Research on the impact analysis and control strategy of load fluctuation in distribution banding operation based on segmented linearization method
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Mar 19, 2025
About this article
Published Online: Mar 19, 2025
Received: Nov 17, 2024
Accepted: Feb 21, 2025
DOI: https://doi.org/10.2478/amns-2025-0443
Keywords
© 2025 Ying Xu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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ANOVA analyzes the p values of different influencing factors
| Influencing factor | Prof>F |
|---|---|
| Maximum temperature | 1.63087.5*1023 |
| Minimum temperature | 2.59187*1028 |
| Mean temperature | 9.00492*1029 |
| Relative humidity (average) | 0.1589 |
| Rainfall amount | 0.4738 |
Combined results of different load volatility models
| N | Fitting result | R2 | Remark |
|---|---|---|---|
| 1 | Distribution load=0.341*WT-3.164 | 0.9687 | High temperature fitting: general |
| (WT<26.4°C) | |||
| Distribution load=1.028*WT-21.508 | 0.8625 | ||
| (WT>26.4°C) | |||
| 2 | Distribution load=0.092*AH-1.572 | 0.9742 | High temperature fitting: general |
| (AH<86kJ/kg) | |||
| Distribution load=0.238*AH-12.278 | 0.8635 | ||
| (AH>86kJ/kg) | |||
| 3 | Distribution load=0.339*DT+0.0644*RH-8.89 | 0.9764 | The fitting is better |
| (WT<26.4°C) | |||
| Distribution load=0.842*DT+0.173*RH-33.346 | 0.9534 | ||
| (WT>26.4°C) | |||
| 4 | Distribution load=0.325*DT+0.328*WT-4.295 | 0.9795 | The fitting is better |
| (WT<26.4°C) | |||
| Distribution load=0.095*DT+0.922*WT-22.371 | 0.9186 | ||
| (WT>26.4°C) |
ANOVA analyzes the highest temperature - load
| SS | df | MS | F | Prof>F | |
|---|---|---|---|---|---|
| Regression analysis | 4.0915*108 | 187 | 2223209.7 | 4.85 | 1.63087.5*10-29 |
| Residual error | 8.61294*107 | 183 | 475859.6 | ||
| Total | 4.967*108 | 372 |