Ultra Short Term Power Prediction of Offshore Wind Power Based on Support Vector Machine Optimized by Improved Dragonfly Algorithm

  • Yanxia Yu CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China
  • Yingshuai Wu CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China
  • Liang Zhao CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China
  • Xiang Li CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China
  • Yanan Li LSCZ Science and Technology Co., Ltd., Suzhou, Jiangshu, China
Keywords: Support vector machine, dragonfly algorithm, offshore power prediction

Abstract

In order to improve the prediction effect of ultra short term power of offshore wind power, the prediction model based on support vector machine optimized dragonfly algorithm is constructed. Based on summary of the prediction methods of wind power, the support vector machine optimized by dragonfly algorithm is established. Finally, prediction simulation analysis of offshore wind power is carried out, results show that the proposed prediction model in this research can effectively improve the computing prediction precision.

Downloads

Download data is not yet available.

Author Biographies

Yanxia Yu, CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China

Yanxia Yu works in CRRC Dalian Locomotive & Rolling Stock Co., Ltd., serving as chief designer and professoral-level senior engineer. Engage in the research and development and application of intelligent control products and train network control system, undertake the research and development of many major and key science and technology projects of China level and CRRC Corporation, and win a number of science and technology awards of CRRC Corporation and Liaoning Province.

Yingshuai Wu, CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China

Yingshuai Wu works in CRRC Dalian Locomotive & Rolling Stock Co., Ltd., serving as the minister of Development Department and a professoral-level senior engineer. Engaged in technical management and electrical overall design. Undertook a number of CRRC Group’s top technology research and development, won a number of CRRC Group and Liaoning Province science and technology awards.

Liang Zhao, CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China

Liang Zhao works in CRRC Dalian Locomotive & Rolling Stock Co., Ltd., as a project manager and senior engineer of CRRC Dalian Industrial Company. Engaged in the application and promotion of scientific research products, in charge of product testing and product evaluation.

Xiang Li, CRRC Dalian Locomotive & Rolling Stock Co., Ltd., Dalian, Liaoning, China

Xiang Li works in CRRC Dalian Locomotive & Rolling Stock Co., Ltd., as an intelligent product test tester, responsible for product testing and reporting.

Yanan Li, LSCZ Science and Technology Co., Ltd., Suzhou, Jiangshu, China

Yanan Li received her PhD in Control Theory and Control Engineering from DLUT. Currently, she is a senior engineer in LSCZ Science and Technology Co., Ltd.. Her research interests mainly include faulty diagnosis of process control system and intelligent detection.

References

Lin Wang, Rui Tao, Huanling Hu, Yu-Rong Zeng, Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder, Renewable Energy, 2021, 164(2):642-655.

Md Alamgir Hossain, Ripon K. Chakrabortty, Sondoss Elsawah, Michael J. Ryan, Very short-term forecasting of wind power generation using hybrid deep learning model, Journal of Cleaner Production, 2021, 296(5):26564.

Shuang Han, Yan-hui Qiao, Jie Yan, Yong-qian Liu, Li Li, Zheng Wang, Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network, Applied Energy, 2019, 239(4):181-191.

D.Y. Hong, T.Y. Ji, M.S. Li, Q.H. Wu, Ultra-short-term forecast of wind speed and wind power based on morphological high frequency filter and double similarity search algorithm, International Journal of Electrical Power & Energy Systems, 2019, 104(1):868-879.

Marcelo Azevedo Costa, Ramiro Ruiz-Cárdenas, Leandro Brioschi Mineti, Marcos Oliveira Prates, Dynamic time scan forecasting for multi-step wind speed prediction, Renewable Energy, 2021, 177(11):584-595.

Fei Li, Guorui Ren, Jay Lee, Multi-step wind speed prediction based on turbulence intensity and hybrid deep neural networks, Energy Conversion and Management, 2019, 186(4):306-322.

Bikram Kumar, Deepak Gupta, Universum based Lagrangian twin bounded support vector machine to classify EEG signals, Computer Methods and Programs in Biomedicine, 2021, 208(9):106244.

Ran An, Yitian Xu, Xuhua Liu, A rough margin-based multi-task ν-twin support vector machine for pattern classification, Applied Soft Computing, 2021, 112(11):107769

Hao Zhang, Yuxin Shi, Xueran Yang, Ruiling Zhou, A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance, Research in International Business and Finance, 2021, 58(12):101482.

Ricardo ManuelArias Velásquez, Support vector machine and tree models for oil and Kraft degradation in power transformers, Engineering Failure Analysis, 2021, 127(9):105488.

Tao Sun, Renjie Wu, Yifan Cui, Yuejiu Zheng, Sequent extended Kalman filter capacity estimation method for lithium-ion batteries based on discrete battery aging model and support vector machine, Journal of Energy Storage, 2021, 39(7):102594.

Hongfei Zhu, Lianhe Yang, Jianwu Fei, Longgang Zhao, Zhongzhi Han, Recognition of carrot appearance quality based on deep feature and support vector machine, Computers and Electronics in Agriculture, 2021, 186(7):106185.

Xiaoyu Liu, Nan Li, Hailin Mu, Miao Li, Xinxin Liu, Techno-energy-economic assessment of a high capacity offshore wind-pumped-storage hybrid power system for regional power system, Journal of Energy Storage, 2021, 41(9):102892.

Behzad Golparvar, Petros Papadopoulos, Ahmed Aziz Ezzat, Ruo-Qian Wang, A surrogate-model-based approach for estimating the first and second-order moments of offshore wind power, Applied Energy, 2021, 299(10):117286.

Jovana Dakic, Marc Cheah-Mane, Oriol Gomis-Bellmunt, Eduardo Prieto-Araujo, Low frequency AC transmission systems for offshore wind power plants: Design, optimization and comparison to high voltage AC and high voltage DC, International Journal of Electrical Power & Energy Systems, 2021, 133(12):107273

Qian Liu, Yan Sun, Mengcheng Wu, Decision-making methodologies in offshore wind power investments: A review, Journal of Cleaner Production, 2021, 295(5):126459.

Lin Zhou, Pengxiang Huang, Shukai Chi, Ming Li, Hu Zhou, Hongbin Yu, Hongda Cao, Kai Chen, Structural health monitoring of offshore wind power structures based on genetic algorithm optimization and uncertain analytic hierarchy process, Ocean Engineering, 2020, 218(12):108201.

Julian David Hunt, Behnam Zakeri, Alexandre Giulietti de Barros, Walter Leal Filho, Augusto Delavald Marques, Paulo Sérgio Franco Barbosa, Paulo Smith Schneider, Marcelo Farenzena, Buoyancy Energy Storage Technology: An energy storage solution for islands, coastal regions, offshore wind power and hydrogen compression, Journal of Energy Storage, 2021, 40(8):102746

Bagesh Kumar, Ayush Sinha, Sourin Chakrabarti, O.P. Vyas, A fast learning algorithm for One-Class Slab Support Vector Machines, Knowledge-Based Systems, 2021, 228(9):107267.

Hongzheng Shen, Kongtao Jiang, Weiqian Sun, Yue Xu, Xiaoyi Ma, Irrigation decision method for winter wheat growth period in a supplementary irrigation area based on a support vector machine algorithm, Computers and Electronics in Agriculture, 182(3):106032.

Jing Zheng, Junliang Fan, Fucang Zhang, Lifeng Wu, Yufeng Zou, Qianlai Zhuang, Estimation of rainfed maize transpiration under various mulching methods using modified Jarvis-Stewart model and hybrid support vector machine model with whale optimization algorithm, Agricultural Water Management, 2021, 249(4):106799

Wen-Chieh Cheng, Xue-Dong Bai, Brian B. Sheil, Ge Li, Fei Wang, Identifying characteristics of pipejacking parameters to assess geological conditions using optimisation algorithm-based support vector machines, Tunnelling and Underground Space Technology, 2020, 106(12):103592.

Dong Liu, Maoxun Li, Yi Ji, Qiang Fu, Mo Li, Muhammad Abrar Faiz, Shoaib Ali, Tianxiao Li, Song Cui, Muhammad Imran Khan, Spatial-temporal characteristics analysis of water resource system resilience in irrigation areas based on a support vector machine model optimized by the modified gray wolf algorithm, Journal of Hydrology, 2021, 597(6):125758.

Beikun Zhang, Liyun Xu, Jian Zhang, Balancing and sequencing problem of mixed-model U-shaped robotic assembly line: Mathematical model and dragonfly algorithm based approach, Applied Soft Computing, 2021, 98(1):106739.

Shilaja C., Arunprasath T., Internet of medical things-load optimization of power flow based on hybrid enhanced grey wolf optimization and dragonfly algorithm, Future Generation Computer Systems, 2019, 98(9):319-330.

Dipayan Guha, Provas Kumar Roy, Subrate Banerjee, Optimal tuning of 3 degree-of-freedom proportional-integral-derivative controller for hybrid distributed power system using dragonfly algorithm, Computers & Electrical Engineering, 2018, 72(11):137-153

Maya Rocha-Ortega, Pilar Rodríguez, Alex Córdoba-Aguilar, Can dragonfly and damselfly communities be used as bioindicators of land use intensification? Ecological Indicators, 2019, 107(12):105553.

Published
2021-12-08
Section
Renewable Power and Energy Systems