An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals
Renewable energy is fast becoming a mainstay in today’s energy scenario. Some of the main sources of renewable engery are wind, solar in addition to waves,tides,etc. These renewable energy-based production, is however inefficient from a practical as well as financial standpoint. The main reason...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Online Access: | https://hdl.handle.net/10356/88844 http://hdl.handle.net/10220/45996 |
| _version_ | 1811687519619645440 |
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| author | Nguyen, Trong Trung Anh |
| author2 | Sundaram Suresh |
| author_facet | Sundaram Suresh Nguyen, Trong Trung Anh |
| author_sort | Nguyen, Trong Trung Anh |
| collection | NTU |
| description | Renewable energy is fast becoming a mainstay in today’s energy
scenario. Some of the main sources of renewable engery are wind,
solar in addition to waves,tides,etc. These renewable energy-based
production, is however inefficient from a practical as well as financial
standpoint. The main reason is being the inability to forecast the exact
energy that could be generated. This thesis develops a forecasting
approach using interval type-2 fuzzy inferences system to address
prediction intervals. The system has been adapted employing a
gradient descent learning algorithm and an extended kalman filtering
method. Meta-cognition is integrated into the system to improve the
learning ability and prevent over-fitting. The proposed systems are
used in two real-world renewable energy problems: wind and wave
prediction. The wave measurement data were collected from
directional waveriders deployed offshore Singapore. The experiments
are then conducted on the wave energy characteristics and wind speed
forecasting problems. |
| first_indexed | 2024-10-01T05:17:36Z |
| format | Thesis |
| id | ntu-10356/88844 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:17:36Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/888442020-11-01T04:53:46Z An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals Nguyen, Trong Trung Anh Sundaram Suresh Interdisciplinary Graduate School (IGS) Energy Research Institute @NTU DRNTU::Engineering::Materials Renewable energy is fast becoming a mainstay in today’s energy scenario. Some of the main sources of renewable engery are wind, solar in addition to waves,tides,etc. These renewable energy-based production, is however inefficient from a practical as well as financial standpoint. The main reason is being the inability to forecast the exact energy that could be generated. This thesis develops a forecasting approach using interval type-2 fuzzy inferences system to address prediction intervals. The system has been adapted employing a gradient descent learning algorithm and an extended kalman filtering method. Meta-cognition is integrated into the system to improve the learning ability and prevent over-fitting. The proposed systems are used in two real-world renewable energy problems: wind and wave prediction. The wave measurement data were collected from directional waveriders deployed offshore Singapore. The experiments are then conducted on the wave energy characteristics and wind speed forecasting problems. Doctor of Philosophy 2018-09-13T06:19:05Z 2019-12-06T17:12:07Z 2018-09-13T06:19:05Z 2019-12-06T17:12:07Z 2018 Thesis Nguyen, T. T. A. (2018). An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/88844 http://hdl.handle.net/10220/45996 10.32657/10220/45996 en 148 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Materials Nguyen, Trong Trung Anh An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title | An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title_full | An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title_fullStr | An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title_full_unstemmed | An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title_short | An evolving interval type-2 fuzzy inference system for renewable energy prediction intervals |
| title_sort | evolving interval type 2 fuzzy inference system for renewable energy prediction intervals |
| topic | DRNTU::Engineering::Materials |
| url | https://hdl.handle.net/10356/88844 http://hdl.handle.net/10220/45996 |
| work_keys_str_mv | AT nguyentrongtrunganh anevolvingintervaltype2fuzzyinferencesystemforrenewableenergypredictionintervals AT nguyentrongtrunganh evolvingintervaltype2fuzzyinferencesystemforrenewableenergypredictionintervals |