메뉴 건너뛰기




Volumn 150, Issue , 2017, Pages 90-107

Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting

Author keywords

Forecasting accuracy and stability; Hybrid forecasting system; Multi objective ant lion optimization algorithm; Wind speed forecasting

Indexed keywords


EID: 85026831291     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2017.07.065     Document Type: Article
Times cited : (154)

References (42)
  • 1
    • 84976636850 scopus 로고    scopus 로고
    • One day ahead wind speed forecasting: a resampling-based approach
    • Zhao, W., Wei, Y.M., Su, Z., One day ahead wind speed forecasting: a resampling-based approach. Appl Energy 178 (2016), 886–901, 10.1016/j.apenergy.2016.06.098.
    • (2016) Appl Energy , vol.178 , pp. 886-901
    • Zhao, W.1    Wei, Y.M.2    Su, Z.3
  • 2
    • 84983753064 scopus 로고    scopus 로고
    • A hybrid multi-step rolling forecasting model based on SSA and simulated annealing—adaptive particle swarm optimization for wind speed
    • Du, P., Jin, Y., Zhang, K., A hybrid multi-step rolling forecasting model based on SSA and simulated annealing—adaptive particle swarm optimization for wind speed. Sustainability, 8, 2016, 754, 10.3390/su8080754.
    • (2016) Sustainability , vol.8 , pp. 754
    • Du, P.1    Jin, Y.2    Zhang, K.3
  • 3
    • 84903179521 scopus 로고    scopus 로고
    • A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting
    • Su, Z., Wang, J., Lu, H., Zhao, G., A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting. Energy Convers Manage 85 (2014), 443–452, 10.1016/j.enconman.2014.05.058.
    • (2014) Energy Convers Manage , vol.85 , pp. 443-452
    • Su, Z.1    Wang, J.2    Lu, H.3    Zhao, G.4
  • 4
    • 84947969727 scopus 로고    scopus 로고
    • Assessing different parameters estimation methods of Weibull distribution to compute wind power density
    • Mohammadi, K., Alavi, O., Mostafaeipour, A., Goudarzi, N., Jalilvand, M., Assessing different parameters estimation methods of Weibull distribution to compute wind power density. Energy Convers Manage 108 (2016), 322–335, 10.1016/j.enconman.2015.11.015.
    • (2016) Energy Convers Manage , vol.108 , pp. 322-335
    • Mohammadi, K.1    Alavi, O.2    Mostafaeipour, A.3    Goudarzi, N.4    Jalilvand, M.5
  • 5
    • 67349211771 scopus 로고    scopus 로고
    • Forecasting the wind generation using a two-stage network based on meteorological information
    • Fan, S., Liao, J.R., Yokoyama, R., Chen, L., Lee, W.J., Forecasting the wind generation using a two-stage network based on meteorological information. IEEE Trans Energy Convers 24 (2009), 474–482, 10.1109/TEC.2008.2001457.
    • (2009) IEEE Trans Energy Convers , vol.24 , pp. 474-482
    • Fan, S.1    Liao, J.R.2    Yokoyama, R.3    Chen, L.4    Lee, W.J.5
  • 6
    • 84958154004 scopus 로고    scopus 로고
    • Wind speed forecasting based on wavelet packet decomposition and artificial neural networks trained by crisscross optimization algorithm
    • Meng, A., Ge, J., Yin, H., Chen, S., Wind speed forecasting based on wavelet packet decomposition and artificial neural networks trained by crisscross optimization algorithm. Energy Convers Manage 114 (2016), 75–88, 10.1016/j.enconman.2016.02.013.
    • (2016) Energy Convers Manage , vol.114 , pp. 75-88
    • Meng, A.1    Ge, J.2    Yin, H.3    Chen, S.4
  • 7
    • 84989811566 scopus 로고    scopus 로고
    • A hybrid wind power forecasting model based on data mining and wavelets analysis
    • Azimi, R., Ghofrani, M., Ghayekhloo, M., A hybrid wind power forecasting model based on data mining and wavelets analysis. Energy Convers Manage 127 (2016), 208–225, 10.1016/j.enconman.2016.09.002.
    • (2016) Energy Convers Manage , vol.127 , pp. 208-225
    • Azimi, R.1    Ghofrani, M.2    Ghayekhloo, M.3
  • 8
    • 84959301543 scopus 로고    scopus 로고
    • Using artificial neural networks for temporal and spatial wind speed forecasting in Iran
    • Noorollahi, Y., Jokar, M.A., Kalhor, A., Using artificial neural networks for temporal and spatial wind speed forecasting in Iran. Energy Convers Manage 115 (2016), 17–25, 10.1016/j.enconman.2016.02.041.
    • (2016) Energy Convers Manage , vol.115 , pp. 17-25
    • Noorollahi, Y.1    Jokar, M.A.2    Kalhor, A.3
  • 9
    • 84860254202 scopus 로고    scopus 로고
    • A method for short-term wind power prediction with multiple observation points
    • Khalid, M., Savkin, A.V., A method for short-term wind power prediction with multiple observation points. IEEE Trans Power Syst 27 (2012), 579–586, 10.1109/TPWRS.2011.2160295.
    • (2012) IEEE Trans Power Syst , vol.27 , pp. 579-586
    • Khalid, M.1    Savkin, A.V.2
  • 10
    • 0342571696 scopus 로고    scopus 로고
    • Wind energy technology and current status: a review
    • Ackermann, T., Söder, L., Wind energy technology and current status: a review. Renew Sustain Energy Rev 4 (2000), 315–374, 10.1016/S1364-0321(00)00004-6.
    • (2000) Renew Sustain Energy Rev , vol.4 , pp. 315-374
    • Ackermann, T.1    Söder, L.2
  • 11
    • 84905494402 scopus 로고    scopus 로고
    • Forecasting wind speed using empirical mode decomposition and Elman neural network
    • Wang, J.J., Zhang, W., Li, Y., Wang, J.J., Dang, Z., Forecasting wind speed using empirical mode decomposition and Elman neural network. Appl Soft Comput 23 (2014), 452–459, 10.1016/j.asoc.2014.06.027.
    • (2014) Appl Soft Comput , vol.23 , pp. 452-459
    • Wang, J.J.1    Zhang, W.2    Li, Y.3    Wang, J.J.4    Dang, Z.5
  • 12
    • 84862213628 scopus 로고    scopus 로고
    • Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
    • Liu, H., Tian, H.Q., Li, Y.F., Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction. Appl Energy 98 (2012), 415–424, 10.1016/j.apenergy.2012.04.001.
    • (2012) Appl Energy , vol.98 , pp. 415-424
    • Liu, H.1    Tian, H.Q.2    Li, Y.F.3
  • 13
    • 84946594359 scopus 로고    scopus 로고
    • An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
    • Zhao, J., Guo, Z.H., Su, Z.Y., Zhao, Z.Y., Xiao, X., Liu, F., An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed. Appl Energy 162 (2016), 808–826, 10.1016/j.apenergy.2015.10.145.
    • (2016) Appl Energy , vol.162 , pp. 808-826
    • Zhao, J.1    Guo, Z.H.2    Su, Z.Y.3    Zhao, Z.Y.4    Xiao, X.5    Liu, F.6
  • 14
    • 0041522327 scopus 로고    scopus 로고
    • Forecasting and simulating wind speed in Corsica by using an autoregressive model
    • Poggi, P., Muselli, M., Notton, G., Cristofari, C., Louche, A., Forecasting and simulating wind speed in Corsica by using an autoregressive model. Energy Convers Manage 44 (2003), 3177–3196, 10.1016/S0196-8904(03)00108-0.
    • (2003) Energy Convers Manage , vol.44 , pp. 3177-3196
    • Poggi, P.1    Muselli, M.2    Notton, G.3    Cristofari, C.4    Louche, A.5
  • 15
    • 84903579343 scopus 로고    scopus 로고
    • A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
    • Babu, C.N., Reddy, B.E., A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data. Appl Soft Comput 23 (2014), 27–38, 10.1016/j.asoc.2014.05.028.
    • (2014) Appl Soft Comput , vol.23 , pp. 27-38
    • Babu, C.N.1    Reddy, B.E.2
  • 16
    • 58949103845 scopus 로고    scopus 로고
    • Day-ahead wind speed forecasting using f-ARIMA models
    • Kavasseri, R.G., Seetharaman, K., Day-ahead wind speed forecasting using f-ARIMA models. Renew Energy 34 (2009), 1388–1393, 10.1016/j.renene.2008.09.006.
    • (2009) Renew Energy , vol.34 , pp. 1388-1393
    • Kavasseri, R.G.1    Seetharaman, K.2
  • 17
    • 85017562291 scopus 로고    scopus 로고
    • A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting
    • Zhang, C., Zhou, J., Li, C., Fu, W., Peng, T., A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting. Energy Convers Manage 143 (2017), 360–376, 10.1016/j.enconman.2017.04.007.
    • (2017) Energy Convers Manage , vol.143 , pp. 360-376
    • Zhang, C.1    Zhou, J.2    Li, C.3    Fu, W.4    Peng, T.5
  • 18
    • 85017476969 scopus 로고    scopus 로고
    • Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm
    • Xiao, L., Qian, F., Shao, W., Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm. Energy Convers Manage 143 (2017), 410–430, 10.1016/j.enconman.2017.04.012.
    • (2017) Energy Convers Manage , vol.143 , pp. 410-430
    • Xiao, L.1    Qian, F.2    Shao, W.3
  • 19
    • 84960381924 scopus 로고    scopus 로고
    • Forecasting energy market indices with recurrent neural networks: case study of crude oil price fluctuations
    • Wang, J., Wang, J., Forecasting energy market indices with recurrent neural networks: case study of crude oil price fluctuations. Energy 102 (2016), 365–374, 10.1016/j.energy.2016.02.098.
    • (2016) Energy , vol.102 , pp. 365-374
    • Wang, J.1    Wang, J.2
  • 20
    • 51849142610 scopus 로고    scopus 로고
    • Short term wind speed forecasting in La Venta, Oaxaca, México, using artificial neural networks
    • Cadenas, E., Rivera, W., Short term wind speed forecasting in La Venta, Oaxaca, México, using artificial neural networks. Renew Energy 34 (2009), 274–278, 10.1016/j.renene.2008.03.014.
    • (2009) Renew Energy , vol.34 , pp. 274-278
    • Cadenas, E.1    Rivera, W.2
  • 21
    • 84892441792 scopus 로고    scopus 로고
    • Optimal parameters selection for BP neural network based on particle swarm optimization: a case study of wind speed forecasting
    • Ren, C., An, N., Wang, J., Li, L., Hu, B., Shang, D., Optimal parameters selection for BP neural network based on particle swarm optimization: a case study of wind speed forecasting. Knowl-Based Syst 56 (2014), 226–239, 10.1016/j.knosys.2013.11.015.
    • (2014) Knowl-Based Syst , vol.56 , pp. 226-239
    • Ren, C.1    An, N.2    Wang, J.3    Li, L.4    Hu, B.5    Shang, D.6
  • 22
    • 84929923153 scopus 로고    scopus 로고
    • Short-term probabilistic forecasting of wind speed using stochastic differential equations
    • Iversen, E.B., Morales, J.M., Møller, J.K., Madsen, H., Short-term probabilistic forecasting of wind speed using stochastic differential equations. Int J Forecast 32 (2016), 981–990, 10.1016/j.ijforecast.2015.03.001.
    • (2016) Int J Forecast , vol.32 , pp. 981-990
    • Iversen, E.B.1    Morales, J.M.2    Møller, J.K.3    Madsen, H.4
  • 23
    • 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. Renew Sustain Energy Rev 34 (2014), 243–254, 10.1016/j.rser.2014.03.033.
    • (2014) Renew Sustain Energy Rev , vol.34 , pp. 243-254
    • Tascikaraoglu, A.1    Uzunoglu, M.2
  • 24
    • 84980410056 scopus 로고    scopus 로고
    • Research and application of a hybrid model based on multi-objective optimization for electrical load forecasting
    • Xiao, L., Shao, W., Wang, C., Zhang, K., Lu, H., Research and application of a hybrid model based on multi-objective optimization for electrical load forecasting. Appl Energy 180 (2016), 213–233, 10.1016/j.apenergy.2016.07.113.
    • (2016) Appl Energy , vol.180 , pp. 213-233
    • Xiao, L.1    Shao, W.2    Wang, C.3    Zhang, K.4    Lu, H.5
  • 25
    • 85010282413 scopus 로고    scopus 로고
    • A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting
    • Zhang, W., Qu, Z., Zhang, K., Mao, W., Ma, Y., Fan, X., A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting. Energy Convers Manage 136 (2017), 439–451, 10.1016/j.enconman.2017.01.022.
    • (2017) Energy Convers Manage , vol.136 , pp. 439-451
    • Zhang, W.1    Qu, Z.2    Zhang, K.3    Mao, W.4    Ma, Y.5    Fan, X.6
  • 26
    • 84922796172 scopus 로고    scopus 로고
    • Combined forecasting models for wind energy forecasting: a case study in China
    • Xiao, L., Wang, J., Dong, Y., Wu, J., Combined forecasting models for wind energy forecasting: a case study in China. Renew Sustain Energy Rev 44 (2015), 271–288, 10.1016/j.rser.2014.12.012.
    • (2015) Renew Sustain Energy Rev , vol.44 , pp. 271-288
    • Xiao, L.1    Wang, J.2    Dong, Y.3    Wu, J.4
  • 27
    • 84995617473 scopus 로고    scopus 로고
    • Air quality early-warning system for cities in China
    • Xu, Y., Yang, W., Wang, J., Air quality early-warning system for cities in China. Atmos Environ 148 (2017), 239–257, 10.1016/j.atmosenv.2016.10.046.
    • (2017) Atmos Environ , vol.148 , pp. 239-257
    • Xu, Y.1    Yang, W.2    Wang, J.3
  • 28
    • 84858001572 scopus 로고    scopus 로고
    • A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting
    • Tang, L., Yu, L., Wang, S., Li, J., Wang, S., A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting. Appl Energy 93 (2012), 432–443, 10.1016/j.apenergy.2011.12.030.
    • (2012) Appl Energy , vol.93 , pp. 432-443
    • Tang, L.1    Yu, L.2    Wang, S.3    Li, J.4    Wang, S.5
  • 29
    • 84962148959 scopus 로고    scopus 로고
    • Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method
    • Wang, S., Zhang, N., Wu, L., Wang, Y., Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method. Renew Energy 94 (2016), 629–636, 10.1016/j.renene.2016.03.103.
    • (2016) Renew Energy , vol.94 , pp. 629-636
    • Wang, S.1    Zhang, N.2    Wu, L.3    Wang, Y.4
  • 30
    • 84994644911 scopus 로고    scopus 로고
    • A hybrid non-dominated sorting genetic algorithm and its application on multi-objective optimal design of nuclear power plant
    • Chen, L., Yan, C., Liao, Y., Song, F., Jia, Z., A hybrid non-dominated sorting genetic algorithm and its application on multi-objective optimal design of nuclear power plant. Ann Nucl Energy 100 (2017), 150–159, 10.1016/j.anucene.2016.09.030.
    • (2017) Ann Nucl Energy , vol.100 , pp. 150-159
    • Chen, L.1    Yan, C.2    Liao, Y.3    Song, F.4    Jia, Z.5
  • 31
    • 85008420154 scopus 로고    scopus 로고
    • An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times
    • Lu, C., Li, X., Gao, L., Liao, W., Yi, J., An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times. Comput Ind Eng 104 (2017), 156–174, 10.1016/j.cie.2016.12.020.
    • (2017) Comput Ind Eng , vol.104 , pp. 156-174
    • Lu, C.1    Li, X.2    Gao, L.3    Liao, W.4    Yi, J.5
  • 32
    • 84979263751 scopus 로고    scopus 로고
    • Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems
    • Mirjalili, S., Jangir, P., Saremi, S., Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems. Appl Intell 46 (2017), 79–95, 10.1007/s10489-016-0825-8.
    • (2017) Appl Intell , vol.46 , pp. 79-95
    • Mirjalili, S.1    Jangir, P.2    Saremi, S.3
  • 33
    • 79956369785 scopus 로고    scopus 로고
    • Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method
    • Yeh, J.-R., Shieh, J.-S., Huang, N.E., Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method. Adv Adapt Data Anal 2 (2010), 135–156, 10.1142/S1793536910000422.
    • (2010) Adv Adapt Data Anal , vol.2 , pp. 135-156
    • Yeh, J.-R.1    Shieh, J.-S.2    Huang, N.E.3
  • 34
    • 80052078099 scopus 로고    scopus 로고
    • Ensemble empirical mode decomposition: a noise-assisted data analysis method
    • Wu, Z., Huang, N.E., Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 1 (2009), 1–41, 10.1142/S1793536909000047.
    • (2009) Adv Adapt Data Anal , vol.1 , pp. 1-41
    • Wu, Z.1    Huang, N.E.2
  • 35
    • 0003953570 scopus 로고
    • Mathematical physics
    • Keagan London (England)
    • Edgeworth, F.Y., Mathematical physics. 1881, Keagan, London (England).
    • (1881)
    • Edgeworth, F.Y.1
  • 36
    • 0003733205 scopus 로고
    • Cours d'economie politique
    • Librairie Droz
    • Pareto, V., Cours d'economie politique. 1964, Librairie Droz.
    • (1964)
    • Pareto, V.1
  • 38
    • 84956971491 scopus 로고    scopus 로고
    • Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller
    • Raju, M., Saikia, L.C., Sinha, N., Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller. Int J Electr Power Energy Syst 80 (2016), 52–63, 10.1016/j.ijepes.2016.01.037.
    • (2016) Int J Electr Power Energy Syst , vol.80 , pp. 52-63
    • Raju, M.1    Saikia, L.C.2    Sinha, N.3
  • 39
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elman, J.L., Finding structure in time. Cogn Sci 14 (1990), 179–211.
    • (1990) Cogn Sci , vol.14 , pp. 179-211
    • Elman, J.L.1
  • 40
    • 68249136965 scopus 로고
    • Comparing predictive accuracy
    • Diebold, F.X., Mariano, R.S., Comparing predictive accuracy. J Bus Econ Stat 13 (1995), 253–263.
    • (1995) J Bus Econ Stat , vol.13 , pp. 253-263
    • Diebold, F.X.1    Mariano, R.S.2
  • 41
    • 0031891445 scopus 로고    scopus 로고
    • A sequential learning approach for single hidden layer neural networks
    • Zhang, J., Morris, A.J., A sequential learning approach for single hidden layer neural networks. Neural Netw 11 (1998), 65–80.
    • (1998) Neural Netw , vol.11 , pp. 65-80
    • Zhang, J.1    Morris, A.J.2
  • 42
    • 85006900517 scopus 로고    scopus 로고
    • A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting
    • Jiang, P., Liu, F., Song, Y., A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting. Energy 119 (2017), 694–709, 10.1016/j.energy.2016.11.034.
    • (2017) Energy , vol.119 , pp. 694-709
    • Jiang, P.1    Liu, F.2    Song, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.