| As global energy consumption keeps increasing every year, it’s becoming more apparent that we need to rely on more renewable energy sources as opposed to the limited ones like fossil fuels. To avoid a huge energy crisis in the event we deplete these limited natural resources, one of the best renewable energy alternatives is wind power. It’s a good choice among the renewable energy for its high security, high integration and high output efficiency. But with the rapid increase of the total installed capacity of wind farm, the contradictions between ‘high efficiency, high reliability and grid-friendly’ and the increases are growing. At the same time, because of the high nonlinearity of the wind power system and the randomness of the wind, the power output has large fluctuations and difficult to meet the power requirements of the grid. In addition, the popular maximum peak power tracking algorithm may cause supply-demand imbalance when the maximum wind power is more than required. Therefore, this paper focuses on the power control problem of wind turbine and conducts the following research:First,we design a rational power allocation strategy for the wind turbines based on multi-agent consensus algorithm to solve the allocation problem when there is a desired reference total power output of the wind farm. According to the cooperate control of each turbine, the scenario achieves a certain total power output, disperses computational burden into the distributed controllers and has a higher fault tolerance capacity than the centralized control framework.Second, we design two robust adaptive controllers for the given output power of the turbines, and prove the stability of the algorithm by using Lyapunov function. The algorithm has little dependence on the system model and strong robustness.Finally, we build numerical simulation experiments on the software platform to verify the control algorithm proposed in this paper. The results illustrate the effectiveness of the proposed method. |
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