Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision		Previous revision
topics:uncertainty [2026/03/27 22:56] – admintopics:uncertainty [2026/04/18 00:58] (current) – vso_vso
Line 1: Line 1:
 <WRAP catbadge>General Topics</WRAP> <WRAP catbadge>General Topics</WRAP>
  
-====== Resilience ======+====== Uncertainty ======
  
 <WRAP meta> <WRAP meta>
-lead-authors: Vitaliy Soloviy +lead-authors: 
-contributors: Klaus Kubeczko+contributors:
 reviewers: reviewers:
-version: 3.0 +version: 0.5 
-updated: 16 March 2026 +updated: 25 March 2026 
-sensitivity: medium +sensitivity: low 
-ai-use: Claude Sonnet 4.6 (Anthropic) was used for topic structuring, editorial revision, reference verification, and formatting; reviewed by Vitaliy Soloviy, 17 March 2026 +ai-use: Claude Sonnet 4.6 (Anthropic) was used for research synthesis and section drafting; all sources independently verified 
-status: in-review+status: draft
 </WRAP> </WRAP>
  
 <WRAP intro> <WRAP intro>
-Resilience refers to the performance and evolution of energy systems under disruptions, from acute shocks like extreme weather and cyberattacks to chronic stresses like shifting demand patterns and climate change. Thinking about resilience goes beyond absorbing shocks to include how systems adapt to the changing nature of disruptions and how they transform to safeguard essential functions over the long term. +Uncertainty denotes conditions where there is no sufficient information to assign reliable probabilities to outcomes, ranging from parametric uncertainty (known unknowns) to deep uncertainty around hardly imaginable futures (unknown unkowns).
-</WRAP> +
- +
-<WRAP insight> +
-Resilient energy systems draw on four capacities — absorptive, adaptive, transformative, and anticipatory — requiring alignment across technical design, institutions, and actor roles.+
 </WRAP> </WRAP>
  
 ===== Why this matters ===== ===== Why this matters =====
  
-Electricity systems were designed around a narrower range of threats than they now face. Extreme weather events are increasing in frequency and severity, cyber threats target both operational technology and data infrastructure, and chronic stresses from ageing assets and shifting generation mixes compound over time.+Energy transitions involve long planning horizons, capital-intensive infrastructure, new actors, and shifting regulatory frameworks. All of this generates both risk and uncertainty in ways that interact and compound. Understanding the difference between the two, and where each comes from in energy systems specifically, is a precondition for designing effective governance responses.
  
-An acute example is the April 2025 Iberian blackout that collapsed the entire Spanish-Portuguese system within seconds. Technically mature renewable installations were operating without grid-forming inverter capabilities, and coordination protocols between TSOs had not been designed for a system where renewables supplied 78% of generation. Technical readiness in individual components did not translate into system-level resilience.((ENTSO-E Expert Panel. (2025). //Grid incident in Spain and Portugal on 28 April 2025: Factual report (Phase 1)//. ENTSO-E. https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/))+<WRAP callout> Uncertainty resists calculation, but it can be approached through embracing the inherent diversity of possible futures. </WRAP>
  
-The number of actors involved in system operation is growing, and the coordination required to manage disruptions cuts across technical, regulatory, and governance domains. Smart grid transitions redistribute where resilience sits in the system. Distributed generation and storage shift some resilience functions from central infrastructure to the grid edge, where households, communities, and microgrid operators become participants rather than passive consumers. Meanwhile, digitalisation makes new forms of coordination possible but also introduces cyber vulnerabilities that did not exist in analogue systems. Whether these changes strengthen or weaken overall resilience depends on how well technical design, institutional rules, and the capacities of different actor groups are aligned.+===== Shared definitions =====
  
-<WRAP callout> +The canonical distinction comes from Frank Knight's 1921 work //Risk, Uncertainty and Profit//.((Knight, F. H. (1921). //Risk, uncertainty and profit//. Houghton Mifflin. https://oll.libertyfund.org/titles/knight-risk-uncertainty-and-profit)) Knight argued that risk applies to situations where the outcome is unknown but the odds are measurable — probabilities can be estimated from prior data or general principles. Uncertainty, by contrast, applies to situations where the odds themselves cannot be known, where no reliable probability distribution can be assigned to future outcomes.
-Smart grid transitions redistribute resilience across the system — distributed resources can strengthen local resilience while digitalisation introduces new cyber vulnerabilities. The net effect depends on how well design, rules, and actor capacities are aligned. +
-</WRAP>+
  
-===== Shared definitions =====+The distinction is not merely academic. In conditions of risk, standard tools of insurance, hedging, diversification, and statistical forecasting can function. In conditions of genuine uncertainty, those tools give false assurance. Institutional economists and governance scholars draw on Knight's distinction to explain why energy system transitions are so difficult to manage: many of the most consequential variables — technology trajectories, political shifts, regulatory change, consumer behaviour at scale — are genuinely uncertain rather than risky in Knight's sense.
  
-Resilience in energy systems encompasses the capacity to anticipate, withstand, respond to, and recover from disruptions while developing and transforming over time to maintain core functions. Two dimensions structure the concept. The first concerns disruptions: the SINTEF/NTNU risk pyramid arranges these along a severity gradient from everyday operational events through serious incidents to catastrophic system failures, each requiring distinct governance and response types. The second concerns the capacities a system can draw on.+Drawing on expert stakeholder research in the UK electricity sector, Connor et al. (2018) group the sources of risk and uncertainty in smart grid deployment into seven categories.((Connor, P. M., Axon, C. J., Xenias, D., & Balta-Ozkan, N. (2018). Sources of risk and uncertainty in UK smart grid deployment: An expert stakeholder analysis. //Energy//, 161, 1–9. https://doi.org/10.1016/j.energy.2018.07.115))
  
 <WRAP tablecap> <WRAP tablecap>
-**Table 1.** Four resilience capacities and their smart grid expressions.+**Table 1.** Seven categories of risk and uncertainty in smart grid deployment.\\ 
 +//Source: Connor et al. (2018).//
 </WRAP> </WRAP>
  
-^ Capacity ^ What it involves ^ Smart grid examples ^ +^ Category ^ What it covers ^ 
-| **Absorptive** | Withstanding shocks without loss of core function through redundancy, robustness, and rapid response | Redundant communication paths, fault-tolerant grid design, ruggedised critical components | +| **Markets** | Uncertainty about how electricity markets will develop, including new market structures, price signals, and business models for distributed resources | 
-| **Adaptive** | Adjusting system configuration and operation in response to changing conditions | Demand response programmes, flexible grid topologies, updated operating procedures, decentralised generation | +| **Users** | Uncertainty about consumer behaviour, adoption rates, and engagement with new services and tariff structures | 
-| **Transformative** | Reconfiguring system architecture when existing arrangements cannot absorb or adapt | Restructuring grid infrastructure and regulatory frameworks, transitioning to distributed architectures | +| **Data and information** | Risks around data access, ownership, privacy, and the governance of information flows that smart grid systems depend on | 
-| **Anticipatory** | Identifying future risks and preparing responses before disruptions materialise | Climate impact modelling, scenario-based grid planning, horizon scanning, blackout preparedness exercises |+| **Supply mix** | Uncertainty about the pace and pattern of renewable deployment, storage, and the changing generation portfolio | 
 +| **Policy** | Uncertainty about regulatory change, policy continuity, and the investment signals that government frameworks send to network operators | 
 +| **Investment conditions** | Risks related to the terms under which regulators allow capital expenditure, and whether operators will invest ahead of demonstrated need | 
 +| **Networks** | Technical and operational risks from increasing complexity when integrating distributed energy resources at scale |
  
-These capacities interact. Anticipation informs investment in absorption and adaptation, while timely adaptation may ease the deeper reconfigurations that transformation requires. A resilient system draws on all four, weighted according to the threats it faces and the time horizon it plans for.+These categories interact. Policy uncertainty raises investment risk. Data governance gaps create market uncertainty. Regulatory frameworks that do not allow investment ahead of need suppress network innovation. Risk and uncertainty in smart grid transitions are therefore systemic rather than sector-specific.
  
 <WRAP tablecap> <WRAP tablecap>
-**Table 2.** Key operational and governance terms in resilience.+**Table 2.** Key terms in risk and uncertainty analysis.
 </WRAP> </WRAP>
  
 ^ Term ^ Definition ^ ^ Term ^ Definition ^
-| **Black start capability** | The ability of a power system or generation unit to restart without relying on external electricity supply, a key function following a complete system blackout.((Panteli, M., & Mancarella, P. (2015). The grid: Stronger, bigger, smarter? Presenting a conceptual framework of power system resilience. //IEEE Power and Energy Magazine//, 13(3), 58–66. https://doi.org/10.1109/MPE.2015.2397334)) | +| **Risk (Knightian)** | A situation where the outcome is uncertain but probabilities can be measured or estimated from available data; standard insurance, hedging, and statistical forecasting apply.((Knight, F. H. (1921). //Risk, uncertainty and profit//. Houghton Mifflin. https://oll.libertyfund.org/titles/knight-risk-uncertainty-and-profit)) | 
-| **Grid-forming inverter** | An inverter that establishes its own voltage and frequency reference, enabling it to support grid stability independently rather than synchronising to an existing grid signal.((ENTSO-E Expert Panel. (2025). //Grid incident in Spain and Portugal on 28 April 2025: Factual report (Phase 1)//. ENTSO-E. https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/)) | +| **Uncertainty (Knightian)** | A situation where no reliable probability distribution can be assigned to future outcomes; the odds themselves are not knowable. Also called deep uncertainty. | 
-| **Islanding** | The ability of a portion of the distribution network or a microgrid to disconnect from the main grid and operate independently during a wider system disruption, maintaining local supply to critical loads.((Panteli, M., & Mancarella, P. (2015). //IEEE Power and Energy Magazine//, 13(3), 58–66. https://doi.org/10.1109/MPE.2015.2397334)) | +| **Regulatory uncertainty** | Uncertainty arising from the possibility that rules or regulatory frameworks will change in ways that cannot be anticipated, affecting the investment case for infrastructure | 
-| **Defence plan** | A coordinated set of automatic protection actions, including load shedding and controlled system separation, designed to arrest cascading failures and preserve as much of the system as possible during severe disturbances.((ENTSO-E Expert Panel. (2025). //Grid incident in Spain and Portugal on 28 April 2025: Factual report (Phase 1)//. ENTSO-E. https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/)) | +| **Risk distribution** | The allocation of risk exposure across actors, including who bears costs when adverse outcomes occur; governance arrangements often determine this as much as underlying probabilities | 
-| **Preparedness** | The ability to anticipate risks, plan strategically, and coordinate effective responses across governance levels before disruptions occur; complementary to resilience, with emphasis on foresight and institutional coordination.((Zilli, R., et al. (2025). //Resilience and preparedness in Europe's energy transition: The role of low-carbon energy R&I// [Position paper]. European Energy Research Alliance. ISBN 9782931174111.)) |+| **Stochastic optimisation** | A class of mathematical techniques for making investment or operational decisions that explicitly model uncertainty about future states, rather than assuming a single expected outcome.((Lara, C. L., Mallapragada, D. S., Papageorgiou, D. J., Venkatesh, A., & Grossmann, I. E. (2018). Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm. //European Journal of Operational Research//, 271(3), 1037–1054.)) |
  
 ===== Perspectives ===== ===== Perspectives =====
  
-How resilience plays out in practice depends on who is responsible for it, what technical capabilities are in place, and which rules govern how actors respond. Where the three perspectives overlap, particularly around data infrastructure and coordination protocols, the interactions matter as much as the individual dimensions.+Risk and uncertainty manifest differently depending on whether the lens is on who bears exposure, what technical tools exist for managing it, or what institutional arrangements reduce it.
  
 <WRAP perspectives> <WRAP perspectives>
 ==== Actors and stakeholders ==== ==== Actors and stakeholders ====
  
-System operators carry primary responsibility for operational resilience, but as grids become more decentralised, the contributions of households with battery storage, energy communities, and microgrid operators gain significance. Different actors hold different views on resilience depending on how they use electricity, which constraints affect them most, and what timescales matter for their decisions. A transmission system operator planning infrastructure investments over decades faces different resilience questions than a community microgrid operator managing seasonal cyclone risk. Coordination among these groups — through knowledge exchange, resource sharing, and rapid response protocols — shapes whether resilience benefits are distributed equitably.+Different actors face structurally different risk and uncertainty exposures. Network operators face regulatory risk about allowable returns and investment timing. Developers of new energy services face market uncertainty about whether viable business models will emerge. Consumers face uncertainty about tariffs, technology commitments, and data use. Aggregators and flexibility providers face compound uncertainty across multiple regulatory and market dimensions at once.
  
-<WRAP case> +The distribution of risk also raises equity questions. Where risk is borne by consumers through tariffs, or by communities through infrastructure siting decisions, the governance of that distribution matters as much as its aggregate level.
-**Japan -- post-Fukushima resilience restructuring** \\ +
-The systemic response to the 2011 disaster involved multiple actor groups: utilities restructured generation portfolios, regulators overhauled safety and market rules, municipalities developed local energy resilience plans, and households adjusted consumption patterns. The 7th Strategic Energy Plan, adopted in February 2025, continues to place energy security alongside decarbonisation as a core policy pillar.((Ministry of Economy, Trade and Industry, Japan. (2025). //7th Strategic Energy Plan//. METI. https://www.enecho.meti.go.jp/en/category/others/basic_plan/)) +
-</WRAP> +
- +
-<WRAP case> +
-**Puerto Rico -- post-hurricane grid reconstruction** \\ +
-Rebuilding the electricity system after Hurricanes Irma and Maria in 2017 involved federal agencies, the utility PREPA, municipal governments, and community organisations, exposing how fragmented institutional responsibilities can slow resilient recovery.((Federal Emergency Management Agency. (2018). //2017 hurricane season FEMA after-action report//. FEMA. https://www.fema.gov/sites/default/files/2020-08/fema_hurricane-season-after-action-report_2017.pdf)) +
-</WRAP> +
- +
-<WRAP case> +
-**Bangladesh -- cyclone-resilient energy infrastructure** \\ +
-Communities in coastal areas have worked with NGOs and government agencies to develop resilient off-grid solutions that withstand frequent cyclone exposure, demonstrating that resilience building in resource-constrained settings depends on local actor capacity as much as technology.((International Renewable Energy Agency. (2016). //Innovation outlook: Renewable mini-grids//. IRENA. https://www.irena.org/publications/2016/Sep/Innovation-Outlook-Renewable-Mini-Grids)) +
-</WRAP>+
  
 ==== Technologies and infrastructure ==== ==== Technologies and infrastructure ====
  
-System architecture — how technical components are arranged and how they interact — is a major factor in a grid's resilience. Wide-area monitoring provides situational awareness during disturbances. Advanced distribution management systems enable rapid reconfiguration after faults. Microgrids with islanding capability allow critical facilities to maintain power during wider outages. Redundancy in communication networks ensures that monitoring and control functions survive localised failures. What distinguishes resilient architecture from robust architecture is the capacity not only to withstand shocks but to reconfigure in response to them.+At the technical level, uncertainty is embedded in the variability of renewable generation, the unpredictability of demand at high granularity, and the behaviour of large numbers of distributed devices coordinating through automated systems. Investment decisions about long-lived infrastructure must be made under uncertainty about what technology costs, capabilities, and market conditions will look like over decades.
  
-<WRAP case> +Planning electricity systems under uncertainty has become a recognised field of research, with stochastic optimisation methods developed specifically to improve investment decisions when future scenarios cannot be reduced to a single expected value.
-**Australia -- South Australia system resilience programme** \\ +
-Following the September 2016 statewide blackout, the South Australian government and AEMO implemented a coordinated response including the Hornsdale Power Reserve, updated frequency control requirements, and revised grid connection standards for wind and solar that addressed the specific technical gaps the event had exposed.((Australian Energy Market Operator. (2017). //Black system South Australia 28 September 2016: Final report//. AEMO. https://www.aemo.com.au/-/media/files/electricity/nem/market_notices_and_events/power_system_incident_reports/2017/integrated-final-report-sa-black-system-28-september-2016.pdf)) +
-</WRAP> +
- +
-<WRAP case> +
-**Spain and Portugal -- April 2025 Iberian blackout** \\ +
-The loss of approximately 15 GW of generation within five seconds revealed how inverter-based renewable plants operating in fixed-power-factor mode contributed to cascading failure. The ENTSO-E factual report identified excessive voltage as the probable trigger, with plants disconnecting automatically to protect equipment rather than actively supporting the grid.((ENTSO-E Expert Panel. (2025). //Grid incident in Spain and Portugal on 28 April 2025: Factual report (Phase 1)//. ENTSO-E. https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/)) +
-</WRAP> +
- +
-<WRAP case> +
-**Denmark -- Bornholm island microgrid demonstration** \\ +
-The EcoGrid EU project tested whether a distribution network with high wind penetration could operate in islanded mode, providing evidence on technical resilience capabilities for isolated systems dependent on variable generation.((EcoGrid EU. (2016). //EcoGrid EU: A prototype for European smart grids. Final report//. http://www.eu-ecogrid.net/)) +
-</WRAP>+
  
 ==== Institutional structures ==== ==== Institutional structures ====
  
-Regulatory frameworks shape how resilience is defined, measured, and invested in. Performance-based regulation can reward utilities for improving resilience outcomes rather than simply expanding infrastructure. Market designs that value fast frequency response, black start capability, and voltage support create commercial pathways for resilience provision. Cross-sector planning for interdependencies between electricity, telecommunications, water, and transport helps ensure that resilience in one domain does not depend on fragile assumptions about another.+Institutions reduce uncertainty by creating stable rules, expectations, and coordination mechanisms. Property rights, contracts, regulatory frameworks, and standards all substitute shared expectations for the need to forecast each individual actor's behaviour. This is the institutional economics argument for why institutional quality matters for infrastructure investment: predictable rules lower the uncertainty premium that investors must price in.
  
-<WRAP case> +Regulatory uncertainty is particularly significant for long-lived capital investments. When the rules governing energy systems shift with political cycles or change unexpectedly, the investment case for smart grid infrastructure becomes harder to make. Mandate clarity, incentive structures, and the legal durability of regulatory commitments are therefore not merely administrative concerns — they shape what transitions are financially viable.
-**United Kingdom -- Ofgem resilience obligations** \\ +
-The RIIO-ED2 regulatory framework includes specific output targets for network resilience, including flood protection and overhead line undergrounding in high-risk areas, linking operator revenue directly to measurable resilience performance.((Ofgem. (2022). //RIIO-ED2 final determinations//. Office of Gas and Electricity Markets. https://www.ofgem.gov.uk/publications/riio-ed2-final-determinations)) +
-</WRAP>+
  
-<WRAP case> 
-**Nigeria -- grid resilience governance** \\ 
-The institutional separation of generation, transmission, and distribution across different entities creates coordination challenges, particularly at the interface between the Transmission Company of Nigeria and regional distribution companies where operational responsibilities overlap. 
 </WRAP> </WRAP>
  
-<WRAP case> +===== Distinctions and overlaps =====
-**Chile -- critical infrastructure protection framework** \\ +
-Institutional arrangements for protecting electricity infrastructure against seismic and climate-related hazards reflect the country's geophysical realities, illustrating how regulatory design can embed resilience requirements specific to local conditions rather than imported from generic templates. +
-</WRAP>+
  
 +<WRAP distinction>
 +**Risk vs uncertainty**\\
 +Knight's distinction is categorical, not scalar. Treating deep uncertainty as high risk may produce a false sense of quantitative rigour. Models that assign precise probabilities to genuinely uncertain outcomes can be more misleading than approaches that acknowledge the uncertainty directly.((Knight, F. H. (1921). //Risk, uncertainty and profit//. Houghton Mifflin. https://oll.libertyfund.org/titles/knight-risk-uncertainty-and-profit))
 </WRAP> </WRAP>
- 
-===== Distinctions and overlaps ===== 
  
 <WRAP distinction> <WRAP distinction>
-**Resilience vs reliability**\\ +**Uncertainty reduction vs risk management**\\ 
-Reliability concerns continuous electricity supply under normal operating conditions and foreseeable contingencies. Resilience concerns the system's response to high-impact, low-probability events and chronic stresses that exceed normal planning assumptions. A reliable system may lack resilience if it cannot cope with conditions it was not designed for.+Institutional arrangements, regulatory frameworks, and governance structures reduce uncertainty by creating stable expectations. Risk management tools such as hedging and insurance address situations where probabilities can be estimated. The two require different instruments and different policy designs. This is why the institutional environment matters for infrastructure investment: it performs uncertainty reduction rather than risk transfer.
 </WRAP> </WRAP>
  
 <WRAP distinction> <WRAP distinction>
-**Resilience vs preparedness**\\ +**Uncertainty vs resilience**\\ 
-Resilience describes the capacity to withstand, adapt to, and recover from disruptions. Preparedness describes the ability to anticipate risks and coordinate responses before disruptions materialise. A system can be resilient in its technical design while underprepared institutionally. The 2025 Iberian blackout illustrated this gap: renewable installations met technical performance standards individually, but the system lacked the grid-forming inverter deployment and cross-TSO coordination protocols that preparedness planning would have identified as necessary.+A system designed for a known risk can be optimised around that risk's probability distribution. A system designed for genuine uncertainty needs different properties: flexibility, redundancy, and the ability to adapt to outcomes that were not anticipated. See [[topics:resilience|Resilience]].
 </WRAP> </WRAP>
  
 ===== Related topics ===== ===== Related topics =====
  
-[[topics:flexibility|Flexibility]] · [[topics:institutions|Institutions]] · [[topics:transitions|Transitions]] · [[topics:digitalisation|Digitalisation]] · [[topics:critical_infrastructure|Critical infrastructure]] · [[topics:operator|Operator]]+[[topics:resilience|Resilience]] · [[topics:scenarios|Scenarios]] · [[topics:institutions|Institutions]] · [[topics:regulation|Regulation]] · [[topics:governance|Governance]] · [[topics:transitions|Transitions]] · [[topics:risk|Risk]]
  
 ===== Topic notes ===== ===== Topic notes =====
  
-~~DISCUSSION|Discussion~~+~~Discussion~~