HIL Testing of Inverter Plant Controls for Grid QA
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Solution Overview
Problem
Existing quality assurance testing processes for inverter-based resource control systems, such as those used in grid-connected PV plants, do not comprehensively test the entire plant control system during factory acceptance testing (FAT) or site acceptance testing (SAT), leading to potential discrepancies and untested operating conditions.
Innovation Solution
A method and system utilizing a power systems modeling environment and hardware-in-the-loop (HIL) simulation to test the plant control system of an inverter-based resource. This involves generating an IBR model, using a PDC, test automation server, and the plant control system to simulate and test various operating conditions, including low voltage ride-through and frequency droop tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional factory acceptance testing (FAT) and site acceptance testing (SAT) processes are used, then testing can be performed with existing equipment and procedures, but the entire plant control system cannot be comprehensively tested and many operating conditions remain untested
Solution Approach 1:
The patent introduces a hardware-in-the-loop (HIL) simulation environment as an intermediary between the plant control system and the physical plant. This HIL environment includes a power system model that can simulate various operating conditions and grid scenarios that cannot be easily reproduced in physical testing. The HIL setup allows comprehensive testing of the control system without requiring actual plant operations under all possible conditions, thereby resolving the contradiction between reliable testing and adaptability to diverse operating conditions.
Solution Approach 2:
The patent implements comprehensive control system testing through HIL simulation before the actual plant is commissioned or before accepting delivery of control equipment. By performing preliminary testing in the virtual environment with the power system model, potential issues can be identified and resolved beforehand, ensuring higher reliability while avoiding the need for extensive on-site testing of all operating conditions later.
2Reliability
If comprehensive testing of all operating conditions is performed, then quality assurance is improved, but testing time and complexity increase significantly
Solution Approach 1:
The patent creates a virtual copy of the power system through detailed power system models that replicate the electrical network, generation assets, and load conditions. This digital model serves as a copy of the physical system, allowing comprehensive testing of the plant control system under various operating scenarios without requiring actual physical testing. The virtual environment can rapidly simulate different grid conditions, fault scenarios, and operating modes, dramatically reducing testing time while maintaining thoroughness.
Solution Approach 2:
The HIL simulation environment provides dynamic testing capabilities where the power system model can rapidly change operating conditions, simulate transient events, and adjust grid parameters in real-time during testing. This dynamic approach allows comprehensive coverage of various operating conditions without the time-consuming setup changes required in physical testing, resolving the contradiction between thorough testing and testing duration.
3Ease of operation
If manual testing procedures are used, then flexibility in test execution is maintained, but testing inconsistencies and human error increase
Solution Approach 1:
The HIL testing system incorporates automated feedback mechanisms where the power system model continuously monitors control system responses and compares them against expected behavior defined in the test specifications. The system automatically logs test results, generates reports, and can even perform self-validation, ensuring consistent and repeatable testing. This automated feedback loop maintains flexibility in test execution while eliminating human error and inconsistency, resolving the contradiction between ease of operation and measurement precision.
Data Source
AI summary
A method for testing a plant control system of an inverter-based resource (“IBR”) coupled to an electric power grid, the method comprising: using a power systems modeling environment implemented in an information system, generating an IBR model, the IBR model including an inverter control model, a generator model, a network solution model, and a model power meter; using a hardware-in-the-loop (“HIL”) simulation environment including the IBR model, a phasor data concentrator (“PDC”), a test automation server, and the plant control system, performing a test of the plant control system by iteratively: receiving measurements from the PDC and setpoints from the test automation server and sending the measurements and the setpoints to the plant control system; generating and sending an active power command and a reactive power command from the plant control system to the inverter control model; generating and sending desired active current and desired reactive current from the inverter control model to the generator model; generating and sending active and reactive currents from the generator model to the network solution model, the network solution model generating and sending a terminal voltage measurement to the generator model and the inverter control model, the network solution model generating and sending POI measurements to the model power meter; generating synchrophasors including electrical property information and sending the synchrophasors from the model power meter to the PDC; generating the measurements from the synchrophasors at the PDC; and, storing the synchrophasors as results of the test in the test automation server.