Wind Energy Forecasting Using Hammerstein-Winer Model

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@article{1709586,
      author = {Zaharaddeen Hassan Abdulganiyu},
      title = {Wind Energy Forecasting Using Hammerstein-Winer Model},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {1},
      pages = {470-492},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709586.pdf},
      abstract = {Wind energy has become the world?s fastest growing source of clean and renewable energy and now contributes a large proportion of total power generation. This proportion will continue to increase because of the global preference for a clean and renewable energy source. However, wind power is difficult to integrate into traditional generation and distribution systems with current technology because it is intermittent, unpredictable and volatile. Thus, it is difficult to match wind generation to energy demand, and the imbalances between demand and generation can cause adverse voltage variations. This power quality problem cannot be solved effectively only by renewable generating technology and/or power electronics. As a whole, wind power integration challenge the power quality, energy planning and power flow controls in the grid. This can be more severe in weak networks, where the whole wind power source may even be disconnected from the grid. In this case, wind energy is forecasted using Hammerstein-wiener model in MATLAB?, the waveform is obtained from the simulation result, the predicted power and the observed power are determined from the waveform. The predicted power determined is improve when it is compared to the observed power. The percentage Error which is calculated from the predicted power and the observed power described the large error associated with the system.},
      month = {July},
  }