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| Content Provider | IET Digital Library |
|---|---|
| Author | Mahmoud, Tawfek Dong, Zhao Yang Ma, Jin |
| Abstract | This research presents a novel approach for optimal active and reactive power control using permanent magnet synchronous generator with fully rated converter (PMSG-FRC). The power output variations and wind energy intermittent performance create significant challenges for power system integration, operation, and control. A fast and reliable sensorless optimal wind speed (WS) control system-based extreme learning machines and complete ensemble empirical mode decomposition with adaptive noise is developed. Also, an approximate entropy-based complexity measure is used for online WS estimation. The fuzzy controller system is used for calculating the optimal wind turbine (WT) speed, power, and torque, and then adjusts WT by the optimal speed value. Moreover, the wind farm (WF) active and reactive power controller is utilised for obtaining the active and reactive power reference values for every region/feeder. The system is applied and integrated to power system grid by using IEEE standard models, and the speed of WT is adjusted by the required active power level and the estimated WS value to increase the maximum power capture from WF. The simulations results using different cases studies and power system voltage levels have confirmed the validity and accuracy of the proposed control algorithms for practical applications and demonstrated excellent performance for power system integration. |
| Starting Page | 474 |
| Ending Page | 485 |
| Page Count | 12 |
| ISSN | 17518660 |
| Volume Number | 12 |
| e-ISSN | 17518679 |
| Issue Number | Issue 4, Apr (2018) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-epa/12/4 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-epa.2017.0497 |
| Journal | IET Electric Power Applications |
| Publisher Date | 2018-01-02 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Acceleration Adaptive Noise Angular Velocity Control Approximation Theory Australia Complete Ensemble Empirical Mode Decomposition Control Engineering Computing Control of Electric Power System Entropy Entropy-based Complexity Measure Approximation FRC Fully Rated Converter Fuzzy Control Fuzzy Controller System Grid Connected Permanent Magnet Synchronous Generator Wind Turbine Hilbert Transform Hybrid Maximum Power Tracking System IEEE Standard Model IEEE Standards Integral Transforms in Numerical Analysis Integrated Optimal Active And Reactive Power Control Scheme Intelligent DIgSILENT Platform Interpolation And Function Approximation Knowledge Engineering Technique Learning in AI MATLAB Platform Maximum Power Point Trackers Numerical Analysis Online WS Estimation Optimal Control Optimal Wind Turbine Speed Calculation Optimal WT Power Calculation Optimal WT Torque Calculation Permanent Magnet Generator Power And Energy Control Power Generation Control Power Grid Power System Control Power System Grid Power System Integration Power System Operation Power System Voltage Levels Reactive Power Control Real WS Data Rotation Control Sensorless Machine Control Sensorless Optimal Wind Speed Control System-based Extreme Learning Machine Synchronous Generator Synchronous Machine Velocity WF Wind Energy Intermittent Performance Wind Farm Active Power Control Scheme Wind Farm Reactive Power Control Scheme Wind Power Plant Wind Turbine WS Control System-based Extreme Learning Machine |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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