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- Publisher Website: 10.1109/TSG.2018.2879226
- Scopus: eid_2-s2.0-85055864533
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Article: GPU-Based Enumeration Model Predictive Control of Pumped Storage to Enhance Operational Flexibility
Title | GPU-Based Enumeration Model Predictive Control of Pumped Storage to Enhance Operational Flexibility |
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Authors | |
Keywords | Switches Generators Automatic generation control Frequency control Graphics processing units |
Issue Date | 2019 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411 |
Citation | IEEE Transactions on Smart Grid, 2019, v. 10 n. 5, p. 5223-5233 How to Cite? |
Abstract | With the integration of more renewable energy, operational flexibility becomes a bottleneck for power system operation. Pumped storage units can enhance their operational flexibility by switching between different operation modes. They have limited capacity for adjustment when operated as generators and are non-adjustable when operated in the pump mode. However, the power ramps generated during the switching of operation modes are valuable for regulating the frequency and increasing the operational flexibility. In order to achieve sufficient performance, it is essential to determine the optimal switching time for the pumped storage units. However, there is no standard method to obtain the optimal switching time due to the complexities and non-linear characteristics of such a problem. In this paper, an enumeration based model predictive control (MPC) strategy is proposed to determine the optimal switching time of a pumped storage unit to enhance its operational flexibility and facilitate frequency regulation. Furthermore, a graphics processing unit accelerated computing method is proposed to solve the problem effectively and to make the MPC controller suitable for practical applications. |
Persistent Identifier | http://hdl.handle.net/10722/278159 |
ISSN | 2023 Impact Factor: 8.6 2023 SCImago Journal Rankings: 4.863 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liang, L | - |
dc.contributor.author | Hou, Y | - |
dc.contributor.author | Hill, DJ | - |
dc.date.accessioned | 2019-10-04T08:08:37Z | - |
dc.date.available | 2019-10-04T08:08:37Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | IEEE Transactions on Smart Grid, 2019, v. 10 n. 5, p. 5223-5233 | - |
dc.identifier.issn | 1949-3053 | - |
dc.identifier.uri | http://hdl.handle.net/10722/278159 | - |
dc.description.abstract | With the integration of more renewable energy, operational flexibility becomes a bottleneck for power system operation. Pumped storage units can enhance their operational flexibility by switching between different operation modes. They have limited capacity for adjustment when operated as generators and are non-adjustable when operated in the pump mode. However, the power ramps generated during the switching of operation modes are valuable for regulating the frequency and increasing the operational flexibility. In order to achieve sufficient performance, it is essential to determine the optimal switching time for the pumped storage units. However, there is no standard method to obtain the optimal switching time due to the complexities and non-linear characteristics of such a problem. In this paper, an enumeration based model predictive control (MPC) strategy is proposed to determine the optimal switching time of a pumped storage unit to enhance its operational flexibility and facilitate frequency regulation. Furthermore, a graphics processing unit accelerated computing method is proposed to solve the problem effectively and to make the MPC controller suitable for practical applications. | - |
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=5165411 | - |
dc.relation.ispartof | IEEE Transactions on Smart Grid | - |
dc.rights | IEEE Transactions on Smart Grid. Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Switches | - |
dc.subject | Generators | - |
dc.subject | Automatic generation control | - |
dc.subject | Frequency control | - |
dc.subject | Graphics processing units | - |
dc.title | GPU-Based Enumeration Model Predictive Control of Pumped Storage to Enhance Operational Flexibility | - |
dc.type | Article | - |
dc.identifier.email | Hou, Y: yhhou@hku.hk | - |
dc.identifier.email | Hill, DJ: dhill@eee.hku.hk | - |
dc.identifier.authority | Hou, Y=rp00069 | - |
dc.identifier.authority | Hill, DJ=rp01669 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TSG.2018.2879226 | - |
dc.identifier.scopus | eid_2-s2.0-85055864533 | - |
dc.identifier.hkuros | 306599 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 5223 | - |
dc.identifier.epage | 5233 | - |
dc.identifier.isi | WOS:000482623500047 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1949-3053 | - |