Regression model in the operation of wind turbines

Abstract

The manuscript presents linear regression models used to predict the amount of energy produced in a wind turbine. As part of the own research, data obtained from the SCADA program for the Enercon E-82 wind turbine was analyzed. It has been shown that it is possible to build a mathematical model to determine the amount of energy generated from the average wind speed. This method can be used to forecast the production volume and balance the energy system. This is important due to the increasing share of renewable energy sources. The application of the developed method in practice will facilitate and accelerate the implementation of the decision-making process in electricity generation systems, while reducing the risk of error. This model can also be used to make wind turbine repowering decisions.

Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System

“…If λ 1 (∞) = ∞, then in order to reach the maximum of criterion function g(x), only the following conditions are required: T 1 ∈ IFR, as well as the condition in formula (20).…”

“…The models developed in this study are based on data stored in the SCADA system and are appropriate for the analyzed wind turbine. This usefulness is due to the lack of analysis of other factors, such as terrain roughness, daytime temperature, and other disruptive factors [17][18][19][20], which may depend on the wind farm's location. To analyze the problem, we developed two linear regression models.…”

“…It is known that H(0 + ) = 0, hence h(0 + ) = β > 0. The fact that condition (20) is fulfilled indicates that α < 0 and function h(x) is increased from h(0…”