N-1 Criterion

The N-1 criterion is the classical, deterministic standard for transmission-grid operational security: the network must be dimensioned and operated so that the loss of any single component — a transmission line, a transformer, a power plant — does not cause a customer outage or push voltages/currents outside predefined limits. “N-1” means the system in its normal state (N) must still function with one (1) fewer component. It is the industry’s foundational answer to “how safe is safe enough,” and it has worked: the Nordic grid has reached roughly 99.98% general availability under it — an outcome so good, and outages so rare, that any actual disruption (as in Spain’s 2025 blackout) draws intense scrutiny precisely because it is so unusual. (Source - Svk Målet Maximal Tillgänglig Kapacitet (2021))

What N-1 actually requires

Svenska kraftnät‘s control room staff work around the clock to keep the transmission grid maximally utilised without ever compromising N-1 compliance — meaning the available capacity offered to the market shifts constantly as underlying conditions change: planned maintenance and construction, but also structural shifts in flow patterns. A concrete Swedish example: historically, Swedish power flows ran predominantly north–south, and the transmission grid was built around that assumption. New east–west flows in central Sweden (driven by changing generation and consumption patterns) now also affect how much transfer capacity can be offered while still guaranteeing N-1 security. Because Sweden and the EU run a deregulated electricity market, Svenska kraftnät cannot simply decide where new generation should be sited to relieve this — it can only take grid-side measures (network reinforcement, ancillary services, new equipment) to make more capacity available within the existing topology. (Source - Svk Målet Maximal Tillgänglig Kapacitet (2021))

The core limitation: risk is never quantified

N-1’s central weakness is not that it is unsafe — it is that it does not measure how safe. A grid operating state either passes N-1 or it doesn’t; there is no number attached to how likely a violating contingency actually is, or how severe the consequences would be if it occurred. This cuts both ways:

• The risk from a given operating state could be too high relative to what the operator believes, if the deterministic assumptions don’t hold.
• Just as importantly — and less intuitively — the risk could be too low. If a state fails N-1, the operator must intervene (curtailing production, paying a generator to start, redispatching), even though the actual probability of the triggering contingency, given real conditions, might be vanishingly small. Because that probability is never calculated, some of these interventions are unnecessary — costing money and affecting the electricity price, when the intervention might not have been needed. (Source - Energiforsk 2026-1165 Stokastisk Driftsäkerhet Transmissionsnät (2026))

Oddbjørn Gjerde of SINTEF Energi frames this sharply: N-1 has become “a hindrance to electrification” — large parts of network capacity sit permanently reserved against a worst-case single-contingency assumption that, in Norway’s more probabilistic practice, is often judged unnecessary. Fornybar Norge (the Norwegian renewables-industry body) argues N-1 leaves grid capacity idle “that could otherwise be used by new green industry.” (Source - Säkerhetskrav Hinder För Elektrifieringen (2024))

The EU shift to probabilistic risk assessment

Europe’s TSOs are moving from N-1 toward stochastic (probabilistic) operational risk assessment — quantifying risk explicitly as probability × consequence, rather than a pass/fail deterministic test.

• Origin: the EU-funded GARPUR project (2013–2017; Generally Accepted Reliability Principle with Uncertainty modelling and through probabilistic Risk assessment) — a consortium of a dozen research institutions and seven TSOs (Denmark, Iceland, France, Belgium, Bulgaria, Czechia, Norway), coordinated by SINTEF Energi — designed the methodological framework now being adopted EU-wide.
• Regulatory mandate: ACER (the EU Agency for the Cooperation of Energy Regulators) decided in June 2019 to establish CSAM (the methodology for coordinating operational security analysis), which requires a common probabilistic risk-assessment methodology (Art. 44), citing GARPUR’s work as the basis. ENTSO-E’s dedicated Working Group Probabilistic Risk Assessment (WG PRA — formed 2021, now 20 TSOs + 2 regional coordination centres) leads the work and has published three biennial progress reports (2021, 2023, December 2025).
• Target date: CSAM Art. 44.1 requires all TSOs to jointly develop and propose the PRA methodology by 31 December 2027 — a drafting/regulatory-approval deadline, not an implementation one. ENTSO-E’s own third progress report states that “It is expected that the PRA methodology will be drafted by 2027 … with implementation occurring post-2027,” with no further date given. In its first implementation phase, PRA is explicitly meant to run in parallel with N-1, not replace it outright. (Source - ENTSO-E Third Probabilistic Risk Assessment Report (2025))
• Progress as of December 2025: probability-computation work has focused on testing the VAFFEL concept (Statnett-developed, tested by MAVIR and TenneT NL, for wind/lightning-driven overhead-line failures) — the only method tested so far; a proof-of-concept impact-assessment tool is in testing (Power Factory/Python), with first results expected early 2026. Data collection: 27 of 40 TSOs provided 2023 grid disturbance data; no accepted “acceptable risk” threshold yet exists across TSOs. No Nordic- or Swedish-specific status is given in the report.
• Norway already deviates from N-1 in practice: around Stavanger, Bergen, and Trondheim, Statnett does not apply N-1 in all operating situations, supplementing with probabilistic calculations instead — while further north, where Norway’s grid is more sparsely built and long-stretched, N-1 remains necessary for smaller towns and low-density regions. The EU framework (network codes) explicitly leaves this kind of case-by-case judgement to each TSO, as long as faults don’t propagate to the wider synchronous area. (Source - Säkerhetskrav Hinder För Elektrifieringen (2024))
• Sweden’s own research programme is converging independently: Energiforsk’s Stokastisk driftsäkerhet av transmissionsnät project (Luleå University of Technology, Zunaira Nazir and Math Bollen, report 2026:1165) developed its risk-quantification methods without direct involvement in the ACER/ENTSO-E process, and its authors note reaching “quite similar conclusions” — which they see as only positive. (Source - Energiforsk 2026-1165 Stokastisk Driftsäkerhet Transmissionsnät (2026))

How operational risk is actually calculated

The Energiforsk report lays out the mechanics (see that source page for full detail): operational risk R is the sum, over all considered contingencies c, of the contingency’s probability P(c) times its severity factor F(c). A “contingency” (oförutsedd händelse) can be first-order (one component fails), second-order (two), or higher; probability is built from each component’s unavailability (Q); severity factors quantify consequences along three axes — technical (voltage/current/frequency vs. thresholds), customer-related (number of customers or kW/kWh disconnected, outage duration), and economic (cost of the disruption and of any mitigating action).

The combinatorics are the immediate practical problem: a transmission network with 250 primary components already has roughly 1.8×10⁷⁵ possible availability combinations — far beyond any feasible computation — so real applications must deliberately limit which contingency orders and combinations are considered, trading completeness for tractability.

Practical barriers still blocking adoption

Energiforsk’s authors say the methods are far from ready to take over from the deterministic N-1 approach, though they may provide additional information on operation and, in the longer term, a basis for operating decisions. The report identifies four research-to-application gaps:

1. Computation time — a hard constraint for short-lead-time applications (real-time or hour-ahead risk), and one that worsens with network size.
2. Presentation of results — needs research into how to present results so it is immediately clear which events and components contribute most to the risk.
3. Interpretation of results — not enough experience yet to develop automatic methods such as machine learning, and no experience of what counts as a high or low risk.
4. Realistic data — good average failure-rate statistics exist for many components over multi-year periods, but statistics are lacking for most component types in high-failure-rate periods such as storms.

Two further obstacles are named elsewhere in the report: severity-factor standardisation (§7.2.3) — the authors’ view of the biggest challenge is defining suitable severity factors, which requires collaboration between researchers and method users; ACER’s 2019 decision calls for a common methodology, but standardisation must not end development of alternative methods — and the absence of any method or criterion for judging whether a computed risk is acceptable (§7.4), described as a serious barrier to risk-based operation.

Why this matters for flexibility

The connection to this wiki’s core subject is explicit, not incidental. Energiforsk’s report states outright that stochastic operational-risk methods “will be important for implementing smart-grid approaches like flexibility markets, large- and small-scale battery storage, demand curtailment, and end-customer participation in electricity markets.” Two concrete mechanisms are named:

• Demand-side forecast error is itself a source of operational-risk uncertainty — the report explicitly names EV charging, demand-side flexibility, and customer battery storage as new types of consumption where forecast errors can be large, alongside the more familiar wind/solar forecast error.
• Day-ahead risk calculations can serve as the decision input for whether to activate a flexibility market — one of the listed possible applications of operational risk assessment (§2.3 of the report) is day-ahead planning to assess the need to intervene in the electricity market or to decide whether flexibility markets need to be activated; the report lists this as a use case, not as an implemented practice.

The broader Energiforsk research programme (Risk- och tillförlitlighetsanalys, 2021–2025 synthesis) shows this N-1-to-probabilistic shift is not an isolated transmission-only story — the same methodological move (deterministic → stochastic) recurs in hosting-capacity/acceptance-limit calculations for distribution networks and in probabilistic transformer thermal-loading studies, where moving beyond fixed, conservative limits is explicitly framed as freeing up capacity for EV charging and solar connections without new infrastructure — the same logic as N-1 reform, applied one level down the voltage hierarchy. (Source - Energiforsk 2025-1148 Syntesrapport Risk Och Tillförlitlighet (2025))

Cross-references

• Congestion Management — N-1 as one input into how “available capacity” is defined; the broader deterministic-vs-flexible capacity-release toolkit
• Grid Capacity Utilization — the distribution-level parallel (hosting capacity / acceptansgräns) to N-1’s probabilistic reform
• Source - Svk Driftsäkerhet Augusti 2025 — Svk’s own six-system-needs framework, in which N-1 (fault tolerance) is one of six operational security requirements
• Svenska kraftnät — the TSO whose control room applies N-1 today and would implement any probabilistic successor
• Flexibility Need Assessment / Distribution Network Development Plan — N-1 analysis as a standard input to Swedish DSO capacity-need quantification
• Energy Storage — battery-related findings from the same Energiforsk research programme

Data gaps

• Whether/how Svenska kraftnät itself has committed to a timeline for adopting probabilistic methods post-2027, beyond the general EU-level mandate — the ENTSO-E report doesn’t name Svk individually or confirm its WG PRA membership
• Concrete accepted risk-threshold criteria, once any TSO or regulator publishes one (currently an open research gap per Energiforsk)