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Symmetry
Volume 16
Issue 6
10.3390/sym16060679
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Open AccessArticle
by Dexu Zou SciProfilesScilitPreprints.orgGoogle Scholar Xinyu Sun SciProfilesScilitPreprints.orgGoogle Scholar Hao Quan SciProfilesScilitPreprints.orgGoogle Scholar Jianhua Yin SciProfilesScilitPreprints.orgGoogle Scholar Qingjun Peng SciProfilesScilitPreprints.orgGoogle Scholar Shan Wang SciProfilesScilitPreprints.orgGoogle Scholar Weiju Dai SciProfilesScilitPreprints.orgGoogle Scholar Zhihu Hong SciProfilesScilitPreprints.orgGoogle ScholarDexu Zou
Xinyu Sun
Hao Quan
,
Jianhua Yin
Qingjun Peng
Shan Wang
Weiju Dai
Zhihu Hong
1
School of Electrical Engineering, Chongqing University, Chongqing 400044, China
2
Electric Power Research Institute, China Southern Power Grid Yunnan Power Grid Co., Ltd., Kunming 650217, China
3
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
*
Author to whom correspondence should be addressed.
Symmetry 2024, 16(6), 679; https://doi.org/10.3390/sym16060679 (registeringDOI)
Submission received: 23 April 2024/Revised: 22 May 2024/Accepted: 30 May 2024/Published: 1 June 2024
(This article belongs to the Special Issue Symmetry/Asymmetry Studies in Modern Power Systems)
Abstract
The operational stability of a power transformer exerts an extremely important impact on the power symmetry, balance, and security of power systems. When the grid load fluctuates greatly, if the load factor of the transformer cannot be maintained within a reasonable range, it leads to increased instability in grid operation. Adjusting the transformer capacity based on load changes is of great significance. The existing control methods for on-load capacity-regulating (OLCR) transformers have low timeliness, and the daily switching frequency of the capacity-regulating switch is not controlled. To ensure the safe and stable operation of transformers, this paper proposes a control method for OLCR transformers based on load prediction and fuzzy control. Firstly, the operating principle of OLCR transformers is analyzed, and a multi-strategy enhanced dung beetle optimizer (MSDBO) combined with a CNN−LSTM model is proposed for load forecasting. On this basis, the daily switching frequency of the capacity-regulating transformer is introduced, and hesitant fuzzy control is used to select the optimal capacity-regulating strategy relying on three factors: loss, economy, and switching frequency. Finally, simulation models are constructed using the MATLAB/SIMULINK platform and simulation analysis is conducted to verify the effectiveness and superiority of the proposed control method. For the three scenarios in this paper, the method reduces daily power loss by 28.5% to 56.3% and daily operating costs by 25.4% to 50.8%. The method used in this paper can sacrifice 3.5% to 9.2% of the loss reduction capability in exchange for reducing the number of switch operations by 28.6% to 57.1%, significantly extending the lifespan of the switches and thereby increasing the operational lifespan of the transformer.
Keywords: on-load capacity-regulating transformer; power system symmetry; fuzzy control; load forecasting; CNN−LSTM
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MDPI and ACS Style
Zou, D.; Sun, X.; Quan, H.; Yin, J.; Peng, Q.; Wang, S.; Dai, W.; Hong, Z.Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control. Symmetry 2024, 16, 679.https://doi.org/10.3390/sym16060679
AMA Style
Zou D, Sun X, Quan H, Yin J, Peng Q, Wang S, Dai W, Hong Z.Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control. Symmetry. 2024; 16(6):679.https://doi.org/10.3390/sym16060679
Chicago/Turabian Style
Zou, Dexu, Xinyu Sun, Hao Quan, Jianhua Yin, Qingjun Peng, Shan Wang, Weiju Dai, and Zhihu Hong.2024. "Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control" Symmetry 16, no. 6: 679.https://doi.org/10.3390/sym16060679
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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MDPI and ACS Style
Zou, D.; Sun, X.; Quan, H.; Yin, J.; Peng, Q.; Wang, S.; Dai, W.; Hong, Z.Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control. Symmetry 2024, 16, 679.https://doi.org/10.3390/sym16060679
AMA Style
Zou D, Sun X, Quan H, Yin J, Peng Q, Wang S, Dai W, Hong Z.Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control. Symmetry. 2024; 16(6):679.https://doi.org/10.3390/sym16060679
Chicago/Turabian Style
Zou, Dexu, Xinyu Sun, Hao Quan, Jianhua Yin, Qingjun Peng, Shan Wang, Weiju Dai, and Zhihu Hong.2024. "Power Transformer On-Load Capacity-Regulating Control and Optimization Based on Load Forecasting and Hesitant Fuzzy Control" Symmetry 16, no. 6: 679.https://doi.org/10.3390/sym16060679
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Symmetry,EISSN 2073-8994,Published by MDPI
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