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A review of short‐term wind power probabilistic forecasting and a taxonomy focused on input data

Ioannis K. Bazionis, Panagiotis A. Karafotis, Pavlos S. Georgilakis
2021 IET Renewable Power Generation  
A review of state-of-the-art short-term wind power probabilistic forecasting models is the focus here.  ...  Future directions in the field of short-term wind power probabilistic forecasting are also proposed.  ...  Short-term WPPF Various wind power probabilistic forecasting models are proposed in the reviewed works . All these works focus on short-term wind power forecasting.  ... 
doi:10.1049/rpg2.12330 fatcat:wk2piydl4fcrvd22jq5qsc7aem

Forecasting renewable energy for environmental resilience through computational intelligence

Mansoor Khan, Essam A. Al-Ammar, Muhammad Rashid Naeem, Wonsuk Ko, Hyeong-Jin Choi, Hyun-Koo Kang, Zaher Mundher Yaseen
2021 PLoS ONE  
Wind power forecasting plays a key role in the design and maintenance of wind power generation which can directly help to enhance environment resilience.  ...  Second, a mixture of the CNN and LSTM models is used to train prominent wind features and further improve forecasting accuracy.  ...  for short-term power forecasting.  ... 
doi:10.1371/journal.pone.0256381 pmid:34415924 pmcid:PMC8378711 fatcat:paeq4ik5nve6bdqsbuxo7iizxu

An Efficient Hybrid Forecasting Approach for Wind Speed Time Series

Bhargavi Munnaluri, K. Ganesh Reddy
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Wind forecasting is one of the best efficient ways to deal with the challenges of wind power generation.  ...  For future management and for future utilization of power, we need to predict the wind speed.  ...  Many improvements in forecasting for short-term time series can be realized by utilizing intelligent approaches .When these models are applied to different wind farms, their forecasting accuracy varies  ... 
doi:10.23956/ijarcsse.v7i9.404 fatcat:6q2fallte5ahlna4woxmjk4n7m

Review of Deterministic and Probabilistic Wind Power Forecasting: Models, Methods, and Future Research

Ioannis K. Bazionis, Pavlos S. Georgilakis
2021 Electricity  
The need to turn to more environmentally friendly sources of energy has led energy systems to focus on renewable sources of energy. Wind power has been a widely used source of green energy.  ...  Deterministic forecasting models have been the main focus of researchers and are still being developed in order to improve their accuracy.  ...  Predictions of NWP models with lower temporal validity are used for short-term wind power forecasting [16] .  ... 
doi:10.3390/electricity2010002 fatcat:7jm5mqb5o5hpblcqprrrjyv37q

Load Forecasting Model for Energy Management System using Elman Neural Network

Sandhiya Devarajan, Chitra S
2019 International Research Journal of Multidisciplinary Technovation  
An accurate system load forecasting which is used to calculate short-term electric load forecasts, is an essential component of any Energy Management System (EMS).  ...  Electric load forecasting is used for forecasting of future electric loads.  ...  Accurate short term load forecasts are necessary for unit commitment and economic dispatch. Very short-term load forecasting is for minutes ahead and is used for automatic generation control (AGC).  ... 
doi:10.34256/irjmt1936 fatcat:5uox4efjjzdkjhz7vqkrxw33p4

A Short-Term Wind Power Forecast Method via XGBoost Hyper-Parameters Optimization

Xiong Xiong, Xiaojie Guo, Pingliang Zeng, Ruiling Zou, Xiaolong Wang
2022 Frontiers in Energy Research  
An improved XGBoost algorithm via Bayesian hyperparameter optimization (BH-XGBoost method) was proposed in this article, which is employed to forecast the short-term wind power for wind farms.  ...  The comparison results led to the recommendation that the BH-XGBoost method is an effective method to forecast the short-term wind power for wind farms.  ...  XX wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.  ... 
doi:10.3389/fenrg.2022.905155 fatcat:732jtesp65dbjfamjpvjxjxzay

Examination of turbulence impacts on ultra-short-term wind power and speed forecasts with machine learning

Hao Chen, Yngve Birkelund, Fuqing Yuan
2021 Energy Reports  
Besides, differences between the types of algorithms for ultra-short-term wind forecasts are also statistically insignificant, demonstrating the unique stochasticity and complexity of wind speed and power  ...  This paper investigates the use of turbulence intensity for ultra-short-term predictions of wind power and speed with a wind farm in the Arctic, including and excluding wind turbulence, within three hours  ...  Shi K et al. (2018) [7] also demonstrated the enhanced accuracy, efficiency, and robustness of improved random forests for short-term wind power forecasting, which has better performance than the backpropagation  ... 
doi:10.1016/j.egyr.2021.08.040 fatcat:buoy5grzwnh57migovheapajke

An improved random forest model of short-term wind-power forecasting to enhance accuracy, efficiency, and robustness

Kunpeng Shi, Ying Qiao, Wei Zhao, Qing Wang, Menghua Liu, Zongxiang Lu
2018 Wind Energy  
An improved random forest model of short-term wind-power forecasting to enhance accuracy, eciency, and robustness.  ...  2018) 'An improved random forest model of short-term wind-power forecasting to enhance accuracy, eciency, and robustness.', Wind energy., 21 (12). pp. 1383-1394. . (2018).  ...  In order to improve the accuracy of short-term wind power prediction, the combination of physical and statistical models is usually adopted.  ... 
doi:10.1002/we.2261 fatcat:q2epkrebmbaingdqwhktr3us5q

Short-term wind power prediction based on extreme learning machine with error correction

Zhi Li, Lin Ye, Yongning Zhao, Xuri Song, Jingzhu Teng, Jingxin Jin
2016 Protection and Control of Modern Power Systems  
Conclusion: The ultra-short-term wind power forecasting accuracy is further improved by using error correction in terms of normalized root mean squared error (NRMSE).  ...  Firstly an ELM is utilized to forecast the short-term wind power.  ...  The ultra-short-term power forecasting is acquired based on processing the forecasting error of short-term forecasting results based on the persistence method in terms of Normalized Root Mean Square Error  ... 
doi:10.1186/s41601-016-0016-y fatcat:slubwtkdlzdjjnd67x3bdfebyy

Real-time Wind Power Prediction System Based on Smart-Grid in Jeju, Korea

Kwon Kim, Young-Jun Seo, Kyoung-Seob Moon, Young-Mi Lee
2012 Journal of International Council on Electrical Engineering  
This is composed of the meteorological forecasting module, calculation module of wind power output and HMI visualization system.  ...  The final output data from this system is short-term (6hr ahead) and mid-term (48hr ahead) wind power prediction values. These values are produced by using physical and statistical model.  ...  Acknowledgements The authors would like to thank many people involved in Real-time Wind Power Prediction System Based on Smart-Grid in Jeju, Korea  ... 
doi:10.5370/jicee.2012.2.2.194 fatcat:m57fta2czbeqjid22zocj555x4

Review on Deep Learning Research and Applications in Wind and Wave Energy

Chengcheng Gu, Hua Li
2022 Energies  
This paper concludes that applications supported by deep learning have enormous potential in terms of energy optimization, harvesting, management, forecasting, behavior exploration and identification.  ...  In the field of big data handing and mining, artificial intelligence plays a critical and efficient role in energy system transition, harvesting and related applications.  ...  Acknowledgments: The authors are thankful for the support of Texas A&M University-Kingsville, National Science Foundation (award # 1757812), National Institute of Standards and Technology (Award # 70NANB20H186  ... 
doi:10.3390/en15041510 fatcat:ww4363yzlfao7bqzsxt7j7l3nm

Review of Evaluation Criteria and Main Methods of Wind Power Forecasting

Xin Zhao, Shuangxin Wang, Tao Li
2011 Energy Procedia  
Wind power forecasting (WPF) will be an important part of the power system construction in the future. Firstly, the classification of WPF is discussed according to the different classified methods.  ...  Wind power has characteristics of randomness and uncontrollability. China needs to learn from the successful experience of wind power prediction in European.  ...  Acknowledgement This work was supported by the National Natural Science Foundation of China under Grant No. 50776005.  ... 
doi:10.1016/j.egypro.2011.10.102 fatcat:csgwfqbtdncafposaehj4eeb54

Optimization of the ANNs Models Performance in the Short-Term Forecasting of the Wind Power of Wind Farms [chapter]

Sergio Velázquez-Medina, Ulises Portero-Ajenjo
2021 Theory of Complexity - Definitions, Models, and Applications [Working Title]  
Due to the low dispatchability of wind power, the massive integration of this energy source in electrical systems requires short-term and very short-term wind farm power output forecasting models to be  ...  A study is conducted in the present paper of potential improvements to the performance of artificial neural network (ANN) models in terms of efficiency and stability.  ...  Improvements in error for two specific models due to implementation of cases A and B.  ... 
doi:10.5772/intechopen.97190 fatcat:37xwlyeivbc2fa6vzba3eucxdu

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Xing Deng, Haijian Shao, Chunlong Hu, Dengbiao Jiang, Yingtao Jiang
2020 CMES - Computer Modeling in Engineering & Sciences  
Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of the atmosphere that  ...  less affected information for forecasting.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmes.2020.08768 fatcat:kjw6rmpjxfdqlp6l57bvzm4wny

Wind Energy

Ming-Hung Hsu, Wei-Jen Lee, Jao-Hwa Kuang, Hua-Shan Tai
2013 Mathematical Problems in Engineering  
short-term wind speed forecasting.  ...  Hong, in their paper "Improved formulation for the optimization of wind turbine placement in a wind farm, " proposed an efficient optimization formulation for the optimal layout of wind turbine placements  ...  short-term wind speed forecasting.  ... 
doi:10.1155/2013/759686 fatcat:n3cnljpyyfh57d5ovxdsusgdhe
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