File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ISGTEurope.2017.8260163
- Scopus: eid_2-s2.0-85046279852
- WOS: WOS:000428016500072
Supplementary
- Citations:
- Appears in Collections:
Conference Paper: Risk-averse joint capacity evaluation of pv generation and electric vehicle charging stations in distribution networks
Title | Risk-averse joint capacity evaluation of pv generation and electric vehicle charging stations in distribution networks |
---|---|
Authors | |
Keywords | PV generation WC-CVaR EVs Distributionally robust chance constrained programming Capacity evaluation |
Issue Date | 2017 |
Citation | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings, 2017 How to Cite? |
Abstract | © 2017 IEEE. Increasing penetration of distribution generation (DG) and electric vehicles (EVs) calls for an effective way to estimate the achievable capacity connected to the distribution systems, but the exogenous uncertainties of DG outputs and EV charging loads make it challengeable. This study provides a joint capacity evaluation method with a risk threshold setting function for photovoltaic (PV) generation and EV charging stations (EVCSs). The method is mathematically formulated as a distributionally robust joint chance constrained programming model. And the worst-case conditional value at risk (WC-CVaR) approximation and an iterative algorithm based on semidefinite program (SDP) are used to solve the model. Finally, the method test is carried out numerically on IEEE 33-bus radial distribution system. |
Persistent Identifier | http://hdl.handle.net/10722/296172 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, Huimiao | - |
dc.contributor.author | Hu, Zechun | - |
dc.contributor.author | Jia, Yinghao | - |
dc.contributor.author | Shen, Zuo Jun Max | - |
dc.date.accessioned | 2021-02-11T04:52:59Z | - |
dc.date.available | 2021-02-11T04:52:59Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings, 2017 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296172 | - |
dc.description.abstract | © 2017 IEEE. Increasing penetration of distribution generation (DG) and electric vehicles (EVs) calls for an effective way to estimate the achievable capacity connected to the distribution systems, but the exogenous uncertainties of DG outputs and EV charging loads make it challengeable. This study provides a joint capacity evaluation method with a risk threshold setting function for photovoltaic (PV) generation and EV charging stations (EVCSs). The method is mathematically formulated as a distributionally robust joint chance constrained programming model. And the worst-case conditional value at risk (WC-CVaR) approximation and an iterative algorithm based on semidefinite program (SDP) are used to solve the model. Finally, the method test is carried out numerically on IEEE 33-bus radial distribution system. | - |
dc.language | eng | - |
dc.relation.ispartof | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings | - |
dc.subject | PV generation | - |
dc.subject | WC-CVaR | - |
dc.subject | EVs | - |
dc.subject | Distributionally robust chance constrained programming | - |
dc.subject | Capacity evaluation | - |
dc.title | Risk-averse joint capacity evaluation of pv generation and electric vehicle charging stations in distribution networks | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ISGTEurope.2017.8260163 | - |
dc.identifier.scopus | eid_2-s2.0-85046279852 | - |
dc.identifier.isi | WOS:000428016500072 | - |