Comparison of supercapacitor storage system control methods for wind power smoothing

摘要

Recently, wind energy has shown the most significant increase in electric power systems among several other renewable energy sources. Due to the intermittent nature of wind, however, such growth has brought some concerns about Power Quality (PQ). This paper investigates three methods of controlling supercapacitor power to smooth and limit the wind power fluctuations injected into the grid. Methods based on the supercapacitor state of charge, the moving average filter and the Artificial Neural Network (ANN) are presented and compared according to their ability to enhance the grid PQ and voltage profile. The base test system consists of a full-converter based wind turbine connected to a modified IEEE 13 Node Test Feeder. Simulations were run using a real time digital simulator. Results show that all methods notably reduced wind power fluctuations and improved the grid voltage profile. Advantages and disadvantages of each control method are discussed.