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| Reference Number | NIA2_NGET0054 | |
| Title | Electricity Transmission Heat Effects, Resilience Measures to Manage Asset Lifecycles (THERMAL) | |
| 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 Electricity Transmission |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 March 2024 | |
| End Date | 30 September 2025 | |
| Duration | ENA months | |
| Total Grant Value | £1,670,000 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (100.000%) |
| Industrial Collaborator | Project Contact , National Grid Electricity Transmission (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGET0054 |
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| Objectives | The technical methods that will be used to address the problem outlined in Section 2.1 are centred around predictive modelling approaches. Global warming is increasing the prevalence of extreme temperature events; however, the extent, severity and durations of such events are not yet known. A probabilistic approach centred around historic data and projected future trends will be developed to postulate future extreme temperature scenarios. The performance of individual assets can be influenced by such extreme temperature events, with both absolute temperature and temperature transients having an influence on asset behaviour, asset performance, and asset aging. The system as a whole is inherently impacted by such events, with static, dynamic and cyclic line ratings requiring detailed evaluation to ensure an appropriate approach going forward. The long-term impacts of such events, and how they may influence failure modes of assets, will be considered through in-depth research into asset performance and degradation mechanisms. The degradation and potential failure of individual assets will have an adverse impact to the performance of the overall system; therefore, the criticality of individual assets can be considered as part of a risk-based evaluation of the wider networks and system as a whole. Specific focus will be given to HV overhead line (OHL) and transformers in open substations, which are known to be exposed and therefore susceptible to extreme temperatures. A combination of engineering simulations, physical models and data science will provide a probabilistic approach to asset aging and degradation.Whilst there has been modelling development to quantify component (mainly Lines and Cables) ageing due to temporary heating (from loading mainly), the analyses do not extend to rapid weather changes with simultaneous loading fluctuations.The models underpinning this project will use a combination of engineering simulation, climate data, physical models and data science to provide a probabilistic output which quantifies uncertainty and thereby enables rigorous risk-based decision making. To address the problem outlined in Section 2.1, a programme of four complementary projects has been developed. This programme will be delivered through a consortium of consultancies and academic institutions, bringing together industry leading knowledge, market leading modelling and analysis expertise and dedicated HV testing facilities. The consortium brings together organisations that are well known in the industry with pre-existing ties to relevant DNOs TNOs, and manufacturers. The four core projects are described below:Climate resilience planning for multi-hazard extreme weather events, and singularly extreme heat/cold and associated rapid temperature shifts. Project scopeIdentify key use cases, including relevant aspects of weather, and how system consequences can be quantified either in the form of cost or in terms of engineering standards, or specification of required technical performance.Develop understanding on required decisions or justifications associated with the project use cases. Confirm appropriate datasets for use, including spatial/temporal resolution, and the appropriate balance (as part of the use cases) between use of historic and climate model data.Review relevant industrial and research literature, and liaise with industry connections e.g., UK/non-UK networks, National Grid (US) etc. on energy industry best practices.Study therisk in future climate associated with at least one of the use cases, and how the risk changes from present day, to ensure the climate analysis is linked to network decision making.Develop detailed for analysis of the other two use cases, and for the application to supporting decision makingProject benefitsImproved planning for asset resilience, balancing reliability and cost for the benefit of customers.Case studies and protocols for application of general methods and datasets in climate science/resilience to energy network use cases.Predictive modelling of high voltage assets under extreme temperaturesProject scopeTo undertake a holistic review of HV network assets, categorising the performance impacts of extreme temperature events on HV asset types and documenting existing approaches / tools used to manage assets under such events. To develop a comprehensive HV network taxonomy, mapping known failure modes and degradation mechanisms associated with extreme temperatures against defined asset categories, thus enabling the quick identification of commonalities across a complex spatially distributed network of assets. The project will capture cross-discipline learning and experience through target stakeholder engagement with subject matter experts (SME) representing resilience teams, asset managers, operations, condition monitoring and network engineers. Creation of a rich data set, capturing both quantitative and qualitative information sourced from existing data sources, stakeholder interviews and the data outputs from other parallel projects. Identification of asset categories that present a risk to future network resilience under extreme temperature events, allowing a prioritisation and scoping of future modelling efforts. Project benefitsProvides a structured framework that allows extreme temperature scenario planning to be undertaken on a high volume of spatially distributed network assets. Provides an evidence-based approach for identifying and prioritising network assets that should be the subject of more detailed analysis, monitoring or modelling activities. Reassessing weather driven capacity limits through improved thermal models of individual network components and integrated framework for evaluation at substation, network and whole-system levels. Project scopeReassess existing methodologies and practices for determining static, dynamic and cyclic thermal ratings (STRs, DTRs and CTRs) of UK network components and formulate suitable improvements of their operational thermal models in the context of ongoing climate change and extreme heat events (e.g., include impact of solar irradiance and wind speed on loading limits of transformers in open substations).Validate and finely tune developed thermal models of different types of network components through targeted field-based measurement campaign (individual asset and substation level measurements). Integrate thermal models and assessed loading limits of individual network components into the analysis of the overall substation/network/system capacity limits. Such integrated methodologies are currently missing and are particularly important for evaluating conditions for the connection of much higher numbers of PV and wind generation systems, as well as increased demand from new electric vehicle and heat pump loads.Formulate final models, which should be derived for specific components using only basic or standard manufacturer specification. Include in the modelling approach evaluation of ageing on components" loading limits during the lifetime and consider improvements of empirical-based ageing models (e.g., impact on components" failure rates).Integrate models into the toolset for asset health monitoring and forecasting: operational for optimal event-response measures, and planning for cost-effective investment decisions.Project benefitsThe improved thermal models of network assets and their integration in the methodologies and tools for the assessment at substation, network and whole-system levels will have following benefits:To transmission and distribution system operators/owners and generating plant developers/operators: Increased system utilisation and efficiency, release of hidden/spare system capacity for the connection of both new generation and new load, deferred investment in system upgrading and system expansion, prevention of generation curtailment due to limited system capacity, improved operational performance, system resiliency and emergency response.To energy suppliers, aggregators and customers: Provision of efficient, affordable and secure power supply, offering higher system capacities for energy exchanges on the market, opening new opportunities for realising more flexible energy balancing and demand-side management services, as well as supporting electrification of road transportation and heating and cost-effective Net Zero transition.Quantifying and incorporating impact of equipment thermal stresses on network reliability by designing and testing resilience analysis framework (system level) and carry out informed experimentation on overhead conductors (asset level) Project ScopeConduct a comprehensive review of the impact of extreme heat on Overhead Line (OHL) assets and summarize the existing approaches employed by network operators to manage these assets during such events.Perform a detailed review of ageing and life prediction models currently in use for OHLs.Perform modelling and experiments on specific OHL conductor to assess the thermal effects on OHLs, considering both thermal stresses during extreme temperature conditions.Assessment and modelling of the aging risks faced by OHL conductors under extreme temperatures.Evaluate the vulnerability of OHL conductors by using analytical methods to produce fragility curves that reflect the asset failure probability under extreme heat conditions.Fragility-dependent resilience analysis: resilience analysis considering the produced fragility curves capturing both network and asset resilience.Project benefitsProvide a detailed resilience framework that assess the impact of extreme heat temperatures on OHL conductor asset under various extreme events scenarios for improved decision making.Optimised maintenance and longevity by understanding the ageing risks under extreme temperature scenarios.The outputs from these four projects will be captured within a common toolset, providing NGET with an interactive web-based solution to support their understanding and evaluation of future extreme temperature events. The project"s specific use-cases will be refined through project delivery, where outputs can be tailored for real-time decision-making, short to medium term forecast support to aid asset management and maintenance, and longer-term network investment planning decisions associated with reinforcement and resilience. This project aims to provide a means to forecast the impact of temperature events on asset behaviour and the implications for overall network performance, risk, and resilience. The ultimate objective of this work is to provide NGET with a better understanding of how future extreme temperatures events can impact the behaviour and performance of both individual assets, and the system as a whole. To achieve this objective the project will:Develop a probabilistic modelling approach to predict the prevalence of future extreme temperature events and rapid temperature shifts that have the potential to have an adverse effect on network assets and system behaviour. Provide a common extreme temperature weather dataset that can be used by supporting programmes to consider bounding conditions for asset degradation and failure modes. Review and consolidate existing studies evidence base into temperature impact on assets.Categorisation and catalogue network assets within a taxonomic structure to support the down selection and prioritisation of assets that will require greater evaluation. Undertake an evaluation of existing methodologies and approaches for determining the static, dynamic and cyclic thermal ratings (STR, DTR & CTR) of UK network components, and identify potential improvements of their operational thermal models. Validate and finely tune developed thermal models of different types of network components through targeted field-based measurement campaign. Integrate thermal models and assessed loading limits of individual network components into the analysis of the overall capacity limits at substation level, local network level, and system level.Experimental/modelling approach to understand thermal stresses of overhead line conductor under extreme temperature conditions and combine these findings within existing engineer models and data science approaches to provide a risk-based evaluation of OHL conductor asset. Provide a resilience framework that assess the impact of extreme heat temperatures on OHL conductor asset under various extreme temperature scenarios. Presentation of study findings within a web-based toolset acting as a framework that can be built upon, integrated to existing platforms, or added to in subsequent projects. | |
| Abstract | This project aims to provide a means (tool structure) to forecast the impact of temperature events on asset behaviour and the implications for overall network performance, risk and resilience. Currently, the absolute strain that extreme heat or rapid temperature changes poses on critical infrastructure is not entirely known. Yet, we expect more multi-faced weather events such as severe heat and cold waves with undulating characteristics which pose a threat to normal operation of electrical components especially within aged equipment. Currently, no method exists to explicitly outline how service delivery is affected, neither is there any matrix to fully assemble resilience against multi-hazards weather extremes. This project will inform NGET"s and SSEN-T"s related RIIO investment planning, in-year planning and improve real time network decision making. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 18/09/24 | |
