Case studies

What the output actually looks like.

Real screening examples showing how LIFO queue analysis and attrition modelling change investment decisions.

Investor screening

99 MW BESS: When headline curtailment tells the wrong story.

North West GSP

Infrastructure fund evaluating a 99 MW BESS project at a constrained GSP in the North West. The developer's broker memo quoted 20% headline curtailment. LIFO analysis revealed 7 projects ahead totalling approximately 735 MW. But temporal profiling showed constraints concentrated during daytime solar peaks, precisely when a BESS would be charging, not exporting.

Key result: The effective revenue impact was 3-6%, not 20%. The fund proceeded to full due diligence.

20%Headline
3-6%Effective
#8Queue position

Curtailment Report

99 MW BESS | North West GSP

Headline Curtailment20%
Effective Curtailment3-6%
Queue Position#8 of 15
Projects Ahead7 projects

Temporal profiling reveals constraints concentrated during daytime solar peaks. BESS charging profile aligns with generation window, reducing actual export curtailment.

Portfolio screening

12-site portfolio: Attrition modelling changes the ranking.

Renewables fund screening 12 prospective BESS sites across central and southern England. Initial curtailment estimates from information memorandum ranked sites one way. LIFO analysis with attrition scenarios produced materially different ranking. Three marginal sites moved to top tier. Two attractive sites had queues with high completion probability (less attrition upside).

Key result: The fund re-prioritised their pipeline and saved months of due diligence on the wrong sites.

12Sites screened
5Rankings changed
3Days total delivery

Portfolio Re-ranking

Before and after attrition modelling

Site A
Before: Rank 4
After: Rank 1
Site B
Before: Rank 1
After: Rank 5
Site C
Before: Rank 8
After: Rank 2
Site D
Before: Rank 2
After: Rank 7
Site E
Before: Rank 11
After: Rank 3
Developer screening

200 MW data centre: Transmission capacity validation.

Data centre developer evaluating two Midlands locations for 200 MW facility. Both had grid offers. Transmission modelling revealed Location A's substation approaching thermal limits due to queued renewables, reinforcement not until 2029. Location B had clearer path with lower congestion and earlier upgrades. Balancing Mechanism Bid Offer Acceptance modelling was used to assess grid access economics at both locations.

Key result: The developer chose Location B, avoiding a potential 18-month delay and £400k abortive costs avoided.

200MW Capacity
2Locations compared
18Months delay avoided

Location Comparison

Location A

Thermal HeadroomCritical
Queue Position8th of 18
Reinforcement Date2029
Congestion RiskHigh

Location B

Thermal HeadroomGood
Queue Position3rd of 11
Reinforcement Date2027
Congestion RiskLow
International programme

Greece BESS programme: Viability assessment across regulatory regimes.

A European energy fund was evaluating a multi-site BESS development programme in Greece. The regulatory framework for grid connections and curtailment compensation differs significantly from the GB model. The fund needed to understand whether curtailment risk assessment methodologies could be adapted, and whether the programme's financial model reflected realistic grid access assumptions.

Quantail assessed the programme against the Greek regulatory framework including ADMIE's grid access rules, RES integration targets, and the curtailment compensation mechanism. The analysis included solar curtailment forecasting based on planned project build out nationally, overlayed with grid infrastructure upgrades planned for the next 10 years. The analysis identified material differences in queue priority logic compared to GB LIFO, and highlighted where the developer's assumptions were optimistic on capacity access timelines.

Key result: The fund revised its entry pricing and negotiated revised connection milestones. Two of the five sites were deprioritised based on grid congestion risk.

5Country wide assessment
2Business Case defined
10yrModelling scenarios

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