go to top scroll for more

Projects: Projects for Investigator
Reference Number	NIA2_NGESO046
Title	STARTZ (Stability Requirements Calculation Toward Net-Zero)
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	PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 20%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 80%;
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 March 2023
End Date	31 August 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_NGESO046
Objectives	"This project, seeks to achieve three main objectives:Review the current methods of calculating system stability needs and identify areas of improvement.Perform the analysis on a sufficiently granular representation of the active and passive network components in the GB system. Apply automation and other necessary methods (machine learning) to manage additional computational burden of using detailed network representation. These objectives will be achieved by breaking down the problem into smaller tasks. As an example, the inertia requirement of the system will be treated as a sub-problem. Not only the total amount of system inertia is directly connected to the frequency stability and robustness of the grid, but also its specific location, especially in low inertia systems. Considering the possibility of procuring inertia as a service, the fundamental question would be where to optimally place synthetic/rotational inertia in the system. One approach to answer this question could be to calculate the electrical distance of all busbars from the Centre of Inertia (COI) of the system after a disturbance based on a Frequency Deviation Index (FDI). This would need to be repeated for every dispatch scenario. Based on the average improvement of the frequency nadir and RoCoF, a few locations can be identified where the system would benefit maximum from inertia services. A similar approach can be adopted for short circuit level. Metrics like Weighted Short Circuit Ratio (WSCR), Composite Short Circuit Ratio (CSCR) and Equivalent Short Circuit Ratio (ESCR) with interaction Factors (SCRIF) can be used to identify the system strength at a particular location when there is a strong electrical coupling between nearby inverter-based resources. Repeating this process for several dispatch scenarios would provide a range of SCR and would provide an idea of the system needs. The project will be delivered in three work packages: WP1 - Review of current methodsWP2 – Apply Alternate MethodsWP3 – Comparison with Existing Tool In line with the ENAs ENIP document, the risk rating is scored Low. TRL Steps = 1 (2 TRL steps)Cost = 1 (£400k)Suppliers = 1 (1 supplier)Data Assumptions = 2Total = 5 (Low) " Decarbonisation is bringing technical challenges that include the management of potential stability issues caused by the reduction in inertia and short circuit levels. In order to overcome potential stability problems while keeping economic and secure operation, NOA Stability Pathfinder projects have been looking to find and procure alternative sources of stability support. One key aspect to the NOA Stability Pathfinder project or any other future stability services procurement process is the calculation of future system stability needs. Overestimation or underestimation of system needs potentially represents, respectively, unnecessary costs for consumers or system vulnerability with increased risk of blackouts. The current methodology to calculate the system stability needs is based on several assumptions, criteria and simplifications that should be revised and improved following network evolving and energy landscape transition. Also, since a number of future generation and demand dispatches are considered, a higher level of automation in the calculation process is required. This project will review the current methods of calculating system stability and identify areas of improvement, performing the analysis on a sufficiently granular representation of the active and passive network components in the GB system. Bases on this analysis, It will apply automation and other necessary methods (machine learning) to manage additional computational burden of using detailed network representation. "The existing tool to compute system needs is a standalone process and is not integrated with any of the NOA tools or ETYS models. The calculations are based on empirical formulas. At the same time, the year-round analysis computes hourly generation and demand dispatches to identify the amount and the location of the services that need to be procured. These dispatches have a temporal variation which is captured through a time series analysis. The current tool is, however, not able to consider spatial uncertainty for inertia assessment, as the model is a lumped representation of the GB system. This project, therefore, seeks to achieve three main objectives: Review the current methods of calculating system stability needs and identify areas of improvement.Perform the analysis on a sufficiently granular representation of the active and passive network components in the GB system. Implement automation and other necessary methods (machine learning) to manage additional computational burden of using detailed network representation. "
Abstract	"This project will review the current methods of calculating system stability needs and implement automation and machine learning to calculate system stability needs for the GB network at a granular level. This project will: Review the current methods of calculating system stability needs and identify areas of improvement.Perform the analysis on a sufficiently granular representation of the active and passive network components in the GB system. Apply automation and other necessary methods (machine learning) to manage additional computational burden of using detailed network representation. "
Publications	(none)
Final Report	(none)
Added to Database	01/11/23