Smart meter half-hourly data for farm solar sizing

Half-hourly (HH) meter data is the single most important input for accurate UK farm solar PV sizing. Without HH data, system sizing is approximate; with it, sizing matches actual load patterns. Every farm considering solar should pull HH data before any design conversations. Here’s how.

What HH data shows

HH meter data records electricity consumption every 30 minutes — meaning a full year of data is approximately 17,520 readings. This level of granularity reveals: daily peak demand patterns (morning warmup, evening shutdown, weekend variation); seasonal variation (winter heating peaks, summer cooling, autumn drying); time-of-day demand alignment with PV generation curve; weekday vs weekend usage patterns; specific equipment cycling (dairy parlour washdown, grain dryer operation, livestock house ventilation).

Monthly or annual aggregated data doesn’t show any of this — it just shows total kWh per period.

Where to find your HH data

For SMETS2 smart meters (most UK farms now have these): the energy supplier portal exports HH data. Octopus, E.ON, British Gas, EDF, Scottish Power, OVO, SO Energy all provide HH export via their customer portals.

For older AMR meters: contact your energy supplier directly to request HH data export.

For sites without smart meters or HH-capable AMR: temporary HH data loggers can be installed for 1-3 months to capture representative load patterns. We provide this as part of standard scope where needed.

How HH data informs system sizing

The sizing algorithm uses HH data to model: total annual kWh consumption (basic annual demand); peak demand patterns (when does the farm consume most electricity); daytime baseload (typical kWh consumed during PV generation hours); seasonal peaks (when do the highest daily demands occur); self-consumption ratio at various system sizes (how much of generation would be self-consumed at 50 kW, 100 kW, 200 kW, etc).

This produces a sizing recommendation that maximises economic value: large enough to meet baseload but not so large that surplus must be exported under SEG at lower value.

Worked example: 200-cow dairy farm

A representative 200-cow Cheshire dairy farm. HH data analysis shows:

• Total annual consumption: 405,000 kWh
• Daily peak demand: 65 kW typically (parlour washdown + cooling)
• Daytime baseload (10am-4pm): 35 kW average
• Overnight baseload (10pm-6am): 18 kW (bulk tank cooling continuing)
• Weekend variation: minimal (parlour operates same hours 7 days)
• Seasonal variation: 12% peak in winter (parlour heat-trace)

Sizing recommendation: 320 kW PV install. At 88% self-consumption (typical for dairy with 24/7 cooling baseload), this captures 282,000 kWh per year at grid retail price plus 38,000 kWh exported under SEG. Annual saving £68,500. Simple payback 4.5 years before AIA.

Without HH data, the same farm might have been sized at 200 kW (under-sized — missed PV value) or 500 kW (over-sized — too much SEG export dilution).

What goes wrong without HH data

Common mistakes when sizing without HH data:

Over-sizing. Without seeing the actual daytime baseload, designers sometimes size based on total annual consumption — assuming much of it can be self-consumed. Reality: lots of consumption is overnight (cooling, lighting) when PV doesn’t generate. Over-sized systems export 40-60% under SEG vs the originally-modeled 80% self-consumption.

Under-sizing. Conversely, conservative sizing without HH visibility leaves money on the table. A dairy parlour with strong daytime baseload could justify 350 kW; without HH data, design might recommend 150 kW.

Missing seasonal patterns. Arable farms with autumn grain-drying peaks need different sizing approach than continuous-baseload operations. Without HH data, the seasonal pattern is invisible.

Wrong battery sizing. Battery storage decisions depend on the gap between daily generation peak and daily consumption peak. Without HH data, battery sizing is guess work.

What we deliver based on HH data

Every proposal we deliver includes: HH data analysis (loaded into our sizing model); recommended system size with rationale; expected self-consumption ratio; expected annual generation; seasonal generation curve; daily generation curve overlaid on consumption pattern; cost and payback at the recommended size; sensitivity analysis showing economics at smaller and larger system sizes.

This level of analysis is standard scope — we don’t charge for it. The desk feasibility study including HH analysis is free; we deliver within 7 working days of receiving the data.

How to send us your HH data

Log in to your energy supplier’s customer portal. Look for ‘energy usage’ or ‘data download’ or similar option. Request HH data for the past 12 months (some suppliers only retain 12 months online). Download as CSV format. Email to us at the address on the contact page.

If the export format isn’t clear or your supplier doesn’t offer easy export, contact us — we can help facilitate the data pull.

For sites without smart meter HH data, we can install temporary loggers for 1-3 months. Cost typically £0 (included in scope) if the project proceeds; £400-£800 if the data collection is standalone consultancy without subsequent install.