Evaluation and analysis of distributed photovoltaic carrying capacity of power grid based on big data technology

Haiying Peng; Shuquan Yang; Fei Gao; Tenglong Li; Xuegao Wang; Wei Li

doi:10.1117/12.2647701

23 August 2022 Evaluation and analysis of distributed photovoltaic carrying capacity of power grid based on big data technology

Haiying Peng, Shuquan Yang, Fei Gao, Tenglong Li, Xuegao Wang, Wei Li

Author Affiliations +

Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 123301F (2022) https://doi.org/10.1117/12.2647701
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China

Abstract

Based on big data technology, sort out the operation and parameter data of distributed photovoltaic in each district and county, and complete the analysis of influencing factors of distributed photovoltaic bearing capacity and thermal stability calculation and analysis in combination with the development background and current situation of regional distributed photovoltaic. Build the calculation algorithm and data model of distributed photovoltaic carrying capacity, mine the acceptable distributed photovoltaic capacity of each district and county, form the calculation boundary conditions of each district and county, and connect to the power grid orderly and reasonably. It ensures the safe and stable operation of the power grid and the full consumption of distributed photovoltaic, which is of great significance to guide all walks of life to actively participate in the orderly grid connection of distributed photovoltaic.

Citation Download Citation

Haiying Peng, Shuquan Yang, Fei Gao, Tenglong Li, Xuegao Wang, and Wei Li "Evaluation and analysis of distributed photovoltaic carrying capacity of power grid based on big data technology", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 123301F (23 August 2022); https://doi.org/10.1117/12.2647701

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