Calculating grid congestion: from interval data to an investment decision
A useful grid-congestion analysis shows not only whether a limit is reached, but when, why and which intervention actually resolves it.
PeakPilot editorial team
Energy simulation and decision-making
Table of contents
Why connection capacity alone is not enough
Grid congestion becomes tangible at a business site when import or export demand collides with available transport capacity at specific moments. Annual totals hide those moments. Even the highest measured demand does not explain which processes coincided or whether an intervention merely shifts the constraint.
Start with a timeline. Place contracted transport capacity next to actual load and mark import and export limits separately. This creates a reproducible baseline: how many breaches occur, how long do they last and how much energy sits beyond the limit?
The minimum dataset for a dependable analysis
Quarter-hourly connection data is the foundation. Add contract limits, operating hours and known changes to production or property use. Model major controllable assets separately, including charging hubs, solar generation, heat pumps and a BESS.
Check time zones, missing intervals and units before calculating. A daylight-saving shift or an energy profile interpreted as power can distort the exact peaks on which the decision depends. Record every correction so an adviser or lender can review the same input.
- Meter data at fifteen-minute resolution or finer, with complete timestamps
- Separate contractual limits for grid import and export
- Power, availability and control strategy for flexible assets
- Operational constraints such as departure times and minimum production
Model interventions as scenarios, not isolated measures
Compare an unchanged baseline with the planned situation first. Then add interventions one by one: smart charging, power control, curtailment or battery storage. A combined scenario is useful only when it remains clear which measure resolves which part of the peak.
Use the same period and operational constraints in every scenario. This prevents a favourable result caused by vehicles leaving undercharged or production being reduced silently. A scenario is valuable only when it is technically and operationally feasible.
Look beyond a single maximum peak
Report the highest peak together with the number of limit breaches, their duration, energy beyond the limit and the moments at which they occur. A short exceptional spike may need a different intervention from a daily plateau lasting several hours.
Inspect side effects as well. Limiting grid import can create more export at another moment, while a battery may lack enough available energy to cover every peak. The timeline reveals these interactions and keeps a context-free KPI from driving the decision.
Turn the analysis into an auditable decision
Connect every scenario to a specific decision: can the expansion fit within the current connection, is phasing required, or should a flexible asset be investigated? Record assumptions, source data and limitations. That makes clear which new information could change the decision later.
For battery storage, solving the technical peak is only the start. Economic value also depends on dispatch strategy, degradation and financing. Evaluate those factors in the same scenario before preparing an investment proposal.