Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan
The Republic of Kazakhstan has significant deposits of fossil fuels and is one of the largest energy producers among the countries of Central Asia. At the same time, The Republic of Kazakhstan is one of the richest countries of the world in terms of renewable resources, evaluated to over 1000 billio...
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8813086/ |
| _version_ | 1818323385273286656 |
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| author | Ravil I. Mukhamediev Renat Mustakayev Kirill Yakunin Sophia Kiseleva Viktor Gopejenko |
| author_facet | Ravil I. Mukhamediev Renat Mustakayev Kirill Yakunin Sophia Kiseleva Viktor Gopejenko |
| author_sort | Ravil I. Mukhamediev |
| collection | DOAJ |
| description | The Republic of Kazakhstan has significant deposits of fossil fuels and is one of the largest energy producers among the countries of Central Asia. At the same time, The Republic of Kazakhstan is one of the richest countries of the world in terms of renewable resources, evaluated to over 1000 billion kWh/year. The application of therenewable energy sources (RES), both on a large scale and at the level of a single household, ensures the transformation of the energy system to a “green state”. However, these initiatives should be substantiated by relevant supportive information to promote transformation of the country's economy to a qualitative ecological state.The paper covers developed multi-criteria decision-making system (MCDM) and software tools for processing of spatial heterogeneous data which could be applied for evaluation of the RES potential.The developed system serves to evaluate the potential of usable RES as it allows the assessment of a territory of the country in terms of installing photovoltaic and wind generators.A feature of the proposed MCDM is the use of an analytical hierarchical process (AHP) in combination with the Bayesian approach, which allows obtaining two complementary assessments of the territory areas. The method allows a rough estimate in an event of lack of data.The verification performed based on the available data on the installed solar and wind power stations shows that the system gives a relatively small root-mean-square error within 15%. |
| first_indexed | 2024-12-13T11:11:51Z |
| format | Article |
| id | doaj.art-3dac0c1032b14f5ea8a1163bd30f50c7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T11:11:51Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3dac0c1032b14f5ea8a1163bd30f50c72022-12-21T23:48:42ZengIEEEIEEE Access2169-35362019-01-01712227512228810.1109/ACCESS.2019.29376278813086Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in KazakhstanRavil I. Mukhamediev0https://orcid.org/0000-0002-3727-043XRenat Mustakayev1https://orcid.org/0000-0002-7341-0452Kirill Yakunin2https://orcid.org/0000-0002-7378-9212Sophia Kiseleva3https://orcid.org/0000-0001-5836-8615Viktor Gopejenko4https://orcid.org/0000-0002-7783-4519Institute of Cybernetics and Information Technology, Satbayev University, Almaty, KazakhstanInstitute of Information and Computational Technologies, Almaty, KazakhstanInstitute of Cybernetics and Information Technology, Satbayev University, Almaty, KazakhstanDepartment of Geography, Lomonosov Moscow State University, Moscow, RussiaDepartment of Natural Science and Information Technologies, ISMA University, Riga, LatviaThe Republic of Kazakhstan has significant deposits of fossil fuels and is one of the largest energy producers among the countries of Central Asia. At the same time, The Republic of Kazakhstan is one of the richest countries of the world in terms of renewable resources, evaluated to over 1000 billion kWh/year. The application of therenewable energy sources (RES), both on a large scale and at the level of a single household, ensures the transformation of the energy system to a “green state”. However, these initiatives should be substantiated by relevant supportive information to promote transformation of the country's economy to a qualitative ecological state.The paper covers developed multi-criteria decision-making system (MCDM) and software tools for processing of spatial heterogeneous data which could be applied for evaluation of the RES potential.The developed system serves to evaluate the potential of usable RES as it allows the assessment of a territory of the country in terms of installing photovoltaic and wind generators.A feature of the proposed MCDM is the use of an analytical hierarchical process (AHP) in combination with the Bayesian approach, which allows obtaining two complementary assessments of the territory areas. The method allows a rough estimate in an event of lack of data.The verification performed based on the available data on the installed solar and wind power stations shows that the system gives a relatively small root-mean-square error within 15%.https://ieeexplore.ieee.org/document/8813086/Decision making support methodsgeo information systemsintelligent information technologiesheterogeneous datamachine learningrenewable energy |
| spellingShingle | Ravil I. Mukhamediev Renat Mustakayev Kirill Yakunin Sophia Kiseleva Viktor Gopejenko Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan IEEE Access Decision making support methods geo information systems intelligent information technologies heterogeneous data machine learning renewable energy |
| title | Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan |
| title_full | Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan |
| title_fullStr | Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan |
| title_full_unstemmed | Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan |
| title_short | Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan |
| title_sort | multi criteria spatial decision making supportsystem for renewable energy development in kazakhstan |
| topic | Decision making support methods geo information systems intelligent information technologies heterogeneous data machine learning renewable energy |
| url | https://ieeexplore.ieee.org/document/8813086/ |
| work_keys_str_mv | AT ravilimukhamediev multicriteriaspatialdecisionmakingsupportsystemforrenewableenergydevelopmentinkazakhstan AT renatmustakayev multicriteriaspatialdecisionmakingsupportsystemforrenewableenergydevelopmentinkazakhstan AT kirillyakunin multicriteriaspatialdecisionmakingsupportsystemforrenewableenergydevelopmentinkazakhstan AT sophiakiseleva multicriteriaspatialdecisionmakingsupportsystemforrenewableenergydevelopmentinkazakhstan AT viktorgopejenko multicriteriaspatialdecisionmakingsupportsystemforrenewableenergydevelopmentinkazakhstan |