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Research on Short-Term Load Forecasting of Distribution Stations Based on the Clustering Improvement Fuzzy Time Series Algorithm
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作者 jipeng gu Weijie Zhang +5 位作者 Youbing Zhang Binjie Wang Wei Lou Mingkang Ye Linhai Wang Tao Liu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第9期2221-2236,共16页
An improved fuzzy time series algorithmbased on clustering is designed in this paper.The algorithm is successfully applied to short-term load forecasting in the distribution stations.Firstly,the K-means clustering met... An improved fuzzy time series algorithmbased on clustering is designed in this paper.The algorithm is successfully applied to short-term load forecasting in the distribution stations.Firstly,the K-means clustering method is used to cluster the data,and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division.On this basis,the data is fuzzed to form a fuzzy time series.Secondly,a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load,which is used to predict the short-term trend change of load in the distribution stations.Matlab/Simulink simulation results show that the load forecasting errors of the typical fuzzy time series on the time scale of one day and one week are[−50,20]and[−50,30],while the load forecasting errors of the improved fuzzy time series on the time scale of one day and one week are[−20,15]and[−20,25].It shows that the fuzzy time series algorithm improved by clustering improves the prediction accuracy and can effectively predict the short-term load trend of distribution stations. 展开更多
关键词 Short-term load forecasting fuzzy time series K-means clustering distribution stations
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Fuzzy Droop Control for SOC Balance and Stability Analysis of DC Microgrid with Distributed Energy Storage Systems
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作者 jipeng gu Xiaodong Yang +4 位作者 Youbing Zhang Luyao Xie Licheng Wang Wenwei Zhou Xiaohui Ge 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2024年第4期1203-1216,共14页
The unbalanced state of charge(SOC)of distributed energy storage systems(DESSs)in autonomous DC microgrid causes energy storage units(ESUs)to terminate operation due to overcharge or overdischarge,which severely affec... The unbalanced state of charge(SOC)of distributed energy storage systems(DESSs)in autonomous DC microgrid causes energy storage units(ESUs)to terminate operation due to overcharge or overdischarge,which severely affects the power quality.In this paper,a fuzzy droop control for SOC balance and stability analysis of DC microgrid with DESSs is proposed to achieve SOC balance in ESUs while maintaining a stable DC bus voltage.First,the charge and discharge modes of ESUs are determined based on the power supply requirements of the DC microgrid.One-dimensional fuzzy logic is then applied to establish the relationship between SOC and the droop coefficient R,in the aforementioned two modes.In addition,when integrated with voltage-current double closed-loop control,SOC balance in different ESUs is realized.To improve the balance speed and precision,an exponential acceleration factor is added to the input variable of the fuzzy controller.Finally,based on the average model of converter,the system-level stability of microgrid is analyzed.MATLAB/Simulink simulation results verify the effectiveness and rationality of the proposed method. 展开更多
关键词 DC microgrid distributed energy storage system fuzzy droop control state of charge(SOC)balance STABILITYANALYSIS
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