Improvement of Power System Stability with Salp Swarm Algorithm and Fuzzy Type II
محورهای موضوعی : Electrical EngineeringPayam Rokni Nakhi 1 , Salman Amirkhan 2 , Javad Safaei Kuchaksaraei 3 , Fatemeh Hamedani 4
1 - Department of Power Engineering, Mahdishahr Branch, Islamic Azad University, Mahdishahr, Iran
2 - Department of Electrical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
3 - Department of Power Engineering, Savadkooh Branch, Islamic Azad University, Savadkooh, Iran
4 - Department of Power Engineering, Mahdishahr Branch, Islamic Azad University, Mahdishahr, Iran
کلید واژه: Wind Farms, Power System Stabilizer, Dynamic stability, Doubly-fed induction generator, Inter-area oscillations, wide- Area measurement system,
چکیده مقاله :
The use of renewable resources in the power system is increasing day by day. Wind energy is one of the forms of renewable energy sources that has been widely available to humans due to the common nature of renewable energy with low concentration (low density). Due to the constant changes of wind and as a result of changes in the power produced by wind farms, uncertainty in the power of the power system will become an integral part. Now, if the permeability of these resources increases, they can directly affect the dynamic stability of the system and the margin of stability of the system will change in power systems expansion, instability was often due to a lack of synchronizing torque. Issues such as the small perturbation stability of local oscillation modes and low-frequency inter-zone oscillation modes became apparent with a significant improvement in power system performance. The paper presents an optimal and coordinated power oscillation damper based on a wind turbine and power system stabilizer (PSS) to maintain the stability of power system and damp inter-area oscillations. The optimal and coordinated design of the PSS located at the generator site and the damper installed in the control section of the doubly-fed induction generator (DFIG) is defined as an optimization problem.
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