Grid Capacity Utilization

Freeing more usable capacity in the existing grid while new build catches up. Because grid reinforcement takes 10–15 years and demand is growing faster, the capacity already physically present but not allocated becomes decisive. The central insight (Energiforsk Kapacitet för tillväxt, 2026) is that allocatable capacity is not a fixed technical limit — it is the output of trade-offs between technical analysis, safety margins, uncertainty handling, the N-1 principle, and the interaction between grid levels. International experience shows 20–40% more capacity can be freed in congested grid sections, with the first 10–15% relatively easy, through better measurement, active operation, and new contract forms. (Source - Energiforsk 2026-1190 Kapacitet för Tillväxt (2026))

The framing matters: a customer’s simple question — “is there 10 MW free?” — hides extensive parallel calculations, and technical potential does not automatically become allocated capacity. Capacity is a system question where technique, rules, and responsibility interact. Increased utilisation is therefore primarily a delivery problem (genomförandeproblem), not a technology problem — gated by leadership, governance, and execution capability rather than by physics.

Three families of capacity-release measures

The five Energiforsk takeaways behind that dependency: without technical margin → no actual power; without working contract logic → no controllable flexibility; without organisational capability → low practical impact; without a clear risk/responsibility split → no scalable solution; without rules that support efficient utilisation → the potential stays on the drawing board.

International evidence

• Netherlands — TenneT TDTR (contractual). Facing a capacity crisis (societal cost estimated €20–40 bn/year), TenneT introduced a standardized conditional agreement, the Time-Driven Transport Right (TDTR): contracted power guaranteed 85% of the year in exchange for a 50% network-fee discount. Analysis of actual annual utilisation identified ~9 GW allocatable to new customers willing to be limited (the source says “a few hours”, which sits uneasily with an 85%-of-year guarantee that leaves up to ~15% of the year). Firm (100%-access) capacity is increasingly treated as a “luxury good.” See Villkorade Avtal, Flexible Connection Agreements.
• Netherlands — Liander (technical). Temperature measurement on transformers and cables freed 20–30% in identified bottlenecks (first 10–20% relatively easy), with a new loading ceiling of 120% of nominal where technically possible. Trade-offs: higher losses, some shorter component life — judged outweighed by the extra connections enabled. See Dynamic Line Rating.
• United Kingdom — Flexible Plug and Play (operative + contractual). Active system management within fully flexible agreements delivered up to 87% lower connection costs and 57% shorter lead times; the pilot’s results were folded into legislation.

Connection-queue reform as a capacity lever

A clogged queue hides the true capacity need and starves ready projects of resources. Energiforsk stresses that effective prioritisation has required state-led frameworks, not decisions left to individual DSOs:

• UK — “first ready and needed, first connected”: clears immature projects and prioritises readiness plus alignment with national goals; projects failing maturity tests lose or drop in the queue.
• Netherlands — national prioritization framework: departs from first-come-first-served for priority categories (actors that free capacity for others, safety-critical operations, basic societal functions), on objective regulator-defined criteria.

Sweden’s own response — the faktisk belastning doctrine, Ei2025:02–05 ställningstaganden, Svk’s Anvisningssystem, and EU Art. 6a/31.3 — is analysed in DSO Connection Queue Reform — The Swedish Policy Response. Sweden currently relies on mognadsgrad maturity criteria and Ei’s “aktiv köhantering” (first-come-first-served need not be followed), but explicitly leaves system/societal prioritisation judgements outside the framework.

The revenue-regulation dimension

Capacity-release measures compete on unequal terms with grid investment unless revenue regulation rewards them. The companion Energiforsk analysis (Source - Energiforsk 2026-1175 Kapacitet för Tillväxt Intäktsreglering (2026)) compares three regimes:

• Netherlands: TOTEX since 2001; from 2027 shifting from benchmark to actual costs with ex-ante assessment and full ex-post truing-up (lower investment risk); flexibility treated as a first-hand measure requiring CAPEX/OPEX neutrality; ACER’s regulator (ACM) proposes a nominal pre-tax WACC of 5.40–5.80% for DSOs for 2027–2031 — still a draft under consultation, not yet finalized.
• United Kingdom: output-based TOTEX since 2013 (RIIO); flexibility rewarded on par with investment via “slow money” (long OPEX depreciation into the RAB), plus the Flexibility Commitment Index (FCI) and Use-or-Explain (justify every reinforcement against a flexibility alternative). Real WACC 4.5–4.7% is Ofgem’s transmission-level figure (RIIO-ET3, 2026–2031); the distribution-level control (RIIO-ED3, 2028–2033) is still only proposed in the cited source, with no confirmed WACC of its own yet.
• Spain: centralised, nationally harmonised tariffs not linked to DSO costs; steered via binding NDPs and detailed rules rather than economic incentives; moving toward output/TOTEX neutrality; mandatory flexibility services from 2026.

These are the reference points for Sweden’s own move to TOTEX / lösningsneutralitet under RP5 (2028–2031) — see Ei › Key positions and Swedish DSO Tariff Reform — Three Parallel Tracks (2025–2027). The UK’s FCI/Use-or-Explain pair is the clearest existing example of regulation that actively rewards a DSO for choosing flexibility over reinforcement.

Swedish context

EIFS 2023:6 defines effektivt nätutnyttjande as “low network losses and even power in the grid” (3 kap. §11) — meaning measures that raise total costs (extra losses, component wear) can be argued to work against efficient utilisation in the Swedish sense, a tension with the loss-accepting dynamic-rating approach abroad. Swedish DSOs already deploy parts of the toolbox: Svk (villkorade anslutningsavtal, kapacitetsåtgärd procurement, controllable AC-flow steering, a DLR pilot); E.ON Energidistribution (villkorad anslutning via styrning, OLCC overhead-line capacity calculation, a belastningsguide, and a flexible-connection process pending reinforcement); Göteborg Energi Nät (effekttariffer, villkorade avtal — e.g. reduce to 1 MW at 2h notice with low activation probability — a local flexibility market, and partial risk-based dimensioning). Swedish villkorade-avtal rules require that market-based alternatives be exhausted first, so these agreements are framed as a last resort and time-limited to protect the customer collective (Ei2025:01).

Trollhättan — smart EV-charging load control (technical, contractual-adjacent): a practical pilot by Trollhättan Energi, Kraftstaden Fastigheter, and Innovatum Science Park in a mixed residential/industrial area found that remote load control of EV charging works and lets property owners add charging points, and DSOs defer transformer-station investment, without new grid contracts — but only where chargers support open communication standards; older chargers without them simply cannot be remotely controlled at all, a hard technical floor rather than a tuning problem. One operational finding worth flagging for any managed-charging deployment: charging power should never be dropped all the way to zero, since some vehicles interpret that as the session ending rather than pausing. Framed by the pilot as primarily an organisational challenge (clear roles, cross-actor collaboration, open-standard procurement requirements) rather than a technical one. (Source - Mätning och Styrning Eleffekt Trollhättan Living Lab (2026), summarised in Source - Energikontor Vast Smart Laddning Trollhattan (web))

Lysekil — Preem Tech Park, flexibility designed in from the planning stage: an industrial-symbiosis scenario study (LEVA, with Lysekil kommun and Preem; a fictional scenario at a real site) for a new circular industrial park combining fish farming, greenhouses, slaughterhouses, water treatment, and EV charging. Scenario gross demand ~30 MW / 103 GWh/year, but ~32 MWp solar + ~23 MW wind assumed local generation plus ~8.5 MW of identified flexibility (6 MW from greenhouse LED lighting, ~1 MW each from two types of fish farm) leave the net rise in average power at only ~1 MW (81 to 82 MW for the whole Stångenäs system including the existing Preem and Lysekil loads and existing generation), framed as better use of existing 130 kV lines from Trollhättan rather than extensive grid build-out. Distinct from the DSO-side retrofits above: flexibility is assumed from the planning stage, not added after the fact (in a scenario, not an operating facility). (Source - Framtida Flexpotential Greenfield Lysekil (LEVA, 2026), summarised in Source - Energikontor Vast Preem Tech Park Lysekil (web))

Probabilistic hosting-capacity and transformer-loading methods

The same deterministic-to-probabilistic shift driving the N-1 reform at transmission level shows up independently in Swedish distribution-level research. Energiforsk’s 2021–2025 risk-and-reliability programme produced a practical handbook standardising deterministic, stochastic, and time-series methods for calculating a distribution grid’s hosting capacity (acceptansgräns) — how much new generation or load a network can accept before voltage limits are breached. Deterministic methods risk understating overvoltage; stochastic methods require agreeing an acceptable planning risk (past practice assumed a 10% risk figure without documented justification for what exactly it applies to — the source doesn’t specify “headroom loss” as the unit); time-series methods are the most realistic but the most data- and compute-heavy. A separate probabilistic transformer thermal-loading study (22 months of measurement plus simulation) found transformers often tolerate materially higher loading than current fixed current-based limits allow, especially once weather and cooling are properly accounted for — and recommends shifting long-term planning from current-based to temperature/ageing-based limits specifically because doing so “can give greater flexibility in the grid, e.g. for connecting solar panels or EV charging.” (Source - Energiforsk 2025-1148 Syntesrapport Risk Och Tillförlitlighet (2025))

Choosing the measure mix — a decision process

Freeing capacity is not only about which measures exist but how a DSO decides between them. Energiforsk’s holistic network-development study (Source - Energiforsk 2026-1192 Holistisk Nätutvecklingsstrategi (2026); Sweco, 12 DSO interviews + a case study) proposes moving DSOs from separate tracks (investment, flexibility, tariff development) to an integrated decision process, with key principles:

• Handle by time horizon, plan adaptively. Under high uncertainty, combine reversible measures (flexibility) with irreversible ones (reinforcement) to limit over- and under-investment — two complementary processes, one short-term (connection requests) and one long-term strategic (iterative).
• No rule of thumb. There is no general threshold for when flexibility beats reinforcement; the outcome depends strongly on local conditions (see DSO Flexibility Valuation — Methods and Swedish Evidence). Capacity problems can also arise soon even where today is manageable, driven by battery and solar connections.
• A proposed ordering of measures: omkopplingar (switching/reconfiguration) as a first-hand measure; network tariffs as a proactive practice that mainly shifts long-term forecasts rather than steering specific hours; reinforcement and flexibility trading as equivalent alternatives compared on both reliability and cost; and villkorade avtal as a “fallback” where flexibility markets are not reliable enough or market-failure consequences are high.

Both reliability trade-offs and economic analysis enter every comparison — making explicit which evaluation steps a decision requires.

Grid utilization trends — Ei R2026:02

Ei‘s first biennial smart grid monitoring report (Ei R2026:02, December 2025) documents two utilization metrics across the Swedish DSO sector:

Utnyttjningsgrad (utilization rate = annual mean demand / mean of 4 highest peaks):

• Declining trend in regionnät 2021–2024 (each year lower than the previous)
• Lokalnät shows a smaller, less clear decline
• Ei explanation: increased variable solar/wind production raises injection (which counts as load in the denominator) without proportionally reducing winter demand peaks; slower-than-expected industrial electrification also holds down mean demand growth
• Increased flexibility services use could improve the indicator

Medellastfaktor (average load factor per day):

• Data 2016–2024; possible weak declining trend in recent years; harder to establish clearly
• Regionnät consistently lower than lokalnät (except 2016)

Both metrics indicate that the DSO grid is being used less uniformly over time — the ratio of peak capacity to average throughput is growing. This has investment implications: if capacity is sized for peaks that represent an increasingly small share of total energy throughput, the case for flexibility as an alternative to reinforcement strengthens. (Source - Ei R2026-02 Utvecklingen av Smarta Elnät (2025))

Why the lead-time gap makes this urgent

Capacity release matters precisely because new build is slow. Energiforsk’s NEPP lead-time study (Source - Energiforsk 2026-1185 Ledtider för Energiomställningen (2026)) finds that the 2045 scenarios (e.g. the 300 TWh planning target) require very high and early project initiation, and that Sweden already carries an investeringsskuld — a shortfall of initiated projects relative to the scenario pathways — with permitting and grid connection as the key bottlenecks. Even large lead-time improvements only partly close the gap. Freeing 20–40% in existing grids is therefore a bridge across the years that reinforcement cannot yet cover — complementary to, not a substitute for, faster build-out (and Svk’s LT50 lead-time programme).

Related pages

• Dynamic Line Rating — the headline technical measure
• Villkorade Avtal · Flexible Connection Agreements — the contractual measures
• Congestion Management — the operational problem this addresses
• N-1 Criterion — the transmission-level parallel to probabilistic hosting-capacity/transformer-loading reform
• DSO Connection Queue Reform — The Swedish Policy Response — the Swedish queue-reform track
• Ei · Swedish DSO Tariff Reform — Three Parallel Tracks (2025–2027) — the revenue-regulation enabler
• Distribution System Operator · Anvisningssystem

Data gaps

• Whether Ei will give capacity-utilisation measures (dynamic rating, active operation) an explicit role/incentive in RP5 beyond the general TOTEX neutrality
• Quantified Swedish DLR/active-operation capacity-release results comparable to the Liander 20–30% figure