Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration
Renewable energy (RE) sources are known to have high intermittency and are unreliable energy sources for power systems. Measures have been taken to improve reliability, such as incorporation of energy storage (ES) systems, and backup diesel engine (DE) generators. These measures require customised p...
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sg-ntu-dr.10356-1667872023-07-07T17:15:39Z Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration Yeo, Wen Hui Gooi Hoay Beng School of Electrical and Electronic Engineering Clean Energy Research Laboratory (CERL) EHBGOOI@ntu.edu.sg Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries Renewable energy (RE) sources are known to have high intermittency and are unreliable energy sources for power systems. Measures have been taken to improve reliability, such as incorporation of energy storage (ES) systems, and backup diesel engine (DE) generators. These measures require customised parameters for a specific microgrid (MG). The day-ahead scheduling and intraday real-time dispatch data for all parameters of a microgrid, which are photovoltaic (PV) generation data, state of charge of ES, charging and discharging power of ES, price of electricity, buying and selling power of ES and lastly, power generation of DE, are considered. Using real-time data measured from a microgrid in Clean Energy Research Lab (CERL), NTU, the trends of the parameters have been studied to compare the impact to the day-ahead scheduling data, which is used for constant improvements of MG parameters to ensure reliability and cost-effectiveness. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-15T01:37:54Z 2023-05-15T01:37:54Z 2023 Final Year Project (FYP) Yeo, W. H. (2023). Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166787 https://hdl.handle.net/10356/166787 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries Yeo, Wen Hui Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
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Renewable energy (RE) sources are known to have high intermittency and are unreliable energy sources for power systems. Measures have been taken to improve reliability, such as incorporation of energy storage (ES) systems, and backup diesel engine (DE) generators. These measures require customised parameters for a specific microgrid (MG). The day-ahead scheduling and intraday real-time dispatch data for all parameters of a microgrid, which are photovoltaic (PV) generation data, state of charge of ES, charging and discharging power of ES, price of electricity, buying and selling power of ES and lastly, power generation of DE, are considered.
Using real-time data measured from a microgrid in Clean Energy Research Lab (CERL), NTU, the trends of the parameters have been studied to compare the impact to the day-ahead scheduling data, which is used for constant improvements of MG parameters to ensure reliability and cost-effectiveness. |
author2 |
Gooi Hoay Beng |
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Gooi Hoay Beng Yeo, Wen Hui |
format |
Final Year Project |
author |
Yeo, Wen Hui |
author_sort |
Yeo, Wen Hui |
title |
Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
title_short |
Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
title_full |
Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
title_fullStr |
Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
title_full_unstemmed |
Multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
title_sort |
multi-time scale rolling optimal dispatch for microgrids with high renewable penetration |
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Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/166787 |
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1772828784577216512 |