File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/TPWRS.2013.2293572
- Scopus: eid_2-s2.0-84903119969
- WOS: WOS:000338189600006
- Find via

Supplementary
- Citations:
- Appears in Collections:
Article: Adaptive Coordinated Voltage Control-Part II: Use of Learning for Rapid Response
| Title | Adaptive Coordinated Voltage Control-Part II: Use of Learning for Rapid Response |
|---|---|
| Authors | |
| Keywords | Adaptive control Coordinated voltage control Learning control Model predictive control Multi-objective optimization |
| Issue Date | 2014 |
| Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59 |
| Citation | IEEE Transactions on Power Systems, 2014, v. 29 n. 4, p. 1554-1561 How to Cite? |
| Abstract | This is the second part of a two-part paper on a new adaptive coordinated voltage control (ACVC) strategy. The overall basic scheme and the online control for prepared faults have been presented in Part I. In this paper, learning control is explored to accumulate knowledge, so that the online control performances can be improved for unknown emergencies. For unknown situations where no past experiences can be exploited, a learning scheme is used by which the control knowledge can be acquired gradually. The learnt knowledge goes into the database and is improved the next time a related situation happens. After full knowledge is acquired, the unknown fault becomes a prepared fault with prepared knowledge. With the learning scheme, control for any emergency can be realized in a rapid and effective response. The learning process is demonstrated by providing control for an unknown emergency in the New England 39-bus power system. The ACVC performance for a sequence of randomly generated fault and load event emergencies is presented at the end of this paper. |
| Persistent Identifier | http://hdl.handle.net/10722/217014 |
| ISSN | 2023 Impact Factor: 6.5 2023 SCImago Journal Rankings: 3.827 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ma, H | - |
| dc.contributor.author | Hill, DJ | - |
| dc.date.accessioned | 2015-09-18T05:46:03Z | - |
| dc.date.available | 2015-09-18T05:46:03Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.citation | IEEE Transactions on Power Systems, 2014, v. 29 n. 4, p. 1554-1561 | - |
| dc.identifier.issn | 0885-8950 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/217014 | - |
| dc.description.abstract | This is the second part of a two-part paper on a new adaptive coordinated voltage control (ACVC) strategy. The overall basic scheme and the online control for prepared faults have been presented in Part I. In this paper, learning control is explored to accumulate knowledge, so that the online control performances can be improved for unknown emergencies. For unknown situations where no past experiences can be exploited, a learning scheme is used by which the control knowledge can be acquired gradually. The learnt knowledge goes into the database and is improved the next time a related situation happens. After full knowledge is acquired, the unknown fault becomes a prepared fault with prepared knowledge. With the learning scheme, control for any emergency can be realized in a rapid and effective response. The learning process is demonstrated by providing control for an unknown emergency in the New England 39-bus power system. The ACVC performance for a sequence of randomly generated fault and load event emergencies is presented at the end of this paper. | - |
| dc.language | eng | - |
| dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=59 | - |
| dc.relation.ispartof | IEEE Transactions on Power Systems | - |
| dc.rights | IEEE Transactions on Power Systems. Copyright © Institute of Electrical and Electronics Engineers. | - |
| dc.subject | Adaptive control | - |
| dc.subject | Coordinated voltage control | - |
| dc.subject | Learning control | - |
| dc.subject | Model predictive control | - |
| dc.subject | Multi-objective optimization | - |
| dc.title | Adaptive Coordinated Voltage Control-Part II: Use of Learning for Rapid Response | - |
| dc.type | Article | - |
| dc.identifier.email | Ma, H: mahaomin@hku.hk | - |
| dc.identifier.email | Hill, DJ: dhill@eee.hku.hk | - |
| dc.identifier.authority | Hill, DJ=rp01669 | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1109/TPWRS.2013.2293572 | - |
| dc.identifier.scopus | eid_2-s2.0-84903119969 | - |
| dc.identifier.hkuros | 253894 | - |
| dc.identifier.hkuros | 253736 | - |
| dc.identifier.volume | 29 | - |
| dc.identifier.issue | 4 | - |
| dc.identifier.spage | 1554 | - |
| dc.identifier.epage | 1561 | - |
| dc.identifier.isi | WOS:000338189600006 | - |
| dc.publisher.place | United States | - |
| dc.identifier.issnl | 0885-8950 | - |
