Abstract
Electrical distribution networks worldwide are facing frequent capacity challenges due to the widespread roll out of various distributed energy resources (DERs). A number of demand response (DR) mechanisms have been developed in order to circumvent the problems and enhance the flexibility of the distribution network. While the existing centralised control system remains its crucial role for reliable and secure grid operation, distributed intelligence is a complement technology with a focus on dividing the control task into a number of simpler problems and solve them with minimum exchange of information. Based on the recent developments of distributed intelligence, this paper investigates a set of different congestion management approaches to effectively regulate the overloading issue of transformers or conductors. The study is validated with simulations for representative Dutch low-voltage (LV) networks.
Original language | English |
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Title of host publication | 2017 IEEE Manchester PowerTech, Powertech 2017 |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Number of pages | 6 |
ISBN (Electronic) | 9781509042371 |
DOIs | |
Publication status | Published - 13 Jul 2017 |
Event | 2017 IEEE PowerTech Manchester - University of Manchester, Manchester, United Kingdom Duration: 18 Jun 2017 → 22 Jun 2017 Conference number: 12 http://ieee-powertech.org/ |
Conference
Conference | 2017 IEEE PowerTech Manchester |
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Abbreviated title | PowerTech 2017 |
Country/Territory | United Kingdom |
City | Manchester |
Period | 18/06/17 → 22/06/17 |
Other | Towards and Beyond Sustainable Energy Systems |
Internet address |
Keywords
- congestion management
- demand flexibility
- Demand response
- distributed energy resources