Learnings

Outcomes

The project was aimed to provide network operators such as National Grid Electricity Distribution an improved understanding of where additional network headroom can provide the greatest benefit to consumers, via a reduction in their energy bills. Whilst a direct saving did not occur during the project, the most significant outcome of the project is the ability for network operators to quantify the benefit of additional headroom as ~£100/MWh.

This figure has now be carried forwards into National Grid’s DSO benefit report, submitted to Ofgem. Looking forwards, further applications of this benefit will be explored, including ceiling prices for flexibility procurement.

The sensitivity study which suggested which voltage levels would have the greatest impact on wholesale markets has highlighted areas in which NGED are looking to develop capabilities further. Greater voltage control on the LV networks is a key step to better allow more renewables such as Solar PV to export freely. These are capabilities being explored in projects such as LV ACT and Phase Switch System.

Lessons Learnt

1) Stage 1 Learnings

a) Curtailment modelling

Summer-only view hides risk.  The Transform™ model used just four DFES representative days; only the “summer-peak-generation” profile contained export, so all forecast curtailment fell in June-Aug and around midday – essentially a PV-only problem  .
Why it matters: other DNOs using similar snapshots will underestimate winter wind or shoulder-season constraints and may time-lag reinforcement.
Solar PV is the dominant LV–EHV driver.  Even within that limited window, PV curtailment set the pattern for all technologies, peaking at 12-15 h  .
Lesson: voltage-rise limits, not thermal headroom, are likely to bite first in high-PV regions.
Behavioural assumptions on BESS swing results.  Static “charge-at-night / discharge-at-midday” profiles overstated curtailment; the report recommended revisiting battery profiles and even regulatory reform to give operators confidence in BESS benefits  .
Lesson: network studies should iterate battery operating envelopes with developers to avoid pessimistic blocking of storage connections.
Parametric averaging masks local hotspots.  The coarse archetype approach may under-report HV constraints where real feeders have far less voltage headroom  .
Lesson: supplement top-down tools with connectivity-based, feeder-level analysis before refusing or heavily constraining schemes.
No demand-driven reinforcement.  Stage 1 froze asset ratings, so curtailment simply grew with DG; this overstates risk where demand growth will trigger uprating anyway.
Lesson: align curtailment forecasts with your investment planning rules for a fairer picture of “natural” headroom release.
b) Power-market modelling

Range-finding benefit test.  Two cases – Network Curtailment (low) vs Maximum Constrained Generation (high) – produced a 2023-34 wholesale system-cost saving between £0.32 bn and £17 bn .
Lesson: even crude curtailment data showed headroom is potentially worth multiples of typical DNO reinforcement budgets.
Price and carbon impacts concentrate in tight margins.  Winter evenings saw the sharpest price uplift (up to £10/MWh) and carbon penalty when headroom was absent  .
Lesson: releasing distribution constraints is system-critical precisely when consumers and ESO need it most.
Uncertainty driven by network data.  Modellers flagged that summer-only LV/HV curtailment drove the enormous benefit range and ignored 132 kV entirely  .
Lesson: give market analysts year-round, voltage-segmented curtailment series or risk misleading planning decisions.
Early signal for DER services.  Value of lost Balancing-Mechanism and ancillary-service opportunities was highlighted but not quantified, hinting at extra upside as ESO widens <1 MW access.
2) Stage 2 Learnings

a) Curtailment modelling

Methodology upgrades deliver year-round realism.  Twelve seasonal representative days, demand-driven reinforcement, realistic grid-scale & domestic BESS cycling, V2G uptake, and planned-outage deratings replaced the Stage 1 simplifications  .
Lesson: other DNOs can borrow this modular improvement list to tighten their own headroom studies.
Curtailment triples and migrates downstream.  Annual curtailed energy rises to 8.5 TWh by 2034, enough to power 3.2 M homes; after 2030 the LV network overtakes 132 kV as the largest source, driven by domestic PV voltage rise  .
Lesson: investment priority shifts from early 132 kV bulk schemes to mass-LV voltage solutions later in the decade.
Solar still king, but wind & BESS matter upstream.  Solar accounts for 4.8 TWh curtailed in 2034, yet decision-tree analysis shows BESS exports are now the single biggest predictor of 132 kV curtailment  .
Lesson: operators must model storage dispatch flexibly and examine whether ANM set-points are inadvertently blocking batteries.
Seasonal diversity emerges.  EHV/132 kV curtailment in winter and shoulder months grows because of wind and gas generation  .
Lesson: winter constraints are coming – don’t rely solely on summertime voltage solutions.
Model limitations acknowledged.  EA Technology notes that parametric averaging still smooths out feeder extremes and advocates a follow-on connectivity-based tool  .
Lesson: granular digital-twin style tools are the next step to target reinforcement precisely.
b) Power-market modelling

Best-view whole-system benefit ~£2.5 bn (2023-34).  £1.93 bn wholesale, £0.21 bn carbon and £0.35 bn balancing-service savings when Stage 2 curtailment is removed  .
Lesson: that is equivalent to ~£200 m yr-¹ – a material addition to business-case appraisals for LV voltage upgrades.
Voltage segmentation sharpens targeting.  LV delivers 37 % of cumulative benefit by 2034 (£796 m) while 132 kV provides 53 % early on but falls thereafter  .
Lesson: regulators and investors can tie funding to time-phased, voltage-specific benefit streams.
Benefit elasticity highlights policy risk.  Varying curtailment ±80 % swings benefit between £0.49 bn and £3.9 bn  .
Lesson: headroom value balloons if renewables race ahead faster than grid build – a realistic outcome under Clean-Power 2030 ambitions.
Data science confirms cascading effects.  Models show LV PV curtailment explains most HV/EHV constraints, and 132 kV is increasingly storage-driven  .
Lesson: releasing LV headroom can relieve upstream networks, reinforcing the case for coordinated planning across voltages.
NESO-DSO coordination is non-negotiable.  Curtailment that blocks DER participation pushes up balancing costs; primacy rules, real-time data exchange and ANM upgrades are flagged as prerequisites  .
Lesson: treat curtailment as a priced action in both ANM and ESO markets to avoid counter-productive dispatch.
Curtailment treated as fixed load in PLEXOS.  This transparent approach captures wholesale, carbon and service impacts in one metric, making it easy for other TSOs/DSOs to replicate.
Why these findings matter beyond NGED?

Quantified, time-stamped headroom value helps justify proactive, rather than connection-driven, investment – a key theme for ED3 price-control negotiations.
The pivot from 132 kV to LV constraints shows that waiting for “visibility” can miss the window where cheap reinforcement at higher voltages delivers high early benefit.
Storage and PV interactions are increasingly central; operators that still model static BESS or ignore V2G risk either over-curtailing renewables or under-valuing flexible assets.
Whole-system carbon and balancing-service savings strengthen the strategic case to align DSO flex procurement, ANM settings and ESO markets – a template other regions can adopt.