A typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations
Traditional clustering methods based on source-load information struggle to accurately describe the time-sequenced operational characteristics of renewable energy power systems. To address this， a typical scenario generation method for renewable energy power systems based on time-sequenced operation...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2025-05-01
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| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=3add38f0-48f3-4248-ac33-f4ede11cedad |
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| Summary: | Traditional clustering methods based on source-load information struggle to accurately describe the time-sequenced operational characteristics of renewable energy power systems. To address this， a typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations is proposed， considering both the AC power flow distribution and startup-shutoff strategies for units. Firstly， a unit combination model that incorporates AC power flow constraints is constructed， and a two-stage solution strategy based on second-order cone relaxation is adopted to perform 8，760-hour time-sequenced simulations in the multi-period optimal power flow model. Secondly， based on data characteristics such as renewable energy output levels， line congestion conditions， and unit startup-shutoff from the time-sequenced simulation results， an improved K-means algorithm is employed to extract typical scenarios. Finally， the validity of the proposed method is verified through a case study， providing a reference for renewable energy power system planning and scheduling. |
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| ISSN: | 1007-1881 |