Forecasting loads for microgrids
98 p.
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sg-ntu-dr.10356-580872023-07-04T15:38:08Z Forecasting loads for microgrids Soo, Fui Lan Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 98 p. In the operation of a microgrid, forecasting of load is an important task. A microgrid, is an integrated energy system comprises price-sensitive loads, energy storage and Distributed Energy Resources (DERs) which could supply power and heat. To operate such an integrated system, Microgrid Energy Management System (MG-EMS) is required to monitor and control these devices. Load forecasting which predicts the total customer load in a district plays an important role in the MG-EMS. Some MG-EMS's functions such as economic dispatch require load forecast with shorter forecast lead time, from a single minute to several dozen minutes and this is referred to as very short-term load forecasting (VSTLF). VSTLF has a significant impact on the efficient market operation, controlling and planning of microgrids. The accuracy of the forecast greatly depends on the algorithms used in prediction. Load forecasting algorithms which give accurate forecast values will result in economic savings as well as enhancing security of the system operation. With the 24-hour ahead load forecast values, Unit Commitment which determines the half-hourly (or quarter-hourly) on/off schedules of DERs and their power generation for the next 24 hours can be executed. Master of Science (Power Engineering) 2014-04-07T12:13:46Z 2014-04-07T12:13:46Z 2011 2011 Thesis http://hdl.handle.net/10356/58087 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Soo, Fui Lan Forecasting loads for microgrids |
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98 p. |
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Gooi Hoay Beng |
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Gooi Hoay Beng Soo, Fui Lan |
format |
Theses and Dissertations |
author |
Soo, Fui Lan |
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Soo, Fui Lan |
title |
Forecasting loads for microgrids |
title_short |
Forecasting loads for microgrids |
title_full |
Forecasting loads for microgrids |
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Forecasting loads for microgrids |
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Forecasting loads for microgrids |
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forecasting loads for microgrids |
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2014 |
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http://hdl.handle.net/10356/58087 |
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