Despite the availability of large and varied quantities of energy resources such as coal, crude oil and natural gas, Nigeria has been facing energy crises for many years. Also, the electricity generated has been inefficiently distributed thus compounding the nation's energy problem. Consequently, the country's industrial and socioeconomic development has stagnated. Successive Nigerian governments have realized the seriousness of this problem and have embarked on laudable action plans to deal with the energy crisis (Fadare, 2009). A more serious attention has been devoted to harnessing of renewable energy resources especially solar and wind power. It is in this bid that Energy Commission of Nigeria instituted Research and Development (R&D) centers across the country to come out with solutions. However, this laudable effort has been bedeviled by a major challenge such as land scarcity in many areas that have been found to be technically and economically feasible to develop wind or solar power projects (Grassi, 2012). In view of this fact, a research problem arises; search for sites where solar or wind energy potentials exist that also have large tracts of land. There is therefore need to map out sites that have high wind or solar energy potentials that also possess the size of land needed to develop those sources of energy.
In view of this obvious need to map out sites that have high solar or wind energy potentials and at the same time possess some land size adequate for the development of solar or wind energy that the Geographic Information System (GIS) come to mind as a veritable tool for the spatial description of suitable sites. While, GIS is a strong tool, it is apt to consider it as a decision making component that operates through both manual and human judgments to solve a given problem (Jankowski, 1995). According to (Chen, 2009) combining GIS and Analytical Hierarchy Process (AHP) has gained much acceptance because of GIS ability to generate enormous data from varied sources and AHP ability to produce acceptable weights from a large criterion.
Finding suitable sites for the development of Nigeria's wind and solar energy resources is therefore more than justifies. This research sets out to develop a method of assessing potential sites for developing wind and solar energy using a GIS-based Multi-criteria analysis, thereby resolving the problem of suitable land.
LITERATURE REVIEW
Geographic Information System (GIS) is considered an indispensible tool for spatial data description and manipulation, it was reported that it is not strong enough as a decision supporting tool; it requires a decision making component and for that reason it operates through manual methods and human judgments for problem solving (Jankowski, 1995). Similarly, another weakness in the present GIS approach as a tool, it is unable to process varieties of criteria and challenging objectives (Carver, 1991). However in the last few decades, advanced methods and techniques have been developed in GIS, making it a powerful supporting tool for spatial planning. For example, many times overlay and buffer functions are used in site location studies, but these types of Geoprocessing tools are still incapable of manipulating multiples of challenging objectives (Hansen, 2005). Also a multiple of underlying variables makes it difficult for overlay operation to differentiate variables of differing importance (Janssen & Rievtveld, 1990).
Similarly, Multi-criteria methods have the ability to handle and combined variables parameters for assessment in different manners and at the end offered guidance to the decision-maker in solving problems (Gil-de-Castro, 2010). Also, (Malczewski, 2006) reports of an efficient use of GIS-MCDA in evaluating land suitability problems in a number of times in waste management, forest, natural hazard management, agriculture, and ecology . On the other hand the main problem in multi-criteria analysis is its ability to generate weights that are convincing and acceptable.
As part of Multi-criteria decision analysis (MCDA) the Analytical Hierarchy Process (AHP) determines the weights which have been one of the basic problems in multi-criteria decision analysis. The process is based on three principles: decomposition, comparative judgment and synthesis of priorities. The (AHP) is a mathematical technique of evaluating difficult decisions related to many criteria (Saaty, 1977). Combining GIS with AHP has gained much acceptance because of the new approaches ability to bring together enormous data from different source to produce acceptable weights from large criteria (Chen, 2009).
In a GIS-based study for optimized siting of municipal solid waste land fill, multi-criteria decision analysis (MCDA) method with an overlay analysis using Geographic Information System (GIS) to locate the most suitable site for the construction of land fill was employed. A number of factors were considered in the process including: geology, water supply resources, land use, sensitive sites, air quality and ground water quality. Weights were later assigned to each criterion depending upon their relative importance and ratings in accordance with the relative importance of their impact. The result of the study confirms the effectiveness of the method in the selection process (Sumathi, 2007).
Coupling GIS with AHP to locate appropriate points for installing power towers has been reported (Bahmani, 2011). It has been postulated that AHP methods are helpful in calculating the cost function of the transmission line between towers. GIS with multi-criteria analysis (MCA) using Analytical Hierarchy Process (AHP) to locate suitable sites for building additional housing areas in Sana'a city in Yemen was also conducted. The method was found to be successful in locating optimum land suitable for housing (Al-SHALABI, 2006).
Similarly, at the beginning of this millennium some studies have emerged that allow buffer distance to be carved in urban areas, water bodies and historic sites to prevent wind farm development in sensitive areas in some European countries( (Babban & Parry, 2001) (Hansen, 2005)). At the present, numerous researches are being conducted in the field of renewable energy employing GIS spatial capabilities. These include research for wind farm siting, photovoltaic electrification, biomass assessment stand out (Dominguez & Amador, 2007).
Also (Gastli & Charabi, 2009) has examined solar electricity prospect in Oman using GIS-based solar radiation maps. At the end of the study, the researchers were able to mapped areas with high potentials of solar radiation; however factors such as roads, rivers, urban areas and sensitive areas were not considered in the analysis. On the other hand, in a study on solar thermal plants in West Africa site selection and potential assessment, used overlay technique in GIS to examine a number of criteria which includes sufficient solar radiation, proximity to transmission lines and low slopes value. The findings show that the intersected areas to be suitable for concentrating solar power development (Ramde, 2011).
In a related study in Colorado (USA) (Janke, 2010) the multi-criteria GIS modeling of wind and solar farms to identify which land cover classes are attached to wind and solar potentials. The overlay technique was used to examine the relationships between the land cover classes and solar and potential data. Even though, the attempt was successful in determining the relationship, the overlay technique has been found to be incapable of handling underlying multiples of variables.
Spatial analysis of renewable energy in the greater Southern Appalachian Mountains (USA) focused on finding multiple renewable energy sources using GIS in the region; any area that did not meet a criteria in one of these set (slope and aspect, land use, conservation restriction) were assigned a zero value in the model, while those that met the criteria were assign the value of 1 (Arnette & Zobel, 2011) .
Therefore, idea of locating and mapping renewable energy resource is not new in the developed countries where large amount of research has been done. In contrast, very little research has been done in locating and mapping solar and wind energy resource in developing countries including Nigeria especially using GIS techniques.
STATEMENT OF THE PROBLEM
The energy crisis in Nigeria has been of serious for many years. Although there are abundant energy resources in the country, the inadequate electricity generation and poor distribution are the central part of the crisis that has strangled the economic development of the country (Adaramola & Oyewola, 2011). It has been estimated that less than 50 percent of Nigeria's population have access to electricity. Also less than 10 percent of electricity goes to rural population who form the majority. Nigerian government is putting effort to end the energy crisis through development renewable energy resources especially solar and wind (Fadare, 2009).
Moreover, a number of studies in the country have examined the availability and viability of generating electricity from wind and solar renewable energy sources. However, one of the problems of developing wind or solar projects is land availability, where it is technically and economically feasible to develop the projects (Grassi, 2012). A location may have the highest wind or solar resources but may be not viable for wind or solar farm (van Haaren & Fthenakis, 2011).
The aim of this research is to examine the factors that will play key role in finding the most suitable land for wind and solar farm development in Nigeria.
Research questions
The research attempt to answer the following questions:
What types of land cover are associated with high wind and solar potentials in Nigeria?
Which areas are suitable for siting wind and solar farm in the country?
What are the spatial-temporal variability of solar and wind energy in the study area?
Which factors account for the variability of solar and wind energy?
What is the prospect of establishing solar-wind hybrid in some areas for complementariness?
Research objective:
The aim of this research is to use a GIS-based Multi-Criteria Analysis to assess suitable sites for locating wind and solar farm development in Nigeria. This will be achieved through the following objectives:
To assess which land cover types are associated with high potentials of wind solar energy in the country.
To assess the spatial-temporal variability of solar and wind energy in the study area.
To examine factors that account for the variability of solar and wind energy.
To explore the prospect of establishing solar-wind hybrid in some areas for complementariness.
METHODOLOGY
Data Sources
The research will use varied of data from different sources. These data include wind speed and solar radiation from Nigeria Meteorological Agency (NIMET), land cover, roads, rivers, wet lands, agriculture, forest and protected areas. These data will be digitized from high spatial resolution satellite image of Nigeria. Similarly, digital elevation data such as slope, elevation and aspect for the Nigeria will be derived from shuttle radar topographic mission (SRTM) data. Others include transmission lines data across Nigeria and area energy demand data.
The data collection method to be use will be based on field measurement and scanning of hard copies for digitization of relevant data which will be stored in a GIS database. The wind speed and solar radiation data are continuously being recorded at strategic locations across the country and the archive of the data are kept by Nigeria Meteorological Agency (NIMET) and are accessible to users on payment. The table below shows different data and their sources.
Table 1: Type and Sources of Data.
Data type
Derived data
Sources
Availability
High spatial resolution satellite image of Nigeria
Land cover, roads, rivers, wet lands, agriculture, forest, protected areas, settlements, Built up areas
Vendor
On payment
Solar radiation
Annual average solar radiation
NIMET
On payment
Wind speed
Measured at 10m height above ground for ten years
NIMET
On payment
Transmission lines map(scanned)
Power transmission line
Power Holding company Nigeria(PHCN)
On request
SRTM
Elevation, slopes and aspect
Online
Free
Data Analysis
The data collected will be processed using of Geographic Information System (GIS) and Multi-Criteria Decision Model (MCDM). The Analytical Hierarchical Process (AHP) will also be used to determine weights for each criterion based on the preference in solar and wind development or suitable model adopted from literature. Criteria for wind farms includes avoiding mountain summits, steep slopes, woodlands or densely populated areas and the sites should be close to roads and existing power transmission lines( (Babban & Parry, 2001) (AHI, H.H, & H.Y, 2009)). Similarly, it has been suggested that the criteria for solar farms should include land cover or vegetation shades, access to roads, closeness to transmission line/substations and population density, however other factors such as hours of sunshine, irradiance, temperature and aspect must be taken into account to maximize potential (Carrion, 2008) .The criteria adopted will be subjected to decomposition, comparative judgement and synthesis of priorities. After pair wise comparison has been developed in Microsoft Excel the results will be transferred into ArcGIS 9.3 framework for spatial analysis.
Also, overlay delete operation on the areas propose to be constrain will be use to identify the associated land cover types (available land). In response to question what land cover types are associated with high wind and solar potentials in Nigeria? Similarly, land suitability analysis will be done through (AHP) weighted overlay which assesses the suitability of grid cells by weighting and combining factor maps. This will be use to map areas suitable for wind and solar farms.
