Harnessing Renewables in Power System Restoration

Transcription

1 Harnessing Renewables in Power System Restoration Dr. Wei Sun, and Amir Golshani Assistant Professor, EECS Dept. University of Central Florida (South Dakota State University) Panel: Cascading Failures: Advanced Methodologies, Restoration and Industry Perspectives 205 IEEE PES General Meeting, Denver, July 28, 205

2 2 Resilient Smart Grid Allows power disturbances to be instantly detected and handled with minimal customer impact. Real-time monitoring and reaction using high performance IT infrastructure: System to constantly tune itself to an optimal state SCADA to PMU (2 4 times/sec to times/sec) Rapid isolation and restoration without human intervention: Isolate parts of the network that experience failure from the rest of the system. Enables a more rapid restoration to reduce outage time.

3 3 Power System Restoration Developed Power System Restoration strategy (PSERC, EPRI projects): Partitioning power grid into islands Start up black start units Establish transmission lines Crank non-black start units Serving Loads Synchronize restored islands Connect with neighboring systems

4 4 Adaptive Restoration Tool G0 G7 Power system under restoration Real-time phasor measurement data System Data Base (sav,dyr, snap, xls,...) PMU PMU. G8 Cplex Python PSS/E G9 PMU PMU G PMU G2 PMU PMU G4 G3 G6 G5 PMU Restoration planning - Gen. start-up seq. - Line energ. seq. - Load pick up step - Dynamic reserve calc. - Voltage stability check - Renewable sources participation - Energy storages contribution MILP robust optimization Real-time security check - Load pick up step calculation - Lines switching and overvoltage check Generate restoration cases & run PSS/E Real-time Security check - Load pick up step calculation - Contingency analysis - Voltage stability margin calculation - Optimal load flow Dynamic Simulation New restoration planning - Gen. start-up seq. - Line energ. seq. - Dynamic reserve calc. - Connection to the neighboring island Restoration time (p.u.) PDC SEL-3373 t=0 Total Blackout Measuremet & record t=4 BSU is connected and first load/line to be energized t=9 First NBSU is connected t=5 Major contingency or equipment failure occurred

5 Case Study Test System IEEE 39-bus system with one BSU (G0) and 9 NBSUs (G-G9) G 7 The total generation capacity is 6,250 MW, and total active and reactive loads are 6,50 MW and,800 Mvar, respectively G 0 G 8 G 5 Frequency is regulated between 59.5 Hz and 6 Hz G 9 Voltage is maintained between 90% to 05% of nominal value The load was modeled as 25% constant current, 25% constant impedance, and 50% constant power G G 2 G 4 G 3 G 6 5

6 R R R 22.2R R R R R 00.3R R Voltage Stability Index Case Study Steady-State Performance 37 BUS 37 8 Load Flow and Bus Voltage Voltage Stability Index BUS BUS BUS BUS BUS BUS 225 BUS 2 8 BUS 8 7 BUS 7 27 BUS BUS BUS BUS BUS 3 6 BUS 6 39 BUS 39 9 BUS 9 8 BUS 8 5 BUS 5 4 BUS 4 6 BUS 6 7 BUS 7 3 BUS 3 7 BUS 0 BUS 0 2 BUS BUS BUS BUS BUS 34 9 BUS 9 20 BUS BUS BUS BUS BUS BUS Restoration Time (p.u.) 2 32 BUS

7 Case Study Dynamic Performance Pick up 92.5 MW and 35 MVar load at t=0 Switching Transient Voltage at Step 4 7

8 8 Renewable Sources Integration U.S. Department of Energy s goal: 20% wind by Traditional restoration excludes renewable sources: Cannot be dispatched like conventional generators Large scale wind farm penetration challenges: BSU or NBSU? Uncertainty and variability Dynamic reserve constraint Load pick up limit

9 9 Restoration Using Large-scale Wind Farm Robust optimization for planning stage: Wind profile Uncertainty set Impacts of budget of uncertainty Objective function: Maximizing the total load pickup and harnessing renewable sources

10 0 Testing Restoration Planning Strategy Probabilistic analysis: Wind Farm Speed Model Multi-Run Simulation Platform Matlab Environment Development of multi-run simulation tools using PSS/E power system software and Python language. Calculate Correlation Factor Matrix & Total Power Output Total Power Ouput Matlab Analytical Tools LHS Sampling Method Probabilistic load flow and voltage stability analysis. CSV File Format CSV File Format Study the effects of wind variability on power system operation during the restoration process. PSSE Environment Python Programming Environment Power system Static and Dynamic Analysis Tools

11 Coordination between PSH and Wind Pumped Storage Hydro (PSH) can be employed to address challenges associated with large scale wind integration. Compensating ramping events Coping with wind uncertainty Providing dynamic reserve Minimizing wind curtailment Reduced time of self-healing process

12 2 Coordination between PSH and Wind Using pumped-storage hydro: Store wind farm energy spillage at initial steps of restoration. Utilizing this energy to pick up load and expedite restoration process.

13 Power (p.u.) Wind farm power (p.u.) 3 Case Study Results Modified IEEE-39 bus with one 500 MW wind farm operated as a NBSU and two 80 MW PSH units 5 Deterministic vs. stochastic wind dispatching Robust Wind-PSH Coordination Wind forecasting value 0.5 Deterministic solution Stochastic solution Restoration Time (p.u.) Restoration time (p.u.) Forecasted power Case 2- scenario - scheduled power Case 3- scenario - scheduled power

14 4 Offshore Wind Farms Large offshore wind farms can be used as BSUs in restoration Supply energy and provide ancillary services, with voltage control and frequency regulation. VSC-HVDC Technology Can be connected to the weak power network and control the voltage and frequency Black start capability Connection to the neighboring grid, and provide enough inertia for self-healing process Connection to the onshore/offshore wind farm, and provide negligible inertia

15 5 Self-healing Process with HVDC Communication-based Strategy Perceive the change of the onshore grid frequency with the proposed inertia support control strategy. Real-time reliable communication links enable remote offshore wind farms to participate in primary frequency control. Communication-less Strategy The relationship between the WF-VSC output frequency and the onshore grid frequency is based on the change of the DC voltage. Using droop characteristics on both the onshore and offshore converters, and frequency variation on the offshore side is proportional to that on the onshore side. On-going collaboration with Dr. Nilanjan Chaudhuri at NDSU.

16 6 Conclusions Adaptive restoration tool is designed to introduce flexible restoration strategies that can be updated and guarantee power system security. Using wind farm as a BSU necessitate to activate inertial and droop control. Wind-PSH unit can mitigate wind variability and uncertainty during the self-healing process. Offshore-wind farm together with VSC-HVDC can be used to start up power system as sources after blackouts.

17 7 References Project funded by NSF ECCS-EPCN #408486, Collaborative Research: An Intelligent Restoration System for a Self-healing Smart Grid (IRS-SG) Further Information A. Golshani, W. Sun, and Q. Zhou, Coordination of Wind and Pumped-Storage Hydro Units in Power System Restoration, IEEE Transactions on Sustainable Energy, in revision. W. Sun, C. C. Liu, and L. Zhang, Optimal Generator Start-up Strategy for Bulk Power System Restoration, IEEE Transactions on Power Systems, vol. 26, no. 3, pp , August 20. N. Kadel, W. Sun, and Q. Zhou, "On Battery Storage System for Load Pickup in Power System Restoration," Proc. IEEE Power & Energy Society General Meeting, 204, National Harbor, MD, 27-3 July 204.