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- Publisher Website: 10.1016/j.ijepes.2021.107384
- Scopus: eid_2-s2.0-85111070302
- WOS: WOS:000705235800025
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Article: An online approach for partial topology recovery in LMP markets
Title | An online approach for partial topology recovery in LMP markets |
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Authors | |
Keywords | Laplacian matrix Locational marginal price (LMP) Online algorithm Semidefinite programming (SDP) Sparse recovery |
Issue Date | 2022 |
Citation | International Journal of Electrical Power and Energy Systems, 2022, v. 134, article no. 107384 How to Cite? |
Abstract | For electricity market participants, proper information on the current grid topology is helpful for applications such as locational marginal price (LMP)/congestion forecasting, valuation of electricity derivatives, and operation of generation/distribution assets. However, in many markets, the publication of the grid topology is usually untimely or incomplete due to confidentiality concerns. To solve this problem, this paper proposes an online approach for recovering the latest complete grid topology from timely LMP data and incomplete partial topology information. Under the assumption that the grid topology is sparse, the recovery problem is formulated as a semidefinite programming (SDP) problem. The online alternating direction method (OADM) is applied to obtain a recursive expression for the optimal solution. Case studies on the IEEE 30-bus and 118-bus systems demonstrate the effectiveness and efficiency of the proposed approach. |
Persistent Identifier | http://hdl.handle.net/10722/308875 |
ISSN | 2023 Impact Factor: 5.0 2023 SCImago Journal Rankings: 1.711 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Gu, Yuxuan | - |
dc.contributor.author | Zheng, Kedi | - |
dc.contributor.author | Wang, Yi | - |
dc.contributor.author | Zhang, Xuan | - |
dc.contributor.author | Chen, Qixin | - |
dc.date.accessioned | 2021-12-08T07:50:19Z | - |
dc.date.available | 2021-12-08T07:50:19Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | International Journal of Electrical Power and Energy Systems, 2022, v. 134, article no. 107384 | - |
dc.identifier.issn | 0142-0615 | - |
dc.identifier.uri | http://hdl.handle.net/10722/308875 | - |
dc.description.abstract | For electricity market participants, proper information on the current grid topology is helpful for applications such as locational marginal price (LMP)/congestion forecasting, valuation of electricity derivatives, and operation of generation/distribution assets. However, in many markets, the publication of the grid topology is usually untimely or incomplete due to confidentiality concerns. To solve this problem, this paper proposes an online approach for recovering the latest complete grid topology from timely LMP data and incomplete partial topology information. Under the assumption that the grid topology is sparse, the recovery problem is formulated as a semidefinite programming (SDP) problem. The online alternating direction method (OADM) is applied to obtain a recursive expression for the optimal solution. Case studies on the IEEE 30-bus and 118-bus systems demonstrate the effectiveness and efficiency of the proposed approach. | - |
dc.language | eng | - |
dc.relation.ispartof | International Journal of Electrical Power and Energy Systems | - |
dc.subject | Laplacian matrix | - |
dc.subject | Locational marginal price (LMP) | - |
dc.subject | Online algorithm | - |
dc.subject | Semidefinite programming (SDP) | - |
dc.subject | Sparse recovery | - |
dc.title | An online approach for partial topology recovery in LMP markets | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.ijepes.2021.107384 | - |
dc.identifier.scopus | eid_2-s2.0-85111070302 | - |
dc.identifier.volume | 134 | - |
dc.identifier.spage | article no. 107384 | - |
dc.identifier.epage | article no. 107384 | - |
dc.identifier.isi | WOS:000705235800025 | - |