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<p>This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible resources and their aggregation technology. Utilizing network crawler technology within a knowledge graph framework, the research data pertinent to demand-side flexible resources and aggregation technology are extracted. These data undergo a meticulous cleaning process before being stored, culminating in the development of a knowledge graph tailored to the imaging and technology of demand-side flexible resources. The findings reveal a response rate of 7.25% ± 1.15%, with an uncertainty interval of 2.33%. Variations in air-conditioning load states appear to exert minimal impact on the response time lag. Following the issuance of a response signal, all systems can rapidly initiate appropriate response actions, demonstrating an uncertainty interval of approximately 52s±11s and 22s. The duration of the responses averages around 75s±11s, with an uncertainty interval of about 30s. This study fulfills the power system criteria for standards of demand-side flexible resources and augments the competitiveness of China’s power market.</p>
</abstract>

This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible resources and their aggregation technology. Utilizing network crawler technology within a knowledge graph framework, the research data pertinent to demand-side flexible resources and aggregation technology are extracted. These data undergo a meticulous cleaning process before being stored, culminating in the development of a knowledge graph tailored to the imaging and technology of demand-side flexible resources. The findings reveal a response rate of 7.25% ± 1.15%, with an uncertainty interval of 2.33%. Variations in air-conditioning load states appear to exert minimal impact on the response time lag. Following the issuance of a response signal, all systems can rapidly initiate appropriate response actions, demonstrating an uncertainty interval of approximately 52s±11s and 22s. The duration of the responses averages around 75s±11s, with an uncertainty interval of about 30s. This study fulfills the power system criteria for standards of demand-side flexible resources and augments the competitiveness of China’s power market.

Research on the Application of Knowledge Graph in Demand-Side Flexible Resource Profiling and Aggregation Techniques

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper commences by assessing the current landscape of power system development, focusing on the theory, principles, and structures of demand-side flexible...

Research on the Application of Knowledge Graph in Demand-Side Flexible Resource Profiling and Aggregation Techniques

Data publikacji: 03 cze 2024

Zakres stron: -

Otrzymano: 29 lut 2024

Przyjęty: 04 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1331

Słowa kluczowe
Demand side, Flexible resources, Aggregation techniques, Knowledge graphs

© 2024 Chao Yang, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Application of Knowledge Graph in Demand-Side Flexible Resource Profiling and Aggregation Techniques

Data publikacji: 03 cze 2024

Zakres stron: -

Otrzymano: 29 lut 2024

Przyjęty: 04 maj 2024

DOI: https://doi.org/10.2478/amns-2024-1331

Słowa kluczoweDemand side, Flexible resources, Aggregation techniques, Knowledge graphs

© 2024 Chao Yang, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Demand side, Flexible resources, Aggregation techniques, Knowledge graphs