Evaluation of renewable energy prediction information for cyber-physical power system

Jingdi Zhang; Tiance Zhang; Gengyin Li; Ming Zhou; Changyu Deng; Yapeng Zhang; Zhibing Hu

doi:10.1117/12.3004277

25 September 2023 Evaluation of renewable energy prediction information for cyber-physical power system

Jingdi Zhang, Tiance Zhang, Gengyin Li, Ming Zhou, Changyu Deng, Yapeng Zhang, Zhibing Hu

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 1278809 (2023) https://doi.org/10.1117/12.3004277
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Today's Internet technology is changing rapidly, the value of information in power systems is increasing. In the renewable energy-rich power grid, relatively accurate renewable energy prediction can reduce uncertainty caused by the random output of renewable energy, thus effectively improve the efficiency of renewable energy use, but also for power companies and power grid companies to provide a reference for economic benefits. In this paper, the value of photovoltaic (PV) predictive information to power systems is evaluated using an innovative evaluation system including Shannon entropy and non-noise ratio. Finally, taking IEEE 30-bus system as an example, the design and implementation of this paper are verified.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingdi Zhang, Tiance Zhang, Gengyin Li, Ming Zhou, Changyu Deng, Yapeng Zhang, and Zhibing Hu "Evaluation of renewable energy prediction information for cyber-physical power system", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 1278809 (25 September 2023); https://doi.org/10.1117/12.3004277

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