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Research Article | Open Access

Application of nine point logic control and predictive pid control algorithms in smart grid decision-making

Department of Urban Rail Transit and Information Engineering, Anhui Communications Vocational & Technical College, Hefei, Anhui 230051, China
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Abstract

The smart grid operation and decision-making system has the characteristics of smart power detection, data cloud storage, and information fusion. The disadvantage is that the difficulty of model estimation is high, significant fluctuations in energy storage and transmission, algorithm update iteration delay, and low accuracy of data fusion technology. First, models and algorithms for smart grids, improve the multiple domain value delay problem of output stability. Second, the nine-point logic control strategy is based on the partition of deviation and deviation variation based on pan Boolean operations, effectively solving the frequency and band amplitude issues of power grid transmission load fluctuations. When the integral variable or input signals change, compared with traditional PID control, it is concluded that, just adjusting according to the nine-point logic control strategy, can obtain ideal control and output results. Finally, establishing a simulation model, the results indicate that its control curve performs well in model matching, satisfactory operation in case of model mismatch, and ensures that the fluctuation amplitude and error accuracy meet the requirements. The control strategy has the characteristics of a fast output response, high stability and robustness, and a small overshoot for changing power grid models.

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Journal of Highway and Transportation Research and Development (English Edition)
Pages 8-15

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Cite this article:
Ou Z. Application of nine point logic control and predictive pid control algorithms in smart grid decision-making. Journal of Highway and Transportation Research and Development (English Edition), 2024, 18(4): 8-15. https://doi.org/10.26599/HTRD.2024.9480037

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Received: 25 October 2023
Revised: 09 January 2024
Accepted: 03 March 2024
Published: 31 December 2024
© The Author(s) 2024.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).