English title

With increasing influence of variable speed wind turbines in power systems, the equivalent inertia of network is reduced. Accordingly, after the occurrence of disturbance in system, the frequency fluctuations in power systems increase. To overcome this problem, a supplementary control loop is added to the converter of the variable speed wind turbine in order to share the inertia of this type of turbines in the network. But the appropriate rate of this contribution depends on the amount of load and must be suitably changed based on the load. In this paper, a Takagi–Sugeno (T–S) fuzzy system is designed to determine the coefficient of the contribution of the variable speed wind turbine after the onset of disturbance, whereas sharing the maximum value of their inertia to compensate the reduced production in the network. However, the turbines do not pass their minimum speed limit while sharing the maximum value of inertia, causing another disturbance in the network. In the proposed method, first, by using Particle Swarm Optimization (PSO) algorithm, the optimal values of contribution proportional to the amount of load is obtained, while the constraint of minimum speed is not violated. In the next stage, the initial T–S fuzzy system is extracted from the optimal values of contribution by using subtractive clustering algorithm. Moreover, Recursive Least Square (RLS) algorithm is used to adjust the consequent part of the T–S system. The efficiency of the proposed method is demonstrated through the simulation in the variable amount of load.