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Reference Number NIA2_NGESO017
Title Probabilistic planning for stability constraints
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 (Applied Mathematics) 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 ESO
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 January 2022
End Date 31 July 2023
Duration ENA months
Total Grant Value £382,000
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_NGESO017
Objectives This project will be completed across four work packages.WP1: Initiation & Review.WP2: Development & Reduced-scale Testing.WP3: Trialling on Full GB Model.WP4: Future Roadmap & Plan for ImplementationRisk AssessmentIn line with the ENAs ENIP document section 3.2, the risk rating is mostly scored Low (Score 1).TRL Steps = Score 2 (four TRL step from 3 to 7)Cost = Score 1 (£385,000)Suppliers = Score 1 (one supplier contracted)Data Assumption = Score 2 (scope known but will be refined during the project and appropriate standards and guidance will be identified during the project)  There is increasing uncertainty (e.g. load composition, line flows through interconnectors) and variability (e.g. wind speed) in power system operating conditions and parameters. The changes in the system operating conditions are happening faster, are more complex and are occurring in places where previously there were no issues. There is an expectation of more angular stability issues in the future due to reduction in synchronous generation and system inertia (e.g. as reported in the FES).Lack of automation in the assessment of stability means that the ESO has to prioritise boundary calculation due to computation time – analysis can be very time consuming and so is focussed on specific areas of the transmission network. For long term planning, power system analysis is currently carried out using deterministic approaches (e.g. selected background studies such as Winter Average Cold Spell – ACS demand or summer minimum demand). These technical studies do not consider all the variability and uncertainty associated with future energy scenarios which could have a significant impact on stability. In the future, this might lead to under- or over-estimated transfer capabilities and sub-optimal techno-economic solutions.In this project, we will explore, develop and test cutting-edge automated and probabilistic approaches for modelling of angular stability. This will enable year-round boundary capability calculation for stability accounting for a number of sources of variability and uncertainty and enabling ESO to consider the possible issues across the system. This work will be completed across four work packages:WP1: In this initiation work package, we will review academic literature, review the overlap and available learning from existing and ongoing work, and identify any policy and practical barriers that could affect possible implementation. In this work package TNEI will engage closely with ESO during the annual ETYS/NOA cycle to understand how new angular stability modelling methods will fit into the process and ensure the development of fit for purpose tools.WP2: In the development work package, we will trial the most promising methods on published test networks or reduced GB networks, to explore how different approaches perform in terms of e.g. accuracy, computation time. This will include methods for (i) screening the network to identify previously unforeseen stability issues, (ii) automated probabilistic evaluation of stability issues, (iii) quantify the uncertainty within the model and key model parameters, and (iv) development of a probabilistic model that captures correlations between demand and renewable generation.WP3: In the trialling work package, we will engage with the Network Development teams during the 2021/22 Electricity Ten Year Statement (ETYS) and Network Operability Assessment (NOA) planning cycle, testing the most promising methods onthe full GBET system models. The learnings, where applicable, will also be shared with other relevant ESO teams like the Operability teams.WP4: In the final work package, we will produce a plan for later implementing the tools into business-as-usual, and produce a roadmap for possible future changes (e.g. in regulation or planning standards) that could help deliver further value for GB energy consumers.Deliverables: These will include (i) innovative automated tools to possibly be used in the ETYS and NOA, to carry out automated probabilistic stability analysis for stability evaluation processes (e.g. probabilistic demand and renewable generation conditions model, method to screen networks for stability issues, probabilistic tool that supports automated power system analysis using Powerfactory) (ii) reports detailing the development and demonstration of these methods (iii) results from the models that are suitable for sharing with third parties (i.e. in NOA and ETYS publications), and (iv) a roadmap and evidence for further future development.  The objectives of this project are to explore the use of cutting-edge techniques (combining traditional power systems stability analysis and statistical modelling), and whether these allow the ESO to better understand the risk and uncertainty associated with angular stability on the GB electricity system. The result of this will be to produce automated tools to allow efficient stability evaluation for more snapshots and locations in the system.This could help the ESO to make more optimal economic decisions with respect to secure and stable operation of the system.
Abstract Continuation of the RIIO1 project - NIA_NGSO0036.In this project, we will explore, develop and test cutting-edge automated and probabilistic approaches for modelling of angular stability.This will enable year-round boundary capability calculation for stability accounting for a number of sources of variability and uncertainty and enabling ESO to consider the possible issues across the system. 
Publications (none)
Final Report (none)
Added to Database 02/11/22