Sub-synchronous resonance damping using high penetration PV plant. (1st February 2017)

• Record Type: Journal Article
• Authors: Khayyatzadeh, M.; Kazemzadeh, R.
• Is Part Of: Mechanical systems and signal processing. Volume 84:Part A(2017)
• Page Start: 431
• Page End: 444
• Publication Date: 2017-02-01
• Subjects: Sub-synchronous resonance (SSR) -- Large scale PV plants -- SSR damping -- Teaching-learning-based-optimization (TLBO) algorithm and power oscillation -- FFT analysis; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.07.023
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The growing need to the clean and renewable energy has led to the fast development of transmission voltage-level photovoltaic (PV) plants all over the world. These large scale PV plants are going to be connected to power systems and one of the important subjects that should be investigated is the impact of these plants on the power system stability. Can large scale PV plants help to damp sub-synchronous resonance (SSR) and how? In this paper, this capability of a large scale PV plant is investigated. The IEEE Second Benchmark Model aggregated with a PV plant is utilized as the case study. A Wide Area Measurement System (WAMS) based conventional damping controller is designed and added to the main control loop of PV plant in order to damp the SSR and also investigation of the destructive effect of time delay in remote feedback signal. A new optimization algorithm called teaching-learning-based-optimization (TLBO) algorithm has been used for managing the optimization problems. Fast Furrier Transformer (FFT) analysis and also transient simulations of detailed nonlinear system are considered to investigate the performance of the controller. Robustness of the proposed system has been analyzed by facing the system with disturbances leading to significant changes in generator and power system operating point, fault duration time and PV plant generated power. All the simulations are carried out in MATLAB/SIMULINK environment. Highlights: The wide area control potential of PV farm in SSR mitigation is investigated. The Fast Furrier Transformer (FFT) analysis is used to determine the oscillatory modes. The TLBO algorithm has been used for managing the optimization problems.