Distributed Renewable Energy Sources Integration and Smart Grid Control

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1 Distributed Renewable Energy Sources Integration and Smart Grid Control Jianwu Zeng Power and Energy Systems Laboratory Department of Electrical & Computer Engineering University of Nebraska-Lincoln URL: pesl.unl.edu May 04, 2015

2 Background Smart Grid Sustainability High efficiency Reliability Flexibility 3M Solution [1] Distributed Renewable Energy Sources Integration [1] Grid Control 2

3 Background Outline Distributed Renewable Energy Sources Integration Two Stage DC-DC-AC One Stage DC-AC DC-DC Converter DC-AC Inverter Grid Control DC Microgrid Scheduling Nonlinear Control Short-time Wind/Solar Power Prediction 3

4 Background Distributed RES Integration Two stage: DC-DC-AC Source m P m Source 2 P 2 Source 1 P 1 One-stage: DC-AC Source m Source 1 P m Source 2 P 2 P 1 DC-DC DC Link Grid DC-AC Grid Functions of converter: 1. Maximum power point tracking (MPPT) 2. Regulate voltage DC-AC 4

5 Background Traffic Signal Light System Traffic Poles at One Intersection Lincoln, NE 418 intersections (2009) 137,940 kwh/month $2.5 million (15 years) Optimally utilizes the existing infrastructure 5

6 Background Traffic Signal Light System A Roadway Wind/Solar Hybrid Power Generation and Distribution Systems (RHPS) Towards Energy-plus Roadway RHPS Microgrid Utility Grid Substation Unit Circuit Breaker Transformer Sponsor: Department of Transportation (DOT) Federal Highway Administration 6

7 Background Traffic Signal Light System Unit: Energy-plus Roadway/Traffic-Signal Light (EPRTL) Wind Turbine Generator PV Panel AC,60 Hz AC Load AC-DC DC Power Electronics Interface LPMC Roadway Microgrid AC,60 Hz Control Signals from SPMC Test site: Hw2 & 84 th ST DC Load Cabinet DC Battery Annually (1 intersection) Production:9,000 kwh Consumer: 4,000 kwh 15 years in Lincoln Save $1.5 million 400 intersections Reduce 12,000 tons of CO 2 7

8 Mechnical power (W) PV panel power (W) Background Challenges of Converter Design 1. Integrating different RES m/s 8 m/s 9 m/s 11 m/s MPP Multiple inputs 200 W/m W/m W/m W/m 2 MPPs Rotor speed (rpm) WTG 2. High power density 3. High voltage conversion ratio 4. High efficiency 5. Deal with intermittence of RES Cost-effective Soft-switched Bidirectional Isolated Multiport Converter PV panel voltage (V) PV panel Compact Isolated: transformer Soft-switching Energy storage Distributed Renewable Energy Sources Integration 8

9 Outline Distributed Renewable Energy Sources Integration Two Stage DC-DC-AC DC-DC Converter 9

10 Distributed Renewable Energy Integration Cost-effective Isolated Multiport DC-DC Converter PV 2 N v 3 i 2 L 3 i 3 D 3 v 2 D 1 i 1 C v 1 3 PV 1 C 2 WTG C 1 L 1 S 3 S 2 S 1 v cs PWM PWM v i 3 PWM 2 1 v i 1 1 v 2 2 i3 MPPT 3 Controller L 2 D 2 i p D s1 D s2 TX v p v s n=n p /N s C s Source m D s4 P m Source 2 P 2 L v dc P o C R D s3 Grid Simple topology: m input port, m switches J. Zeng, W. Qiao, L. Qu, and Y. Jiao "An isolated multiport DC-DC converter for simultaneous power management of multiple different renewable energy sources," IEEE Journal of Emerging Selection Topics in Power Electronics, vol. 2, no. 1, pp , Mar Source 1 P 1 DC-DC DC Link DC-AC 10

11 Distributed Renewable Energy Integration ZCS Isolated Multiport DC-DC Converter Pm i m vsm P2 P1 i 2 L 2 D 2 v s2 C m C 2 L m v s1 i rm L rm C 1 S m i 1 D m i r2 v ds2 L r2 L 1 S 2 D 1 v ds1 i r1 L r1 S 1 LCL-Resonant Circuit v C r L p1 L p L' p i p i T TX L C M V dc R L i M v cs v p C s n=np:ns D s1 D s4 D s2 i Ds2 D s3 P out P out Zero-current Switching (ZCS) m ports, m switches Low voltage stress High efficiency 11

12 Mode 1 v 1 i 1 Distributed Renewable Energy Integration ZCS Isolated Multiport Bidirectional DC-DC Converter PV P 1 P v bat P 2 V * dc e v v dc v 1 i bat C 2 MPPT Controller Saturation C 1 i 1 L 1 L 2 S 2 PWM 3 t on T S 3 PWM2 Voltage PI PWM1 i PWM generator I * bat L r S 1 v C r i p L m i m v cs d 3 d 2 i bat I * bat> 0 1 K 2 I * bat 0 i bat L p v p TX D s1 i T2 vt2 n=np:ns C s D s4 Discharge PI Charge PI D s2 d 2 d 3 v dc D s3 P out C P out Power flows PV Panel Battery Mode 1 Mode 1: Daytime Mode 2: Night Mode 3 Mode 1 Mode 2 Load Mode 3: Battery is unavailable J. Zeng, W. Qiao, and L. Qu, An isolated three-port bidirectional dc-dc converter for PV systems with energy storage, IEEE Trans. Industry Applications, accepted for publication. 12

13 Power (W) Output power of PV panel (W) Wind speed (m/s) Output power of PV panel (W) Distributed Renewable Energy Integration MPPT Results 7 6 WTG :00 4:00 5:30 6:00 6:30 PV Time (sec) Ideal MPP Measurement Voltage (V) PV 2 3:00 4:00 5:30 6:00 6: PV curve Operating points Time (sec) Voltage (V) 13

14 Efficiency (%) Distributed Renewable Energy Integration Soft-switching Efficiency i r1 (5A/div) v ds1 (20V/div) i r2 (1A/div) vds2 (20V/div) Time (2 us/div) 87 ZCS 86 Hard switching Soft switching Output power (W) Soft-switched converter has higher efficiency than that of hard-switched converter 14

15 Mode 1 Distributed Renewable Energy Integration Bidirectional Power Flow PV Panel PV p 1 MPPT Three-port isolated DC-DC Converter Battery p 2 p out Load Operating points Battery Mode 1 Mode 3 Mode 1 Mode 2 Load MPP p W 40W p W 40W p W v dc 50.18V v 1 i V 2.67A i bat 0.87A Charge battery 20W v 0W 1 4V 12V 20V i 1 p 1 v 1 20W v 0W 1 4V 12V 20V Time: (10 us/div) p 1 : (5 W/div) v dc : (10 V/div) i 1 : (1 A/div) i bat : (0.5 A/div) Time: (2 ms/div) i 1 : (1 A/div) p 1 : (5 W/div) v 1 : (2 V/div) 15

16 Mode 1 Distributed Renewable Energy Integration Bidirectional Power Flow PV Panel v dc PV p 1 MPPT Three-port isolated DC-DC Converter Battery 49.91V p 2 18W p out Load p 1 Operating points 13.33W Battery Mode 1 Mode 3 Mode 1 Mode 2 18W p 1 Load MPP 14.5W p 1 v 1 i bat i W 14.28V 2.67A 0.92A 10W Discharge battery 2W v 1 4V 12V 20V i 1 p 1 10W v 2W 1 4V 12V 20V v 1 Time: (5 us/div) v dc : (10 V/div) p 1 : (2 W/div) i bat : (1 A/div) i 1 : (0.5 A/div) Time: (2 ms/div) i 1 : (0.5 A/div) p 1 : (2 W/div) v 1 : (2 V/div) 16

17 Outline Distributed Renewable Energy Sources Integration One Stage DC-AC DC-AC Inverter 17

18 Distributed Renewable Energy Integration PV ZVS Isolated Multiport DC-AC Inverter Port 1 i 1 S 1 S 2 C 1 v Port 2 1 i bat i 2 r b C 2 v 2 MPPT Controller * v 1 C b v bat PWM1 PWM2 PWM generator PWM3 i p S 42 L k TX Ns L L m v p 2 Np v 1 IVC d 1 OVC v o Source m Source 1 P m Source 2 P 2 P 1 S 3 d 3 DC-AC Ns S 52 i o L o C o Port 3 R L v o S 41 S 51 PWM 41 ~PWM 52 PWM d 4 sign( ) generator d 5 1 * v o Grid Sine wave Zero-voltage Switching (ZVS) Single-Stage: high efficiency No electrolytic capacitor (<15 years) PV panel: 25 years J. Zeng, W. Qiao, and L. Qu, "An isolated multiport single-stage microinverter for the distributed power generation systems," IEEE Trans. Industrial Electronics (in review) 18

19 Distributed Renewable Energy Integration ZVS Output voltage v ds2 (20V/div) PWM2 PWM51 PWM41 ZVS v ds3 (50V/div) PWM3 PWM3 v o (100V/div) AC voltage, 60 Hz 19

20 Smart Grid Control Utility Grid Substation Circuit Breaker Transformer RHPS Microgrid Standalone Mode Grid-connected, Island Mode DC Microgrid Scheduling 20

21 Outline Grid Control DC Microgrid Nonlinear Control 21

22 Nonlinear Control for DC Microgrid System DC Microgrid System DC Bus DC Bus Source #1 Source #n P 1 DC-DC Converter #1 DC-DC Converter #n P n P 2 DC-DC Converter #2 CPL #1 CPL #m Inverter/ Rectifier Utility Grid Source #2 Source v DC/DC Converter CPL P=Const. DC/DC Converter Control Signal Output Voltage Controller Resistor dv/di >0 Load Output Voltage Reference Voltage Constant Power Load (CPL): cause instability due to its negative incremental impedance dv/di <0 22 i

23 v Nonlinear Control for DC Microgrid System Interconnection and Damping Assignment Passivity- Based Controller (IDA-PBC) Energy Contour Hamiltonian Energy Function H 1 1 ( x ) 2 x L 2C x Desired Energy Function 1 1 Hd ( x) x x x x 2L 2 Energy Reshape * x1 r1 1 d r1 x1 x L L C * x2 1 (1 d) x1 C r2 L r * 2 * C o -- current point 2 2 E 1 x C 2 CP x 2 * -- desired point C 1 E i i - - v E r1 ( P / E i) d v J. Zeng, Z. Zhang, and W. Qiao, "An interconnection and damping assignment passivity-based controller for a DC-DC boost converter with a constant power load," IEEE Trans. Industry Applications, vol. 50, no. 4, pp , Jul./Aug L r 1 ' S D C v r 2 ' P CPL

24 Inductor current (A) Nonlinear Control for DC Microgrid System Experimental Results r 1 ' r 1 ' r 1 ' = 0.25 = 0.42 = Time (s) 24

25 Outline Grid Control Scheduling Short-time Wind/Solar Power Prediction 25

26 Short-term Wind/Solar Power Prediction X t Short-term solar power prediction (SPP) (1) X t Normalization (Sigmoid Function, ( m 1) X y t t Transmissivity) ȳ t DOY TOD Feature Representation x t Prediction yˆ ( t h) (SVM, AR, Denormalization yˆ ( t h) RBFNN) DOY TOD Normalization: transmissivity yt t Rt y t : Time series of ground radiations R t : Time series of extraterrestrial radiations R t y t J. Zeng and W. Qiao, "Shot-term solar power prediction using a support vector machine," Renewable Energy, vol. 52, pp , Apr

27 Short-term Wind/Solar Power Prediction Short-term wind power prediction (WPP) Pˆ v y Normalization Power Curve Preprocessing vˆ Feature Representation Denormalization Wind speed-to-wind power conversion x x b N D t, j i, j i h i 1 j 1 a i yx ˆ( t ) x x N D * t, j i, j ( i i ) h b (ε-wsvm ) i 1 j 1 ai WSVM Wavelet Support Vector Machine (WSVM) ŷ x (LS-WSVM) J. Zeng and W. Qiao, "Shot-term wind power prediction using a wavelet support vector machine," IEEE Trans. Sustainable Energy, vol. 3, pp , Apr

28 Short-term Wind/Solar Power Prediction SPP Results SVM > Neural Networks > Auto regression 28

29 Short-term Wind/Solar Power Prediction WPP Results WSVM achieved the least prediction error 29

30 Summary Distributed Renewable Energy Sources Integration Two Stage DC-DC-AC One Stage DC-AC Three novel converters High efficiency Low cost MPPT Grid Control DC Microgrid Scheduling Energy-based control SVM SPP WSVM WPP 30

31 Summary Other Experience Fault Detection and Diagnosis Wind Energy Conversion Systems (ACC 2013) Mechanical, Transmission System (M.S. Thesis) Control Sensorless Control: PV system (ECCE 2011) Direct Torque Control: PMSM (ECCE 2014) Computational Intelligence Neural Networks (PESGM 2011) Rough Set (M.S. Thesis) 31

32 Future Research Electric Power & Energy Generation Systems Sustainable Energy Energy Generation Energy Integration Energy Efficiency Energy Storage Systems Energy Hub High Voltage Large Current Fault Detection & Diagnosis Computational Conditional Monitoring Intelligence Big Data Distributed Control Intelligent Control Energy Hub Smart Grid Control & Optimization Control Vehicle to Grid (V2G) Grid to Vehicle (G2V) Motor Drive Electric Vehicle Systems High Frequency New Materials (SiC, GaN) Biomedical Applications Power Electronics 32

33 Teaching Power & Energy Power Electronics Electric Power Systems Electronics Controlled Electric Drives Renewable Energy Systems Advanced Topics in Power Electronics Control Linear Systems Digital Signal Processing Control of Electrical Power Conversion Systems Real-Time Computer Control Systems Computational Intelligence Computational Intelligence in Power and Energy Systems 33

34 Teaching Power & Energy Power Electronics * Electric Power Systems Renewable Energy Systems Advanced Topics in Power Electronics ** Control Electronics * Controlled Electric Drives * Teaching experiences * TA (including labs) ** Lecture Control Systems Digital Signal Processing * Control of Electrical Power Conversion Systems Real-Time Computer Control Systems Computational Intelligence Computational Intelligence in Power and Energy Systems ** Students Mentoring Andrew He (decoupling control) Jackson Olson & Brandon Guenther (Wireless communication) Xi He (converter design, C, DSP) 34

35 Thanks! 35

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