Wind Speed Forecasting for Designing Sustainable Wastewater Treatment Plants

The power output from a wind turbine depends on the accurate predictions of the wind speed. Wind speed forecasting is also critical for installing wind turbines in wastewater treatment plants to lower the energy costs and carbon emissions. We use hourly meteorological data between 2011 and 2019 to predict the wind speed in the city of San Marcos, Texas. We explore several regression models including recurrent neural network, long short-term memory, and ensemble model, and compare their prediction errors to identify the best-performing model. Our study contributes to precisely anticipating wind speed prior to installing wind turbines in wastewater treatment plant, so that it will help in balancing other types of electricity generation, such as coal, natural gas, geothermal, and hydroelectric units.