Prospective risk scenario set construction and patternized response strategy for AC/DC distribution system
The increasingly complex architecture of distribution networks and the expanding presence of new types of source-load resources have introduced numerous operational risks and challenges to distribution systems. Problems such as voltage violations and branch overloads occur frequently， severely impac...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2025-04-01
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| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=d6bf059b-2449-40d6-ad63-830b3fe6bd97 |
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| Summary: | The increasingly complex architecture of distribution networks and the expanding presence of new types of source-load resources have introduced numerous operational risks and challenges to distribution systems. Problems such as voltage violations and branch overloads occur frequently， severely impacting the security and reliability of the distribution systems. Therefore， enhancing the risk assessment and rapid risk response capabilities of the distribution systems is urgently needed. To enable rapid risk response in AC/DC distribution systems， a method for constructing a prospective risk scenario set and a modeling-based response strategy is proposed. First， a risk assessment framework for AC/DC distribution system operations is developed based on uncertain power flow calculation results， identifying potential risk elements in the systems. A method for constructing a prospective risk scenario set is proposed， taking into account the occurrence probability and impact of risk scenarios. Next， a method for generating a repository of response strategies for prospective risk scenarios is introduced， focusing on the key risk elements in the system’s prospective risk scenarios. By incorporating immune risk theory， a modeling-based response strategy for control signal generation is proposed， utilizing fuzzy evaluation to assess the overall operational state of distribution systems. Finally， a method for generating modeling-based response strategies based on the similarity of risk scenarios is presented. Case studies are conducted to validate the effectiveness of the proposed modeling-based response method. |
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| ISSN: | 1007-1881 |