Application of nine point logic control and predictive pid control algorithms in smart grid decision-making
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 iterati...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2024-12-01
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| Series: | Journal of Highway and Transportation Research and Development |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/HTRD.2024.9480037 |
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| Summary: | 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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| ISSN: | 2095-6215 |