Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152622
Title: Short-term load forecasting in Singapore's energy market
Authors: Liang, Elroy Bo Jun
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Liang, 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/10356/152622
Abstract: This 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.
URI: https://hdl.handle.net/10356/152622
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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