The complexity in the power system is expected to continue to increase, and power system planners need better information about the risk exposure and vulnerability of the power system. This information is necessary to ensure an acceptable level of security of electricity supply for decisions on all planning horizons: from short-term operational planning to long-term asset management and system development. The objective of the project is to develop knowledge and methods for long-term prognosis of the risk to reliability of supply. New methods should be able to inform decisions in both power system asset management and system development in the Nordic power system in a consistent manner. Specifically, the methodologies will account for 1) the condition and spatial location of power system components, 2) the long-term development and uncertainties in risk-influencing factors, and 3) interdependencies between the asset management and system development planning horizons.
One key challenge the project will have to overcome is to bridge the gap between individual assets and the power system in analyses of reliability of supply. There is currently a lack of consistency between risk analysis carried out at an asset level and at a power system level: The former focuses on a single asset or component in the power system (e.g. a transformer station) but does not properly account for its importance in the power system for the reliability of supply. The latter takes a broader view of the power system but usually neglects how the condition of individual components influences their probability of failure and how this contributes to the overall power system risk with regard to reliability of supply.
In the initial phase the project has focused on power transformers, which are large and complex components that are having a central role in the power system. A first case study has used as its starting point a model previously developed by SINTEF for the overall technical condition of individual transformers. This model has previously been applied for asset management purposes, but in this case study it is integrated with a method for reliability of supply analysis. By using real data for a selection Norwegian transformers, it was shown that reliability of supply is influenced by component condition only to a limited extent when the condition is as good as for the Norwegian transformers. If the condition deteriorates, however, it is found that reliability of supply suffers substantial reductions.
Two new case studies with the transmission system operator (TSO) partners in the project have also been defined during 2021: The case study with Statnett (who is the TSO of Norway) aims to provide better information about the duration individual transformers may be out of service after failure (or in other words, their outage time). The case study with Landsnet (who is the TSO of Iceland) aims to capture the effect of the asset management strategy on reliability of supply. This modelling can be further integrated in Landsnet's long-term grid development studies and thus better inform grid development decisions.
Through the case studies, methodology will be developed targeted towards concrete applications that are relevant for the TSO partners. In the case study with Statnett, a model for transformer outage times is already under development. It is further planned how this model can both i) be integrated in Statnett's reliability of supply analyses and ii) be used to improve Statnett's maintenance planning methodology.
More advanced modelling of outage times is also an example of how the methodology that is developed can provide better information about the factors that influence risk to reliability of supply. Location and technical condition are examples of such risk-influencing factors. Better knowledge about these factors and their uncertainties will provide a more complete risk picture. More specifically, it has the potential to help system planners to identify vulnerabilities associated with power supply interruptions with severe consequences to reliability of supply. For example, better knowledge about component outage times can make it possible to identify vulnerabilities associated with transformers that could have particularly long outage times after failure.
Ultimately, better information about the risk to reliability of supply and how it may develop over time helps ensuring the security of supply, while enabling the power system to continue integrating more variable renewable energy.
In an increasingly complex and changing power system, system planners need information about the risk exposure and vulnerability of the system. This information is necessary to ensure an acceptable level of security of supply for decisions on all planning horizons: from short-term operational planning, mid-term asset management, and long-term system development. The objectives of this project is to develop methodologies for long-term power system risk prognosis that account for 1) the condition and spatial location of power system components, 2) the long-term development and uncertainties in risk-influencing factors, and 3) interdependencies between the asset management and system development planning horizons.
To do so, one must close the gap between asset level and power system level risk analysis: The former traditionally focuses on a single power system component but does not fully account its importance in the power system for the security of supply; the latter takes a broader view but usually neglects how the condition of individual components influences the overall power system risk. One key challenge is that component condition and other risk-influencing factors are associated with uncertainties, which develop with time. The project seeks to quantify and propagate these uncertainties in the risk prognosis.
Better knowledge about the contribution of risk-influencing factors, their uncertainties and interactions will provide analysts and decision makers with a more complete risk picture. The results have the potential to help system planners to identify vulnerabilities associated with severe consequences to security of supply. It is also anticipated that the knowledge and methodologies developed in the project can be used to inform asset management and system development decisions. By quantifying the long-term risk to security of supply in monetary terms, the methodologies can be used in cost-benefit analyses of risk-mitigating measures.