Optimal STATCOM controller for enhancing wind farm power system performance under fault conditions

Harnessing wind energy for producing electrical power becomes vital and essential now a day in our communities. However the large penetration of wind farms into the electrical power grid affects the dynamic performance of grid especially during abnormal conditions. STATCOM FACTS device is employed for mitigation the voltage sage and improving power quality at the point of common coupling (PCC) where large scale wind power plants (WPP) are connected to grid during faults period. PI regulators with classical gain tuning are the most common procedure used for controlling the STATCOM performance. In this paper the particle swarm optimization (PSO) and ant colony optimization (ACO) as evolutionary methods are adopted to obtain flexible and reliable PI parameter tuning for cogging and improving STATCOM dynamic behavior during voltage sage occurrence. The main contribution of using STATCOM is to obtain an adequate fault ride through for wind driven doubly fed induction generator that can track the grid code requirements. So the impacts of deep voltage sage introduced to 9 MW wind farm DFIG and connected to 120 kV power grid are investigated by using Matlab/Simulink program. Results obtained show the effectiveness of the proposed PSO and ACO methodologies.

[1]  Jin-Woo Jung,et al.  Doubly-fed induction generator based wind turbines: A comprehensive review of fault ride-through strategies , 2015 .

[2]  Bibhuti Bhusan Pati,et al.  A review on optimization algorithms and application to wind energy integration to grid , 2015 .

[3]  Dionisio Ramirez,et al.  Use of STATCOM in wind farms with fixed-speed generators for grid code compliance , 2012 .

[4]  Nicholas A. Vovos,et al.  A Genetic Algorithm-Based Low Voltage Ride-Through Control Strategy for Grid Connected Doubly Fed Induction Wind Generators , 2014, IEEE Transactions on Power Systems.

[5]  Haibo He,et al.  Optimized Control of DFIG-Based Wind Generation Using Sensitivity Analysis and Particle Swarm Optimization , 2013, IEEE Transactions on Smart Grid.

[6]  Turan Paksoy,et al.  A novel hybrid approach based on Particle Swarm Optimization and Ant Colony Algorithm to forecast energy demand of Turkey , 2012 .

[7]  S. Iniyan,et al.  A review of technical issues on the development of wind farms , 2014 .

[8]  Mansour Mohseni,et al.  Review of international grid codes for wind power integration: Diversity, technology and a case for global standard , 2012 .

[9]  Omid Shariati,et al.  An overview on doubly fed induction generators′ controls and contributions to wind based electricity generation , 2013 .

[10]  Rabindra Kumar Sahu,et al.  A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems , 2015 .

[11]  S. Paramasivam,et al.  Experimental investigations on Ant Colony Optimized PI control algorithm for Shunt Active Power Filter to improve Power Quality , 2015 .

[12]  Omar Noureldeen,et al.  Stability improvement of fixed speed induction generator wind farm using STATCOM during different fault locations and durations , 2011 .

[13]  D V N Ananth,et al.  Fault ride-through enhancement using an enhanced field oriented control technique for converters of grid connected DFIG and STATCOM for different types of faults. , 2016, ISA transactions.

[14]  Fangxing Li,et al.  Adaptive PI control of STATCOM for voltage regulation , 2014 .

[15]  Rubiyah Yusof,et al.  Hybrid technique of ant colony and particle swarm optimization for short term wind energy forecasting , 2013 .

[16]  Mohamed Machmoum,et al.  Control of a wind energy conversion system equipped by a DFIG for active power generation and power quality improvement , 2013 .

[17]  Bharat Singh,et al.  Reactive Capability Limitations of Doubly-fed Induction Generators , 2009 .

[18]  Serap Ulusam Seçkiner,et al.  Design of wind farm layout using ant colony algorithm , 2012 .

[19]  Ramesh C. Bansal,et al.  Improving power quality of wind energy conversion system with unconventional power electronic interface , 2013 .

[20]  Olimpo Anaya-Lara,et al.  Impacts of High Penetration of DFIG Wind Turbines on Rotor Angle Stability of Power Systems , 2015, IEEE Transactions on Sustainable Energy.

[21]  Consolación Gil,et al.  Optimization methods applied to renewable and sustainable energy: A review , 2011 .

[22]  Shaotao Dai,et al.  Enhancing Low-Voltage Ride-Through Capability and Smoothing Output Power of DFIG With a Superconducting Fault-Current Limiter–Magnetic Energy Storage System , 2012, IEEE Transactions on Energy Conversion.

[23]  Enrique Acha,et al.  An Advanced STATCOM Model for Optimal Power Flows Using Newton's Method , 2014, IEEE Transactions on Power Systems.

[24]  Sadegh Vaez-Zadeh,et al.  Efficient fault-ride-through control strategy of DFIG-based wind turbines during the grid faults , 2014 .