Abstract
This study was conducted to analyze the impact of surrounding environmental changes on the feedback gain and performance of a closed-loop wind farm controller that reduces the error between total power output of wind farm and power command of transmission system operator. To analyze the impact of environment changes on wind farm controller feedback gain, the feedback gain was manually changed from 0 to 0.9 with a 0.1 interval. In this study, wind speed and wind direction changes were considered as environment changes; it was found by simulation code that the wind farm controller gain is in inverse proportion to wake recovery rate. In other words, the feedback gain should be higher if the distance between upstream and downstream wind turbine is not sufficient to wake recovery. Furthermore, the feedback gain should be lower when the upstream wind turbine generates a relatively weak wake by operating above the rated wind speed. The wind farm simulation was performed using reference 5 MW wind turbines from the National Renewable Energy Laboratory (NREL), which are numerically modeled for each element so that wind farm power output and tower load can be calculated according to the variation of the power command by using a modified wake model with improved accuracy. All the simulations performed in this study were carried out to review the power output accuracy of wind farms, but only if the transmission system operator’s power command was lower than the available power of wind farm. In this study, the gain of the wind farm controller was applied differently depending on the wind speed and direction to consider benefits in terms of power and tower load, especially if the wake effect of the upstream wind turbine was rapidly transferred to the downstream wind turbine. Ultimately, a simple, but more effective, power distribution method was proposed for distributing power commands to wind turbines that constitute wind farms and the study indicated the need for controller gain adjustment based on surrounding environmental changes.
Highlights
Among power generation technologies that utilize renewable energy sources wind power generation is known to have relatively mature technology and high efficiency
The cost of energy generated by wind power, which can be calculated by dividing the sum of the capital expenditure (CAPEX) and operating expenses (OPEX) for twenty years by the total power production, has been continuously reduced as the technology evolves further and further
The performance of the proposed wind farm controller composed of a closed-loop was verified using an in-house wind farm simulation code
Summary
Among power generation technologies that utilize renewable energy sources wind power generation is known to have relatively mature technology and high efficiency. Previous wind farm controller studies have proposed various methods for active power control and verified the performance through simulation, they are limited in that they are using simple wind turbine models in their simulations. The recent study by Boersma et al proposed a wind farm controller that combines wake steering control algorithm and active power control techniques based on the MPC technique to improve the output of wind farms [23]. This study proposes a simple but effective method of wind farm control that is as simple as the well-known and already-applied method of proportional wind farm control and is as effective as closed-loop control in matching the power command by the TSO and reducing the tower loads. The wake model applied to the wake simulation code could be different from the wake generated in the actual environment because the model was developed assuming axial symmetry, etc
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