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Projects: Projects for Investigator
Reference Number	NIA2_NGESO049
Title	Data-Driven Online Monitoring and Early Warning for GB System Stability (DOME)
Status	Started
Energy Categories	Other Power and Storage Technologies(Electricity transmission and distribution) 100%;
Research Types	Applied Research and Development 100%
Science and Technology Fields	ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation	Not Cross-cutting 100%
Principal Investigator	Project Contact No email address given National Grid plc
Award Type	Network Innovation Allowance
Funding Source	Ofgem
Start Date	01 July 2023
End Date	31 December 2024
Duration	ENA months
Total Grant Value	£400,000
Industrial Sectors	Power
Region	London
Programme	Network Innovation Allowance
Investigators	Principal Investigator	Project Contact , National Grid plc (100.000%)
	Industrial Collaborator	Project Contact , National Grid plc (0.000%)
Web Site	https://smarter.energynetworks.org/projects/NIA2_NGESO049
Objectives	"DOME will examine whether measuring on-line impedance spectra of a gird can give early-warning of emerging oscillations, and beyond that, whether it is possible to identify which aspects of which equipment should be re-tuned to damp those oscillations. This is a data-driven method that will not require owners/vendors of wind farms to disclose their internal control models. The analytical methods for mode identification and participation assessment have been created in previous academic research and so this study will assess whether these methods are capable of practical implementation. DOME is a desktop study that will use data gathered by transmission owners, example systems models and small-scale laboratory testing. The project will report on the viability of practical implementation and on how field trials could be conducted. This project will consist of the following five Work Packages (WPs) as listed below: WP1: Assessment of Measurement Noise It is important for the viability of the overall method to establish how a sufficiently large signal-to-noise ratio (SNR) can be achieved in practice. The first step is to determine the statistical properties of noise in measurements made on a real transmission network. Data made available by the Transmission Owners (TOs) from phasor measurement units (PMUs) will be analysed and a statistical noise model created. An assessment will be made of whether the noise model is influenced by the location of the measurement, the type of transducer and PMU or the operating point of the system (such as line flow). A crucial factor in the analysis is the update-rate or bandwidth of the PMU measurements and high bandwidth will be necessary. Deliverable: Short technical report on noise characteristics of PMU data. WP2: Optimal Injection Level The noise model from WP1 will be added to a simulation model of an example transmission network and an assessment conducted of the amplitude of signal injection (shunt current injection with a voltage response or series voltage injection with a current response) to obtain a response signal with a large enough SNR for further processing. Two types of measurement will be considered: injection and measurement at the same node (a diagonal term in the impedance matrix) and injection at one node and measurement at another (an off-diagonal term). Various conditions will be considered such as electrical distance between injection and response measurement, the number of system modes to be identified, and the damping factors of those modes. An important further factor to be considered is the consequence of exciting a system mode with the injected signal, albeit at low amplitude, and the need to trade-off SNR against avoiding mode excitation. The results will indicate the rating (in MVA) of the injection needed. An assessment will be made of the viability of creating the injection with a dedicate power electronic unit at a substation versus adding an additional control function to an inverter-based resource such as a battery energy storage unit or wind turbine. NREL will provide additional input on technical characteristics of megawatt-scale inverters used as injection devices. Deliverable: Short technical report on the rating required of a dedicated injection device and the viability of injection via existing third-party inverter-based resources. WP3: Location Choices for Injection Ideally, a full identification of the system and all of its modes would use injectionand measurement at every node. This is not feasible in practice: injection at every node would involve too much equipment but even measurement at non-injection nodes (for off-diagonal terms) may incur expense of very high accuracy time-stap alignment of measurements. This project will use a test system mode to examine how many injections and measurements are needed to find and identify the dominant modes of a system. It will consider how much reliance to place of prior knowledge of a system such as a known vulnerability to oscillation in a region of the network. DNV-GL will provide advice and guidance on representation of wind farms in system models. Deliverable: Short technical report on how many injection points and measurement points are needed to identify adequately the modes of a region of the GB transmission system or indeed the whole system. WP4: Verification Through WP1 to WP3, a series of system models will be built (noise statistics, injection equipment, injection locations) which will be combined into a final verification model. The intention is to create a test system that has similar characteristics to the GB system. The model will be used for a final set of verification and demonstration tests to verify how well one can expect to find mode participation factors from data-driven models. This model or a reduced version of it will be run in real-time on an OPAL-RT platform with a power-hardware-in-the-loop (PHIL) arrangement of a power amplifier and inverter to give reassurance that practical issues of measurement and control of the injection device are accounted for. Deliverable: A set of results verifying the work of WP1 to WP3. WP5: Global Engagement The project will draw conclusions on the size and extent of equipment required for a viable identification of system modes from measurement data. This will include the geographic reach obtained by injection and therefore how coverage is obtained for a national-scale system, the extent to which existing PMUs are sufficient for measurement, the extent to which root-cause can be identified as a function of measurement coverage. These conclusions will be disseminated though workshops and working groups of professional organisations (such as Cigre and IEEE). If the conclusions indicate that the method is indeed viable as a means to find, identify and analyse emergent oscillation to provide both early warning of problems and mitigation measures, a high-level plan for progressing to field trials will be created. Deliverable: Dissemination activities and report that outlines how a field trial of the method could be conducted. In line with the ENAs ENIP document, the risk rating is scored Low. TRL Steps = 2 (3 TRL steps) Cost = 1 (£400k) Suppliers = 1 (1 supplier) Data Assumptions = 2 Total = 6 (Low) " "This project aims to prove the viability of online monitoring and confirm whether a full implementation would provide benefits, including: Early Warning and Reduced Risk for Possible Oscillations: By continuously monitoring the power grid in real-time, online monitoring can detect the early signs of oscillations and alert grid operators before they escalate into a more significant issue. This can reduce the risk of system instability and potential blackouts.Reduced Renewable Curtailment: Online monitoring can provide grid operators with more accurate information about the behaviour of renewable resources such as wind farms and solar PV. This can help to reduce the curtailment of renewable energy, which occurs when the power grid cannot absorb all the renewable energy being generated.Reduced Model Dependency: Traditional methods for detecting oscillations rely on accurate models of the power grid and its components. Online monitoring can provide more accurate and up-to-date information about the power grids behaviour, reducing the reliance on models.Increased System Security: By providing grid operators with more accurate and timely information, online monitoring can increase the overall security of the power grid.Contributing Toward Net Zero Target: Online monitoring can help to integrate more renewable energy into the power grid, which is critical to achieving net-zero emissions targets.Deeper Understanding of the Root Cause of Oscillation Instability and Potential Solutions: Online monitoring can provide grid operators with more detailed information about the behaviour of the power grid, helping to identify the root causes of oscillation instability and potential solutions to address them. In summary, the implementation of online monitoring could bring several benefits, including increased system security, reduced renewable curtailment, and a deeper understanding of the behaviour of the power grid. " "The main objective of the DOME project is to investigate whether measuring online impedance spectra of a grid can provide early warning of emerging oscillations and whether it is possible to identify which aspects of the equipment should be re-tuned to dampen those oscillations. The project aims to develop a data-driven method that does not require the disclosure of internal control models by the owners/vendors of wind farms. The project consists of five work packages that will focus on different aspects of the methodology, including assessing measurement noise, determining the optimal injection level for obtaining a response signal with a large enough signal-to-noise ratio (SNR), identifying the location choices for injection, verification, and global engagement. Overall, the project aims to assess the viability of the proposed method for practical implementation and to determine how field trials could be conducted. The project also aims to draw conclusions on the size and extent of equipment required for a viable identification of system modes from measurement data, including the geographic reach obtained by injection and the extent to which existing PMUs are sufficient for measurement. The final outputs should include:  Deliverable from WP1 is a short technical report on noise characteristics of PMU data.Deliverable from WP2 is a short technical report on the rating required of a dedicated injection device and the viability of injection via existing third-party inverter-based resources.Deliverable from WP3 is a short technical report on how many injection points and measurement points are needed to identify adequately the modes of a region of the GB transmission system or indeed the whole system.Deliverable from WP4 is a set of results verifying the work of WP1 to WP3.Deliverable from WP5 is a set of dissemination activities and report that outlines how a field trial of the method could be conducted. "
Abstract	DOME will examine whether measuring on-line impedance spectra of a gird can give early warning of emerging oscillations, and beyond that, whether it is possible to identify which aspects of which equipment should be re-tuned to damp those oscillations. This is a data-driven method that will not require owners/vendors of wind farms to disclose their internal control models. The analytical methods for mode identification and participation assessment have been created in previous academic research, this project will assess whether these methods are capable of practical implementation. DOME is a desktop study that will use data gathered by Transmission Owners (TOs), example systems models and small-scale laboratory testing. The project will report on the viability of practical implementation and on how field trials could be conducted.
Publications	(none)
Final Report	(none)
Added to Database	01/11/23