A multi-scale model for day-ahead wind speed forecasting: A case study of the Houhoku wind farm, Japan

Wind power engineering is one of the environmentally safe areas of energy and certainly makes a significant contribution to the fight against CO2 emissions. The study of the air masses movement in the zone of wind turbines and their influence on the boundary layer of the atmosphere is a fundamental basis for the efficient use of wind energy. The paper considers the theory of the movement of air masses in the rotation zone of a wind turbine, and presents an analytical review of applied methods for modeling the atmospheric boundary layer and its interaction with a wind turbine. The results of modeling the boundary layer in the wind turbine zone using the STAR CCM+ software product are presented. The wind speed and intensity of turbulence in the near and far wake of the wind turbine at nominal load parameters are investigated. There is a significant decrease in the average wind speed in the near wake of the wind generator by 3 m/s and an increase in turbulent intensity by 18.3%. When considering the long-distance track behind the wind turbine, there is a decrease in the average speed by 0.6 m/s, while the percentage taken from the average value of the turbulent intensity is 7.2% higher than in the section in front of the wind generator. The influence of a wind turbine on the change in the temperature stratification of the boundary layer is considered. The experiments revealed a temperature change (up to 0.5 K), which is insignificant, but at night the stratification reaches large values due to an increase in the temperature difference in the surface boundary layer. In the long term, the research will contribute to the sustainable and efficient development of regional wind energy.

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Market Value and Agents Benefits of Enhanced Short-Term Solar PV Power Generation Forecasting

Manso-Burgos

Ribó-Pérez

Mateo-Barcos

et al. 2022

Machines

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Renewable energy sources such as PV solar or wind power are intermittent and non-dispatchable. Massive integration of these resources into the electric mix poses some challenges to meeting power generation with demand. Hence, improving power generation forecasting has raised much interest. This work assesses the market value of enhanced PV solar power generation forecasting. Then, we analyse the different agents present in the electricity system. We link the studied agents to the proposed market values based on both analyses. Improving the accuracy of RES forecasting has massive potential as the sector grows and new agents arise. It can have reactive values like reducing imbalances or proactive values such as participating in intraday markets or exercising energy arbitrage. However, accurate forecasting can also lead to opportunistic values that can be exploited by malicious agents if they are not adequately regulated.

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A multi-scale model for day-ahead wind speed forecasting: A case study of the Houhoku wind farm, Japan

Cited by 3 publications

References 38 publications

Physics-Informed AI Surrogates for Day-Ahead Wind Power Probabilistic Forecasting with Incomplete Data for Smart Grid in Smart Cities

Physics-Informed AI Surrogates for Day-Ahead Wind Power Probabilistic Forecasting with Incomplete Data for Smart Grid in Smart Cities

Modeling and Investigation of the Effect of a Wind Turbine on the Atmospheric Boundary Layer

Market Value and Agents Benefits of Enhanced Short-Term Solar PV Power Generation Forecasting

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