Shiyi Ma, Jun Wu, Zhihui Liu, T. Xu, Wei Ma, Xuezhi Wu, L. Jing
{"title":"Impact and Solution of PV Power Fluctuations on Operation of Hybrid AC/DC Microgrid","authors":"Shiyi Ma, Jun Wu, Zhihui Liu, T. Xu, Wei Ma, Xuezhi Wu, L. Jing","doi":"10.1109/CIEEC.2018.8745983","DOIUrl":null,"url":null,"abstract":"In the hybrid AC/DC microgrid, the random fluctuations of the PV output power will cause the voltage variation of microgrid bus. The power fluctuations have significant negative effects on the power quality and reliability of the hybrid AC/DC microgrid. A fast charging and discharging control of energy storage and PV power limited operation control based on the power fluctuation characteristic is proposed in this paper. The two controls cooperate so that the fluctuation of PV power can be effectively suppressed. First of all, the autoregressive moving average algorithm (ARIMA) is used to predict ultra-short term forecasting of PV power generation, and the limited power operation mode of PV is whether to enter is determined by the predicted results. Then, in the limited power operation mode, the power limit percentage is adjusted dynamically through the PI algorithm according to the size of PV power fluctuations. Finally, an adaptive Kalman filtering algorithm is proposed in this paper to optimize the control of charging and discharging of energy storage device. The filter parameters can be adjusted automatically through the state of charging (SOC) of energy storage device, ensuring the safe operation of the energy storage device. Simulation results show that the above algorithms can be effectively coordinated, significantly reduce the fluctuation of PV power, and make the hybrid AC/DC microgrid operating safer.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIEEC.2018.8745983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In the hybrid AC/DC microgrid, the random fluctuations of the PV output power will cause the voltage variation of microgrid bus. The power fluctuations have significant negative effects on the power quality and reliability of the hybrid AC/DC microgrid. A fast charging and discharging control of energy storage and PV power limited operation control based on the power fluctuation characteristic is proposed in this paper. The two controls cooperate so that the fluctuation of PV power can be effectively suppressed. First of all, the autoregressive moving average algorithm (ARIMA) is used to predict ultra-short term forecasting of PV power generation, and the limited power operation mode of PV is whether to enter is determined by the predicted results. Then, in the limited power operation mode, the power limit percentage is adjusted dynamically through the PI algorithm according to the size of PV power fluctuations. Finally, an adaptive Kalman filtering algorithm is proposed in this paper to optimize the control of charging and discharging of energy storage device. The filter parameters can be adjusted automatically through the state of charging (SOC) of energy storage device, ensuring the safe operation of the energy storage device. Simulation results show that the above algorithms can be effectively coordinated, significantly reduce the fluctuation of PV power, and make the hybrid AC/DC microgrid operating safer.