Spatial Multi-Criteria Analysis (MCA) for Airport with Air Traffic Control Tower Site Selection based on GIS Platform

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAir transportation is fast growing, and safety is of paramount importance in order to protect lives of passengers and crew as well as the properties of commercial airlines and airports facilities providing services to air travelers. To maintain safety and minimize the risk of air traffic accident, it is necessary to put in place adequate infrastructures like the airports with air traffic control tower that will support air traffic and provide accessibility to passengers utilizing air as a medium of transportation to move from one location to the other. Choosing a location to site an airport can be a complex problem because of multiple factors such as maneuverability of aircraft, movement of passengers, location of warehouse and government authorities like security, immigration and customs which need to be considered and most times are influenced by personal interest, political interest or religious affiliations while neglecting safety. Furthermore, airport is a gigantic project that requires substantial allocation from the federal budget in order to fund it, and hence requires careful consideration and critical analysis to make sure that such a project will maximize its potential when completed. Geographic Information Science (GIScience) based approach which is devoid of human influence can be used in solving a complex problem like choosing a location for airport with air traffic control tower. In this study, GIScience based approach such as spatial multi-criteria analysis (MCA) which combines analytic hierarchy process (AHP) with experts’ opinion is used to build a model which produced suitability map for site selection of airports with air traffic control tower in Nigeria. This study discovered that distance to road network (38%), distance to settlement (26%), and slope (12%) are the most contributing criteria in the suitability map. Comparative analysis also showed that 10.4% and 58.3% of existing airports with air traffic control tower are in areas classified as highly suitable and moderately suitable respectively

An integrated multiple layer perceptron-genetic algorithm decision support system for photovoltaic power plant site selection

There is a need for non-renewable energy sources in generation of power for almost every domestic and commercial purposes. This source of energy helps in the development of a country. Because of the increasing usage of the fossil fuels and depletion of these resources, our focus has been shifted towards the renewable sources of energy like solar, water and wind. Therefore, in the present scenario, the usage of renewable sources has been increasing rapidly. Selection of a solar power plant (SPP) requires environmental factor, local terrain, and local weather issues. Thus, a large amount of investment is required for installation. Multi-criteria decision making (MCDM) is a method that identifies one in choosing the best sites among the other proposed options. This paper gives a detailed study of optimal ranking of SPP site using analytical hierarchy process (AHP), multiple layer perceptron (MLP) neural network trained with back propagation (BP) algorithm and genetic algorithm (GA). Three SPP sites of India were considered and various important criteria like local weather, geographical location, and environmental factors are included in our study as SPP site selection is a multi-criteria problem. A precise comparison of these three methods is listed in this paper

Selection of biogas, solar, and wind power plants’ locations: An MCDA approach

This study discusses a multi-criteria approach to locating biogas, solar and wind power plants that significantly addresses the challenge of global warming caused by power generation. Because the utility of locations to build renewable energy power plants depends on economic, social and environmental dimensions, after reviewing literature, the sustainable frameworks of criteria affecting the location of biogas, solar and wind power plants were examined in this paper. The offered frameworks are applied to determining the site of biogas, solar, and wind power plants in Iran. The provinces of Iran are assessed as alternatives in this paper. To compute the weight of criteria in the offered framework, data from a sample of experts in Iran are used via an online survey form designed based on the best-worst method (BWM). Using the results of the BWM and the performance data, the overall score are calculated for the various provinces of Iran. The results of this study indicate that energy saving, effect on resources and natural reserves and wind flow, respectively, are the most effective factors for determining the place of biogas, solar and wind power plants, and South Khorasan, Khuzestan, and Khuzestan show the best result for establishing biogas, solar, and wind power plants in Iran respectively

Wind energy potential for the electricity production - Knjazevac Municipality case study (Serbia)

Geospatial potential for harvesting wind energy is not an easy task to perform in conditions of deficiency of accurate data in remote and large areas (macro to medium locations). There are different methodologies available to identify the most suitable location for the installation of wind power generators. One of the most suitable approaches that employ the Multi-Criteria Analysis method for wind energy potential of the Municipality of Knjazevac (East Serbia) is combining the Analytic Hierarchy Process (AHP) and Geographic Information Systems. Collection and creation of geospatial data for the research encompassed meteorological data from all available sources, digital elevation model (DEM) to analyze the orography of the terrain, and Landsat 8 satellite data to analyze six land cover (LC) classes. The identification of three best locations for the wind power generators (wind farms) using Multi-Criteria Decision Making (MCDM) analysis solved the major location problem: how to select the best locations for investment in the renewable energy sector and minimize the impact on the environment. The result indicates that only one part of the municipality, at the hub height of 100 m, has enough wind potential to produce energy

Mapping concentrated solar power site suitability in Algeria

The investment in solar thermal power technologies has become increasingly attractive, despite their still perceived high costs. Algeria presented an ambitious plan for increasing the participation of renewable energy sources (RES) in the power system, with significant investments foreseen for solar power technologies. To achieve this objective, it is necessary to identify optimal sites for the implementation of these plants, as well as others where implementation is highly inadvisable from the economic, social, or environmental points of view. The main goal of this study is to present and apply a methodology to identify adequate locations for the installation of solar power plants in Algeria. The study addressed the particular case of concentrated solar power (CSP) and proposed a hybrid approach combining multi criteria decision making and Geographic Information System. The approach allowed mapping and visualizing unfeasible areas and ranking the feasible sites. The results showed that more than 51% of the territory of the country is unfeasible for the implementation of CSP, mainly due to criteria related to topographic aspects, water availability, and distance to the grid. The results demonstrated that relying only on Direct Normal Irradiation (DNI) values may result in a reductionist vision for energy planning and thus other criteria can play a fundamental role in the decision process. The model allowed also to identify the best regions for CSP investment and opens routes for more detailed studies for the exact site selection.The authors would like to thank all open source data providers and ESRI Maps for provide the background maps. Also authors thank J. R. Oakleaf et al. for make available spatial data linked to global potential for renewable energy. The authors are also thankful to experts of the research center CDER and the engineering experts who participated in the AHP for their assistance

Suitability analysis for implementing wind and solar farms based AHP method: Case study in Inner Mongolia, China

As important green energy, wind power and photovoltaic power have great development prospects. The suitability evaluation of wind and solar power plants is a popular research field, which is related to the sustainable and healthy development of wind and solar power generation. In this paper, based on multiple dimensions such as land types, climatic conditions, topographic features and policy environment, we selected 10 indicators and combined (analytical hierarchy process) AHP method to build a suitability assessment model for evaluating the suitability of solar and wind power in Inner Mongolia, China. The findings revealed that, Inner Mongolia has a great potential to generate wind and solar electricity, for wind power, the category of ‘excellent’ regions covers 83855 km2 and represents 7.10% of the total surface area; for solar power, 7.66% (nearly 90420 km2) are classified as ‘excellent’. The suitability of both solar and wind energy in the western region is considered to have the most suitable development region, parts of Alxa League and Bayannur City have great potential for combined wind and solar power generation. The research results could provide important technical and data support for capacity evaluation and power station location decision

Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland.

Offshore wind energy takes up an important place in Ireland’s renewable generation portfolio thanks to its abundant offshore wind resource. Optimal offshore site selection and developing site-specific energy policy instruments are of key importance to the success of offshore wind energy investments. In this respect, this study aims at developing a multi-criteria decision-making (MCDM) model considering technical, economic, environmental and social criteria to assess Ireland’s most promising offshore wind sites in terms of their sustainable development. An interval type-2 fuzzy sets based MCDM model is developed that integrates the score function with positive and negative solutions to achieve better results. Moreover, advanced energy economic metrics such as levelized cost of electricity with higher resolution are integrated into the decision-making process to make more precise decisions. Case studies are conducted for the five of the offshore sites in development pipeline. Results are compared to those of other state-of-the-art MCDM methods. It is found that Arklow Bank-2 is the most favorable site while Sceirde is the least site. The ranking of other sites is found to be Oriel>Dublin Array>Codling Park. It is shown that the proposed approach is superior in terms of stability and implementation as compared to its counterparts