Pub Date : 2012-11-26DOI: 10.12720/IJOEE.1.4.188-193
Y. Alharbi, A. Yunus, A. A. Siada
Variable speed wind turbine generators installation has been significantly increased worldwide in the last few years. Voltage sag at the grid side may call for the disconnection of the wind turbine from the grid as under such faults it may not comply with the recent developed grid codes for wind energy conversion systems (WECS). In this paper, a Unified Power Flow Controller (UPFC) is applied to improve the low voltage ride through (LVRT) capability of doubly fed induction generator (DFIG)-based WECS during voltage sag at the grid side. Simulation is carried out using MATLAB/Simulink software. Results show that UPFC can significantly improve the LVRT capability of DFIG-based WECS and hence maintaining wind turbine connection to the grid during certain levels of voltage sag at the grid side.
{"title":"Application of UPFC to improve the LVRT capability of wind turbine generator","authors":"Y. Alharbi, A. Yunus, A. A. Siada","doi":"10.12720/IJOEE.1.4.188-193","DOIUrl":"https://doi.org/10.12720/IJOEE.1.4.188-193","url":null,"abstract":"Variable speed wind turbine generators installation has been significantly increased worldwide in the last few years. Voltage sag at the grid side may call for the disconnection of the wind turbine from the grid as under such faults it may not comply with the recent developed grid codes for wind energy conversion systems (WECS). In this paper, a Unified Power Flow Controller (UPFC) is applied to improve the low voltage ride through (LVRT) capability of doubly fed induction generator (DFIG)-based WECS during voltage sag at the grid side. Simulation is carried out using MATLAB/Simulink software. Results show that UPFC can significantly improve the LVRT capability of DFIG-based WECS and hence maintaining wind turbine connection to the grid during certain levels of voltage sag at the grid side.","PeriodicalId":179587,"journal":{"name":"2012 22nd Australasian Universities Power Engineering Conference (AUPEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129703240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicability of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. These potential model could be apply as a local predictor for any proposed hybrid method in the real life application for six hour in advance prediction to ensure constant solar power supply in the smart grid operation.
{"title":"Hybrid prediction method of solar power using different computational intelligence algorithms","authors":"Md. Reduan Hossain, A. Oo, A. S. Ali","doi":"10.4236/SGRE.2013.41011","DOIUrl":"https://doi.org/10.4236/SGRE.2013.41011","url":null,"abstract":"Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicability of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. These potential model could be apply as a local predictor for any proposed hybrid method in the real life application for six hour in advance prediction to ensure constant solar power supply in the smart grid operation.","PeriodicalId":179587,"journal":{"name":"2012 22nd Australasian Universities Power Engineering Conference (AUPEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129205233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[Title page]","authors":"John H Pula","doi":"10.1109/ase.2009.1","DOIUrl":"https://doi.org/10.1109/ase.2009.1","url":null,"abstract":"Presents the title page of the proceedings.","PeriodicalId":179587,"journal":{"name":"2012 22nd Australasian Universities Power Engineering Conference (AUPEC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121840848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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