메뉴 건너뛰기




Volumn 39, Issue 20, 2015, Pages 12-18

Dynamic optimal combination model considering adaptive exponential for ultra-short term wind power prediction

Author keywords

Adaptive forgetting factors; Cook's distance; Dynamic combination forecast; Wind power prediction

Indexed keywords

MULTILAYER NEURAL NETWORKS; WEATHER FORECASTING; WIND POWER;

EID: 84945934357     PISSN: 10001026     EISSN: None     Source Type: Journal    
DOI: 10.7500/AEPS20141128002     Document Type: Article
Times cited : (15)

References (28)
  • 1
    • 77957605946 scopus 로고    scopus 로고
    • Problems and measures of power grid accommodating large scale wind power
    • ZHANG Liying, YE Tinglu, XIN Yaozhong, et al. Problems and measures of power grid accommodating large scale wind power [J]. Proceedings of the CSEE, 2010, 30(25): 1-9.
    • (2010) Proceedings of the CSEE , vol.30 , Issue.25 , pp. 1-9
    • Zhang, L.1    Ye, T.2    Xin, Y.3
  • 2
    • 83255192458 scopus 로고    scopus 로고
    • Coordinated control frame of large-scale intermittent power plant cluster
    • XUE Feng, CHANG Kang, WANG Ningbo. Coordinated control frame of large-scale intermittent power plant cluster [J]. Automation of Electric Power Systems, 2011, 35(22): 45-53.
    • (2011) Automation of Electric Power Systems , vol.35 , Issue.22 , pp. 45-53
    • Xue, F.1    Chang, K.2    Wang, N.3
  • 3
    • 84902341795 scopus 로고    scopus 로고
    • Overview of problems in large-scale wind integrations
    • YUAN Xiaoming. Overview of problems in large-scale wind integrations [J]. Journal of Modern Power Systems and Clean Energy, 2013, 1(1): 22-25.
    • (2013) Journal of Modern Power Systems and Clean Energy , vol.1 , Issue.1 , pp. 22-25
    • Yuan, X.1
  • 4
    • 84927131442 scopus 로고    scopus 로고
    • A review on short-term and ultra-short-term wind power prediction
    • XUE Yusheng, YU Chen, ZHAO Junhua, et al. A review on short-term and ultra-short-term wind power prediction [J]. Automation of Electric Power Systems, 2015, 39(6): 141-151.
    • (2015) Automation of Electric Power Systems , vol.39 , Issue.6 , pp. 141-151
    • Xue, Y.1    Yu, C.2    Zhao, J.3
  • 6
    • 79960287766 scopus 로고    scopus 로고
    • A comprehensive error evaluation method for short-term wind power prediction
    • XU Man, QIAO Ying, LU Zongxiang. A comprehensive error evaluation method for short-term wind power prediction [J]. Automation of Electric Power Systems, 2011, 35(12): 20-26.
    • (2011) Automation of Electric Power Systems , vol.35 , Issue.12 , pp. 20-26
    • Xu, M.1    Qiao, Y.2    Lu, Z.3
  • 7
    • 33947506506 scopus 로고    scopus 로고
    • Total transfer capability calculation of power system including large-scale wind farm
    • WANG Chengshan, SUN Wei, WANG Xinggang. Total transfer capability calculation of power system including large-scale wind farm [J]. Automation of Electric Power Systems, 2007, 31(2): 17-21.
    • (2007) Automation of Electric Power Systems , vol.31 , Issue.2 , pp. 17-21
    • Wang, C.1    Sun, W.2    Wang, X.3
  • 8
    • 84876806520 scopus 로고    scopus 로고
    • A regional wind power forecasting method based on statistical upscaling approach
    • CHEN Ying, SUN Rongfu, WU Zhijian, et al. A regional wind power forecasting method based on statistical upscaling approach [J]. Automation of Electric Power Systems, 2013, 37(7): 1-5.
    • (2013) Automation of Electric Power Systems , vol.37 , Issue.7 , pp. 1-5
    • Chen, Y.1    Sun, R.2    Wu, Z.3
  • 9
    • 77349103016 scopus 로고    scopus 로고
    • Study on the physical approach to wind power prediction
    • FENG Shuanglei, WANG Weisheng, LIU Chun, et al. Study on the physical approach to wind power prediction [J]. Proceedings of the CSEE, 2010, 30(2): 1-6.
    • (2010) Proceedings of the CSEE , vol.30 , Issue.2 , pp. 1-6
    • Feng, S.1    Wang, W.2    Liu, C.3
  • 11
    • 84865813922 scopus 로고    scopus 로고
    • Wind power prediction method based on sequential time clustering support vector machine
    • DING Zhiyong, YANG Ping, YANG Xi, et al. Wind power prediction method based on sequential time clustering support vector machine [J]. Automation of Electric Power Systems, 2012, 36(14): 131-135.
    • (2012) Automation of Electric Power Systems , vol.36 , Issue.14 , pp. 131-135
    • Ding, Z.1    Yang, P.2    Yang, X.3
  • 12
    • 57949110864 scopus 로고    scopus 로고
    • Wind power prediction based on artificial neural network
    • FAN Gaofeng, WANG Weisheng, LIU Chun, et al. Wind power prediction based on artificial neural network [J]. Proceedings of the CSEE, 2008, 28(34): 118-123.
    • (2008) Proceedings of the CSEE , vol.28 , Issue.34 , pp. 118-123
    • Fan, G.1    Wang, W.2    Liu, C.3
  • 13
    • 84897459902 scopus 로고    scopus 로고
    • A review of combined approaches for prediction of short-term wind speed and power
    • TASCIKARAOGLU A, UZUNOGLU M. A review of combined approaches for prediction of short-term wind speed and power [J]. Renewable and Sustainable Energy Reviews, 2014, 34: 243-254.
    • (2014) Renewable and Sustainable Energy Reviews , vol.34 , pp. 243-254
    • Tascikaraoglu, A.1    Uzunoglu, M.2
  • 14
    • 84885450326 scopus 로고    scopus 로고
    • Combined model for ultra short-term wind power prediction based on sample entropy and extreme learning machine
    • ZHANG Xueqing, LIANG Jun, ZHANG Xi, et al. Combined model for ultra short-term wind power prediction based on sample entropy and extreme learning machine [J]. Proceedings of the CSEE, 2013, 33(25): 33-40.
    • (2013) Proceedings of the CSEE , vol.33 , Issue.25 , pp. 33-40
    • Zhang, X.1    Liang, J.2    Zhang, X.3
  • 15
    • 82055184071 scopus 로고    scopus 로고
    • Combined model based on EMD-SVM for short-term wind power prediction
    • YE Lin, LIU Peng. Combined model based on EMD-SVM for short-term wind power prediction [J]. Proceedings of the CSEE, 2011, 31(31): 102-108.
    • (2011) Proceedings of the CSEE , vol.31 , Issue.31 , pp. 102-108
    • Ye, L.1    Liu, P.2
  • 16
    • 80052788143 scopus 로고    scopus 로고
    • A short-term wind power prediction method based on wavelet decomposition and BP neural network
    • SHI Hongtao, YANG Jingling, DING Maosheng, et al. A short-term wind power prediction method based on wavelet decomposition and BP neural network [J]. Automation of Electric Power Systems, 2011, 35(16): 44-48.
    • (2011) Automation of Electric Power Systems , vol.35 , Issue.16 , pp. 44-48
    • Shi, H.1    Yang, J.2    Ding, M.3
  • 18
    • 84891498604 scopus 로고    scopus 로고
    • Improved short-term wind power forecasting method based on accumulative error correction
    • MAO Meiqin, CAO Yu, ZHOU Songlin. Improved short-term wind power forecasting method based on accumulative error correction [J]. Automation of Electric Power Systems, 2013, 37(23): 34-38.
    • (2013) Automation of Electric Power Systems , vol.37 , Issue.23 , pp. 34-38
    • Mao, M.1    Cao, Y.2    Zhou, S.3
  • 19
    • 78651570639 scopus 로고    scopus 로고
    • A combination forecasting model for wind farm output power
    • LIU Chun, FAN Gaofeng, WANG Weisheng, et al. A combination forecasting model for wind farm output power [J]. Power System Technology, 2009, 33(13): 74-79.
    • (2009) Power System Technology , vol.33 , Issue.13 , pp. 74-79
    • Liu, C.1    Fan, G.2    Wang, W.3
  • 20
    • 70350528549 scopus 로고    scopus 로고
    • Wind speed and wind turbine output forecast based on combination method
    • ZHANG Guoqiang, ZHANG Boming. Wind speed and wind turbine output forecast based on combination method [J]. Automation of Electric Power Systems, 2009, 33(18): 92-95.
    • (2009) Automation of Electric Power Systems , vol.33 , Issue.18 , pp. 92-95
    • Zhang, G.1    Zhang, B.2
  • 21
    • 79952454042 scopus 로고    scopus 로고
    • Multiple architecture system for wind speed prediction
    • BOUZGOU H, BENOUDJIT N. Multiple architecture system for wind speed prediction [J]. Applied Energy, 2011, 88(7): 2463-2471.
    • (2011) Applied Energy , vol.88 , Issue.7 , pp. 2463-2471
    • Bouzgou, H.1    Benoudjit, N.2
  • 22
    • 84870801010 scopus 로고    scopus 로고
    • Wind power combination prediction based on the maximum information entropy principle
    • June 24-28, 2012, Puerto Vallarta, Mexico
    • HAN S, LIU Y, LI J. Wind power combination prediction based on the maximum information entropy principle [C]// World Automation Congress, June 24-28, 2012, Puerto Vallarta, Mexico: 4p.
    • (2012) World Automation Congress , pp. 4
    • Han, S.1    Liu, Y.2    Li, J.3
  • 23
    • 84857460469 scopus 로고    scopus 로고
    • A combination method for wind power prediction based on cross entropy theory
    • CHEN Ning, SHA Qian, TANG Yi, et al. A combination method for wind power prediction based on cross entropy theory [J]. Proceedings of the CSEE, 2012, 32(4): 29-34.
    • (2012) Proceedings of the CSEE , vol.32 , Issue.4 , pp. 29-34
    • Chen, N.1    Sha, Q.2    Tang, Y.3
  • 24
    • 84897711411 scopus 로고    scopus 로고
    • A harmonic current detection method based on variable forgetting factor RLS algorithm
    • HAN Wei, WANG Dazhi, LIU Zhen. A harmonic current detection method based on variable forgetting factor RLS algorithm [J]. Transactions of China Electrotechnical Society, 2013, 28(12): 70-74.
    • (2013) Transactions of China Electrotechnical Society , vol.28 , Issue.12 , pp. 70-74
    • Han, W.1    Wang, D.2    Liu, Z.3
  • 25
    • 33344458837 scopus 로고    scopus 로고
    • Recursive estimation of dynamic models using Cook's distance, with application to wind energy forecast
    • SÁNCHEZ I. Recursive estimation of dynamic models using Cook's distance, with application to wind energy forecast [J]. Technometrics, 2006, 48(1): 61-73.
    • (2006) Technometrics , vol.48 , Issue.1 , pp. 61-73
    • Sánchez, I.1
  • 26
    • 0742271676 scopus 로고    scopus 로고
    • Combining time series models for forecasting
    • ZOU H, YANG Y. Combining time series models for forecasting [J]. International Journal of Forecasting, 2004, 20(1): 69-84.
    • (2004) International Journal of Forecasting , vol.20 , Issue.1 , pp. 69-84
    • Zou, H.1    Yang, Y.2
  • 27
    • 55349144840 scopus 로고    scopus 로고
    • Adaptive combination of forecasts with application to wind energy
    • SÁNCHEZ I. Adaptive combination of forecasts with application to wind energy [J]. International Journal of Forecasting, 2008, 24(4): 679-693.
    • (2008) International Journal of Forecasting , vol.24 , Issue.4 , pp. 679-693
    • Sánchez, I.1
  • 28
    • 74949136254 scopus 로고    scopus 로고
    • Development of methods for regional wind power forecasting
    • France: Ecole des Mines de Paris
    • SIEBERT N. Development of methods for regional wind power forecasting [R]. France: Ecole des Mines de Paris, 2008.
    • (2008)
    • Siebert, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.