A combined fuzzy gmdh neural network and grey wolf optimization application for wind turbine power production forecasting considering scada data

• A cost-effective and efficient wind energy production trend leads to larger wind turbine generators and drive for more advanced forecast models to increase their accuracy. This paper proposes a combined forecasting model that consists of empirical mode decomposition, fuzzy group method of data handling neural network, and grey wolf optimization algorithm. A combined K-means and identifying density-based local outliers is applied to detect and clean the outliers of the raw supervisory control and data acquisition data in the proposed forecasting model. Moreover, the empirical mode decomposition is employed to decompose signals and pre-processing data. The fuzzy GMDH neural network is a forecaster engine to estimate the future amount of wind turbines energy production, where the grey wolf optimization is used to optimize the fuzzy GMDH neural network parameters in order to achieve a lower forecasting error. Moreover, the model has been applied using actual data from a pilot onshore wind farm in Sweden. The obtained results indicate that the proposed model has a higher accuracy than others in the literature and provides single and combined forecasting models in different time-steps ahead and seasons.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Keyword

Fuzzy GMDH neural network

Grey wolf optimization

Power system

SCADA data

Wind power production

Cost effectiveness

Data acquisition

Data handling

Digital storage

Forecasting

Fuzzy inference

Fuzzy logic

Fuzzy sets

Onshore wind farms

Signal processing

Statistics

Wind turbines

Combined forecasting

Different time steps

Empirical Mode Decomposition

Forecasting modeling

GMDH neural network

Optimization algorithms

Supervisory control and data acquisition

Wind energy production

Fuzzy neural networks

Publication and Content Type

ref (subject category)

art (subject category)