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Modeling and Control of Solar PVs for Large Grid Disturbances and Weak Grids DE-FOA-1987 SETO Advanced System Integration for Solar Technology (ASSIST) Program Award # DE-EE-0008771 PI: Lingling Fan Team: University of South Florida National Renewable Energy Lab

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Page 1: Modeling and Control of Solar PVs for Large Grid Disturbances … - Modeling and... · 2019-08-19 · Modeling and Control of Solar PVs for Large Grid Disturbances and Weak Grids

Modeling and Control of Solar PVs for Large Grid Disturbances and Weak Grids

DE-FOA-1987 SETO Advanced System Integration for Solar Technology (ASSIST) Program

Award # DE-EE-0008771

PI: Lingling Fan Team: University of South FloridaNational Renewable Energy Lab

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• USF’s DOE project goals, project tasks.• Milestone requirements of Year 1• Stakeholder engagement

• Initial findings from Task 2 and Task 3• Remarks

Outline

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Motivation: Industry Needs

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Objectives of this project: 1. Facilitate NERC Mod-033 event replication.2. Detection of IBR performance at the planning stage.

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• Modeling Gaps: Large-scale grid analysis adopts simplifications. Currently Many converter controls are ignored, including current control loops, voltage feedforward, phase-locked-loop (PLL). • Cannot replicate real-world inverter trip event due to sub-cycle overvoltage (current control loop plays role)• Cannot replicate real-world inverter trip event due to synchronization issues (PLL modeling)• Cannot replicate 7 Hz oscillation due to PV in weak grid (PLL, voltage feedforward all play roles)

• Goals: • Adequate modeling of current PV control technology (grid-following) à mod-033 model

validation• Multi IBR interaction and coordination, • Stability enhancement through supplementary IBR converter control.

• (Power system stabilizer for IBR)

Technical Objectives: modeling, coordination, stability enhancement

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Project Plan: Overview

5Tasks 1-4 focus on computer-based platforms.Tasks 5-8 focus on hardware experiment platforms.

Task 2: EMT models of PV systems

Task 3: Analytical models of PV systems.

Task 4: PHIL-based characterization of utility-

scale 1 MW inverter

Task 7: Coordination strategy of multiple PVs and DERs.

Task 9: Stability enhance module for PV inverters

Task 10: Control hardware implementation

Task 11: Inverter coordination hardware implementation

Task 6: EMT and analytical models for PV systems with grid interactions

BP1:

BP2:

BP3:

Task 5: Stakeholder engagement

Task 1: Stakeholder engagement

Task 8: Stakeholder engagement

BP1 focuses on single PV infinite bus system: subcycle overvoltage, low-frequency oscillations BP2 focuses on multiple IBR + grid topology: potential interactionsBP3 focuses on converter control: power system stabilizer for VSC

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• Goal 1: Adequate modeling of PV systems• Approaches:

• Develop detailed models with full dynamics.• Develop adequate simplified models suitable for the application scopes• Rigorous validation with EMT testbed validation and Physical Hardware-In-the-Loop (PHIL) tests,

including comparison of frequency domain responses, time-domain responses under various grid disturbance scenarios and weak grid conditions.

• Outcomes:• Analytical models of PVs with essential dynamics suitable for large grid disturbance study and

weak grid condition• Real-world events study:

• PLL reaction to transmission grid phase-to-phase fault; • PV inverter sub-cycle overvoltage due to grid voltage dip• 7 Hz oscillations due to transmission line tripping

Technical Objectives: modeling, coordination, stability enhancement

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• Goal 2: Effective coordination strategy development of multiple PV farms, energy storage systems, other energy sources, and grid.

• Approaches: • Analysis through a scalable analytical modeling frame with power grid and inverter-interfaced resources

considered. • Validation through EMT testbeds. We employ RT-Lab real-time digital simulators to develop EMT testbeds.

• Outcomes: • Large-scale power grid (including synchronous generators, network topology, inverter-interfaced

resources) analytical models for dynamic simulation and analysis• New insights of potential converter interactions will be obtained by bringing efficient and computing

techniques into modeling & analysis.– Ex 1: the effect of network topology on grid stability can be examined by treating power grid network as Laplacian graph

[Fan2017]; Ex 2: numerical small perturbation to extract linear models and further to apply various modular analysis tools (root loci [Fan2018], impedance [Miao2013]).

• Mechanism-based coordination strategy will be developed to avoid device interactions.

Technical Objectives: modeling, coordination, stability enhancement

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[Fan2017]: L. Fan, Interarea Oscillations Revisited, IEEE trans. Power Systems, vol. 32, no. 2, pp. 1585-1586, Mar. 2017.[Fan2018]: L. Fan and Z. Miao, “An explanation of Oscillations Due to Wind Power Plants Weak Grid Interconnection,” IEEE trans. Sustainable energy, Jan. 2018[Miao2012] Z. Miao, "Impedance-Model-Based SSR Analysis for Type 3 Wind Generator and Series-Compensated Network,“IEEE trans. Energy Conv., Dec. 2012

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• Goal 3: Control strategies for stability enhancement and hardware prototyping

• Approaches: • Mechanism based control design; EMT validation; hardware

prototyping and controller HIL tests.• Equipment requirement for control prototyping: National Instrument • Equipment requirement for HIL validation: HIL testbench (OPAL-RT).

• Outcomes: • Control strategies of PV stability enhancement for weak grid

operation• Hardware prototypes of controllers using NI sbRIO, cRIO and PXI

boards

Technical Objectives: modeling, coordination, stability enhancement

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RT-Labs at USF SPS

National Instrument sbRIO enabled power electronic testbed

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Features: PHIL experiments for rigorous validation

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CGI Forming 13.8kV/7 MVA Isolated Research Grid The CGI can be configured by NREL researchers to create an isolated Research

Grid. NREL researchers can selectively connect any combination of Power Devices to the Research Grid.

PHIL experiments to be carried out: 1. PV under large grid disturbance and weak

grid will be studied using CGI. 2. PV impedance model will be measured using

CGI3. PV and other resources (battery) respond to

fast changing grid conditions.

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Initial findings from Task 2 and Task 3 (EMT & analytical model of PV + infinite bus)

13Fig. 1 400-kW PV Farm EMT testbed in Matlab/SimPowersystms.

3rd NERC report 2019Key finding #3: Ac overvoltage/dc reverse currentKey finding #5: Inverter terminal voltage and POI voltage are vastly different

Understand why sub-cycle overvoltageWhy difference in POI and inverter voltageWhy dc reverse current

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Dq-frame Analytical model building

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Consider only GSC, dc-link and grid dynamics.

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• Grid strength matters (weaker, larger over-voltage)

• Grid voltage dip matters (0.1 pu dip)

• PV farm shunt capacitor involves in the dynamic mode.

• PV converter control structure/parameter matters.

Analysis results based on the analytical model

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PV output power is zero-momentary Cessation

Xg from 0.2 pu to 0.6 pu.

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EMT validation

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7Hz oscillations

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PPCC = 0:937, Xg varies from 0.5 to 0.96 pu, with each step 0.02 pu

EMT validation: grid strength reduces

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• Through this DOE project, USF would like to closely work with WECC on model validation.

• If you are interested to be in the industry advisory board, please contact me. • My contact info: • [email protected]• Tel: (813)974-2031• http://power.eng.usf.edu – update timely to have research papers posted.

Remarks

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