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FACTS-based Schemes for Distribution Networks with Dispersed Renewable Wind Energy . Professor Dr. Adel M Sharaf ECE Dept., UNB Fredericton, NB, Canada. Outline. Introduction Motivations Sample Study System Modelling Novel FACTS-based Schemes Controller Tuning Digital Simulation
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FACTS-based Schemes for Distribution Networks with Dispersed Renewable Wind Energy Professor Dr. Adel M Sharaf ECE Dept., UNB Fredericton, NB, Canada
Outline • Introduction • Motivations • Sample Study System Modelling • Novel FACTS-based Schemes • Controller Tuning • Digital Simulation • Conclusions and Recommendations
Introduction • Wind is a renewable Green Energy source Load kinetic Energy Mechanical Energy Electrical Energy
Introduction • Wind is also a clean Abundant Source • No Emissions, No Pollutions carbon dioxide sulfur dioxide particulates
Introduction • Wind energy is a promising green energy and becomes increasingly viable &popular. • The cost of wind-generated electric energy has dropped substantially(6-7 per KWH). • By 2005, the worldwide capacity had been increased to 58,982 MW-Cost is $ 2000-2500/KW • World Wind Energy Association expects 120,000 MW to be installed globally by 2010.
Introduction Total installed wind power MW-capacity (data fromWorld Wind Energy Association)
Introduction • Wind Energy Conversion System (WECS) Using Large Squirrel Cage/Slip ring Induction Generators • Stand alone-Village Electricity • Electric Grid Connected WECS • Distributed/Dispersed/Farm Renewable Wind Energy Schemes • Located closer to Load Centers • Low Reliability, Utilization, Security
Motivations • Energy crisis • Shortage of conventional fossil fuel based energy • Escalating/rising cost of fossil fuels • Environmental/Pollution/GHG Issues • Greenhouse gas emission /Carbon Print • Acid Rain/Smog/VOC-Micro-Particulates • Water/Air/Soil Pollution &Health Hazards
Motivations • Large wind farm utilization is also emerging (50MW-250 MW) Sized Using Super Wind driven Turbines 1.6, 3.6, 5 MW Sizes • Many new interface Regulations/Standards/PQ Requirements regarding full integration of large distributed/dispersed Wind Farms into Utility Grid.
Motivations • Challenges for Utility Grid–Wind Integration. • Stochastically-Highly Variable wind power injected into the Utility Grid. • Increased Wind MW-Power penetration Level. • Low SCR-Weak Distribution/Sub Transmission/Transmission Networks - Mostly of a Radial Configuration - Large R/X ratio distribution Feeder with high Power Losses (4-10 %), Voltage Regulation Problems/Power Quality/Interference Issues. • Required Reactive Power Compensation & Increased Burden brought by the induction generator
Sample Distribution Study System L.L.1 L.L.2 T2 T3 N.L.L T1 Infinite Bus L.L.3 WECS I.M.
WECS-Decoupled Interface Scheme Uncontrolled Rectifier PWM Inverter I.G. Lf To Grid Cf DC Link Interface Wind Turbine Cself
System Description-wind turbine • Wind turbine model based on the steady-state power characteristics of the turbine • S -- the Total BladeArea swept by the rotor blades (m^2) • v -- the wind velocity (m/s) • ρ--air density (kg/v^3)
System Description tip speed ratio λ is the quotient between the tangential speed of the rotor blade tips and the undisturbed wind velocity C1=0.5176, C2=116, C3=0.4, C4=5, C5=21 and C6=0.0068
System Description – Wind speed • The dynamic wind speed model consists of four basic components: • Mean wind speed-14 m/s • Wind speed ramp with a slope of ±5.6 • Wind gust • Ag: the amplitude of the gust • Tsg: the starting time of the gust • Teg: the end time of the gust • Dg = Teg - Tsg • Turbulence components: a random Gaussian series
Wind Speed Dynamic Model The eventual wind speed applied to the wind turbine is the summation of all four key components.
MPFC-FACTS Scheme 1 • Complementary PWM pulses to ensure dynamic topology change between switched capacitor and tuned arm power filter • Two IGBT solid state switches control the operation of the MPFC via a six-pulse diode bridge
Tri-loop Error Driven Controller Modulation Index Voltage Stabilization loop Current Harmonic Tracking Loop Current Dynamic Error Tracking loop
DVR-FACTS Scheme 2 If S1 is high and S2 is low, both the series and shunt capacitors are connected into the circuit, while the resistor and inductor will be fully shorted • A combination of series capacitor and shunt capacitor compensation • Flexible structure modulated by a Tri-loop Error Driven Controller If S1 is low and S2 is high, the series capacitor will be removed from the system, the resistor and inductor will be connected to the shunt capacitors as a tuned arm filter
HPFC-FACTS Scheme 3 • Use of a 6-pulse VSC based APF to have faster controllability and enhanced dynamic performance • Combination of tuned passive power filter and active power filter to reduce cost Coupling capacitor Coupling transformer PWM converter Passive Filter tuned near 3rd harmonic frequency DC Capacitor to provide the energizing voltage
Novel Decoupled Multi-loop Error Driven Controller • Using decoupled direct and quad. (d , q) voltage components • Using The Phase Locked Loop (PLL) to get the required synchronizing signal- phase angle of the synthesized VSC-Three Phase AC output voltages with Utility-Bus • Using Proportional plus Integral (PI) controller to regulate any tracked errors • Using Pulse Width Modulation-PWM with a variable modulation index -m
Novel Decoupled Multi-loop Error Driven Controller • Outer-Voltage Regulator: Tri-loop Dynamic Error-Driven controller • The voltage stabilization loop • The current dynamic error tracking loop • The dynamic power tracking loop • Inner-Voltage Regulator: Mainly to control the DC-Side capacitor charging and discharging voltage to ensure almost a near constant DC capacitor voltage
Controller Tuning • Control Parameter: Selection/optimization • Using a guided Off-Line Trial-and-Error Method based on successive digital simulations • Minimize the objective function-Jo • Find optimal Gains: kp, ki and individual loop weightings (γ) to yield a near minimum Jo under different set-selections of the controller parameters
Digital Simulation • Digital Study System Validation is done by using Matlab/Simulink/Sim-Power Software Environment under a sequence of excursions: • Load switching/Excusrions • At t = 0.2 second, the induction motor was removed from bus 5 for a duration of 0.1 seconds; • At t = 0.4 second, linear load was removed from bus 4 for a duration of 0.1 seconds; • At t = 0.5 second, the AC distribution system recovered to its initial state. • Wind-Speed Gusting changes modeled by dynamic wind speed-Software model
Digital Simulation • Digital Simulation Environment: MATLAB /Simulink/Sim-Power • Using the discrete simulation mode with a sample time of 0.1 milliseconds • The digital simulations were carried out without and with the novel FACTS-based devices located at Bus 5 for 0.8 seconds
The frequency variation at the WECS interface without and with MPFC
The frequency variation at the WECS interface without and with DVR
The frequency variation at the WECS interface without and with HPFC
Comparison of Voltage THD with Different Compensation Scheme
Comparison of Steady-state Bus Voltage with Different Compensation Scheme
Conclusions • Three Novel FACTS-based Converter & Control schemes, namely the MPFC, the DVR, and the HPFC, have been Developed and validated for voltage stabilization, power factor correction and power quality improvement in the distribution network with dispersed wind energy integrated.
Recommendation • The Low-Cost MPFC-Scheme 1 is preferred for low to medium size wind energy integration schemes (from 600 to 5000 kW). • The DVR-Scheme 2 is good for Strong AC sub-transmission and distribution systems with large X/R ratio • The HPFC-Scheme 2 Active Power Filter & Capacitor Compensator is most suitable for Larger Wind-Farms with MW-energy penetration level (100 MW or above).
Recommendation • The schemes validated in this research need to be fully tested in the distribution network with real dispersed wind energy systems. • This research can be extended to the grid integration of other dispersed renewable energy. • Other Artificial Intelligence based control strategies can be investigated in future work.
Conclusions • A Validation Study of a unified sample study system Using the ATLAB/Simulink • A dynamic wind speed software model was developed to simulate the varying Random/Stochastic and temporal wind variations in the MATLAB/Simulink • Three Novel FACTS based Stabilization Schemes were validated using digital simulations • Novel Control strategies using dynamic Multi-Loop Decoupled Controllers were developed & Validated
Publications • [1] A. M. Sharaf and Weihua Wang, ‘A Low-cost Voltage Stabilization and Power Quality Enhancement Scheme for a Small Renewable Wind Energy Scheme’, 2006 IEEE International Symposium on Industrial Electronics, 2006, p.1949-53, Montreal, Canada • [2] A. M. Sharaf and Weihua Wang, ‘A Novel Voltage Stabilization Scheme for Standalone Wind Energy Using A Dynamic Sliding Mode Controller’, Proceeding- the 2nd International Green Energy Conference, 2006, Vol. 2, p.205-301, Oshawa, Canada • [3] A. M. Sharaf, Weihua Wang, and I. H. Altas, ‘Novel STATCOM Controller for Reactive Power Compensation in Distribution Networks with Dispersed Renewable Wind Energy’, 2007 Canadian Conference on Electrical and Computer Engineering, Vancouver, Canada, April, 2007 • [4] A. M. Sharaf, Weihua Wang, and I. H. Altas, ‘A Novel Modulated Power Filter Compensator for Renewable Dispersed Wind Energy Interface’, the International Conference on Clean Electrical Power, 2007, Capri, Italy, May, 2007 • [5] A. M. Sharaf, Weihua Wang, and I. H. Altas, ‘A Novel Modulated Power Filter Compensator for Distribution Networks with Distributed Wind Energy’ (Accepted by International Journal of Emerging Electric Power System)