solar photovoltaic plants, it will be easier to establish possible areas where they can be installed, in addition to locating them in places where their efficiency is as high as possible.

The methodological proposal that emerges from this research establishes which criteria are the most important when carrying out a multi-criteria analysis of this type, how each of them should be treated, and how to weight these criteria objectively, being able to subsequently check whether the weighting is consistent or not. These are the three main contributions of this research, which marks a before and after of the procedures traditionally used.

By means of the proposed methodology, an analysis of a specific territory such as Cantabria is carried out. From this specific analysis, it can be concluded that the proposal developed in this research allows for obtaining a map where the best areas of the territory for the location of a hypothetical plant are established. This proposal first specifies the criteria to be used, then defines a mechanism for the quantification of the criteria themselves, and finally establishes a weighting method between criteria, going from a qualitative comparison to a quantitative one, which also allows checking its consistency. Nevertheless, the main contributions of the research lie in the typification of the mainly energetic or climatic criteria dependent on the time variable, the quantification of qualitative criteria or variables, the proposed number and selection of criteria and last and less important, the Saaty valuation method. In contrast to the classification based on the average annual temperature, the proposal based on the average value of the measurement in three representative hours throughout the day allows a better adjustment of the criteria to the real behavior of the variable during the daytime hours of operation of the photovoltaic plants. The quantification of criteria allows variables such as cloudiness to be included in the analysis in a measurable way, as well as a particular criteria selection focused on optimizing plant performance for the target location.

All this means that the proposal can be considered a very innovative one since it provides both a vision and analysis of the criteria that are different from all those that have been used in similar projects up to now, as well as a weighting method that can be contrasted. In addition, the new methodological proposal can be applied or extrapolated to any other region of the planet.

[ad_2]