Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152622
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dc.contributor.authorLiang, Elroy Bo Junen_US
dc.date.accessioned2021-09-03T00:36:48Z-
dc.date.available2021-09-03T00:36:48Z-
dc.date.issued2021-
dc.identifier.citationLiang, E. B. J. (2021). Short-term load forecasting in Singapore's energy market. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/152622en_US
dc.identifier.urihttps://hdl.handle.net/10356/152622-
dc.description.abstractThis paper presents a time series analysis for short-term electricity demand forecasting in Singapore. In the liberalised energy market, the Energy Market Company facilitates the wholesale market by providing market participants with price and energy demand forecasts at regular intervals. These forecasts help generators plan the amount of energy to produce ahead of the actual time period and ensure that the supply and demand of the grid are balanced. In this paper, deep learning models are implemented to improve the demand forecasts provided by the Energy Market Company. Particularly, 4 variations of Long Short-Term Memory models are implemented on Singapore’s historical load data from 2017 to 2020. The performances of these models are compared with the provided benchmark forecast.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleShort-term load forecasting in Singapore's energy marketen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorBo Anen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.supervisoremailboan@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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