Research on power grid planning based on complex adaptive system theory
Most of the traditional power grid planning methods take the system point of view as the starting point, and use the top-down method to design the planning model. This not only limits the discovery of new rules, but also the planning results are relatively simple and do not adapt to the flexible pow...
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Published in | Proceedings of SPIE, the international society for optical engineering Vol. 13641; pp. 136410T - 136410T-13 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
SPIE
22.05.2025
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Online Access | Get full text |
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Summary: | Most of the traditional power grid planning methods take the system point of view as the starting point, and use the top-down method to design the planning model. This not only limits the discovery of new rules, but also the planning results are relatively simple and do not adapt to the flexible power system environment. Therefore, a new idea of power grid planning based on complex adaptive system theory is proposed. Firstly, the basic concepts and characteristics of complex adaptive system theory are expounded. Secondly, the complex adaptability characteristics of the power grid are analyzed. Then, combined with the characteristics of power grid planning and modeling in a subject-object-based manner, a power grid planning model based on the theoretical framework of complex adaptive system is established, and the objective function is determined. Finally, the example of 18-node system is calculated on Swarm platform, and the key technical indicators of power system planning are studied by using complex adaptive system theory. The dynamic planning results are obtained, the emergence and development process of power grid planning is revealed, and the effectiveness of this method for power grid planning is verified. |
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Bibliography: | Conference Date: 2025-02-28|2025-03-02 Conference Location: Guangzhou, China |
ISBN: | 9781510691933 1510691936 |
ISSN: | 0277-786X |
DOI: | 10.1117/12.3067939 |