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Reference Number NIA2_NGESO009
Title D3 - Data-driven Network Dynamic Representation for Derisking the HVDC and Offshore Wind
Status Started
Energy Categories OTHER CROSS-CUTTING TECHNOLOGIES or RESEARCH(Energy Models) 50%;
OTHER POWER and STORAGE TECHNOLOGIES(Electricity transmission and distribution) 50%;
Research Types Applied Research and Development 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 10%;
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 10%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 80%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Energy modelling) 100%
Principal Investigator Project Contact
No email address given
National Grid ESO
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 February 2022
End Date 31 March 2024
Duration ENA months
Total Grant Value £300,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
 
Investigators Principal Investigator Project Contact , National Grid ESO (100.000%)
  Industrial Collaborator Project Contact , National Grid plc (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA2_NGESO009
Objectives This project will look to undertake the following scope of work: WP1: Development of power electronic integrated benchmark power system with HVDC and Wind Farm (4 months)WP2: Development and validation of frequency-dependent power system model (8 months)WP3: Development and validation of model reduction technique (6 months)In line with the ENAs ENIP document, the risk rating is scored Low.TRL Steps = 2 (2 TRL steps)Cost = 1 (£300k)Suppliers = 1 (1 supplier)Data Assumptions = 4 Development of benchmark testing system in PSCAD/EMTDC Environment for complex power networks with integration of typical Power Electronics Based HVDC and Wind Generation systems.Development and validation of frequency-dependent power system model for identifying potential interaction risks.Development and validation of advanced model reduction technique to reduce the high-order frequency-dependent model to low-order power system one for system representation, to achieve a good balance between system accuracy and computational efforts via comprehensive data-driven simulations. This project will aim to bridge the current gaps, through the development of new models and technical reports which will mitigate risks when adding new power electronic equipment to the system. The final outputs will be: Developed Testing system and models in PSCAD/EMTDC environment.Technical reports for each WP.Final project reportInternational journal/conference publications.Dissemination event to share the outcomes of the project with stakeholders.
Abstract The GB electricity network is rapidly moving into a power electronic dominated one due to the installations of new HVDC and renewable generation systems. This brings considerable risks of control interactions between new power electronic equipment and existing ones. Manufacturers/owners of new power electronic systems have obligations to adjust their control parameters to minimise the control interactions. To carry out this research, they will need to have detailed grid dynamic models from National Grid ESO (NGESO). However, it is difficult for NGESO to share detailed system information due to system models complexity, confidentiality, and IP issues. This project will aim to address these issues by developing advanced tools for obtaining accurate grid dynamic models which dont reveal confidential system data and can be shared with outside stakeholders. 
Publications (none)
Final Report (none)
Added to Database 14/10/22