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First V1 home: January 1-May 9, 2026

First deployment, real data.

The first V1 dataset shows what changes when home energy stops being managed as separate devices. The headline result: in the best tested safe scenario, net energy cost was 62.7% lower than the flat-import, fixed-export baseline.

129 days in the first published V1 analysis period
62.7% lower net cost in the best safe scenario vs baseline
260.49 EUR net difference over the period

TLDR

The surprise was not only savings. It was tariff freedom.

Before this deployment, our working expectation was that a well-coordinated home could realistically move into the 15-26% improvement range in the right conditions. The first V1 dataset supports that direction, but the more important lesson is bigger: once the home can react automatically, the old "safe" tariff may no longer be the best tariff.

GridPassport changes the shape of the decision. An unmanaged home has to fear volatility because people cannot manually chase every price, solar and battery signal. A coordinated home can use volatility because it can keep re-evaluating what to buy, store, use, export and protect. In this dataset, the strongest safe scenario was not a fixed tariff. It was time-of-use import plus dynamic export.

The category promise is simple: 365 days a year, in short operating intervals, the home should re-check price, solar, load, reserve and comfort, then choose the best safe action available. The homeowner should not become a trader. The home should become volatility-ready: price movement becomes an input the system can use, not only a risk the homeowner has to avoid.

Tariff primer

Read this before the charts.

The case study compares tariff shapes, not just local tariff names. Import is electricity bought from the grid. Export is electricity sold or credited back to the grid.

Fixed

One predictable price.

The price is stable or smoothed. It is simple, but it gives the home fewer useful moments to react to.

Time-of-use

Known cheap and expensive windows.

The schedule is predictable. The home can plan around cheaper and more expensive parts of the day.

Dynamic

Price changes with the market.

The opportunity can be larger, but manual control becomes unrealistic. Automation has to read the signal.

Net cost

Import cost minus export revenue.

This is the number that matters in the article. Sometimes importing more can still produce a better net result.

Daily timeline

Load and PV moved every day.

The first deployment was not one stable operating condition. Winter demand, spring PV and a few unusual days created a moving problem that fixed schedules cannot handle well.

Jan 1 Feb Mar Apr May 9
Daily load Daily PV production

Evidence readout: the 129-day period moved from winter demand to spring PV surplus. That is why a fixed rule is weak: the household problem changes as weather, load and production change.

Three days that explain why a single static rule is weak
Day Load PV Import cost Export revenue Net result Grid charge Battery export
2026-01-21 30 kWh 62 kWh 4.98 EUR 12.38 EUR -7.40 EUR 23 kWh 33 kWh
2026-02-25 138 kWh 30 kWh 19.86 EUR 0.78 EUR 19.08 EUR 22 kWh 4 kWh
2026-05-05 25 kWh 120 kWh 2.04 EUR 13.11 EUR -11.07 EUR 8 kWh 25 kWh

Evidence readout: the three selected days show different jobs for the same home. One day rewards export timing, one day is mostly a high-load day, and one day asks the system what to do with solar surplus.

What was measured

The dataset covers one real GridPassport V1 home in Central Poland from January 1 to May 9, 2026. It contains household load, PV generation and scenario replays for import tariffs, export rules and GridPassport control strategies. The goal is not to claim a universal saving. The goal is to show what changes when home energy decisions are coordinated.

The home is a useful first test because it contains ingredients that are becoming normal in modern houses: household demand, PV production, storage and tariff choices that change the economics of timing. Across the period, the home consumed 6,407 kWh and produced 7,703 kWh from PV. It is the kind of home where the heavy side of smart home starts to matter.

House and dataset summary
Metric Value Why it matters
Analysis period Jan 1-May 9, 2026 129 days, covering winter demand and spring PV growth.
Total household load 6,407 kWh Enough day-to-day demand for timing and device priorities to matter.
Total PV production 7,703 kWh More annualized production than load, but not always at the right time.
Battery capacity 25 kWh nominal 21.25 kWh usable window The configured usable window is 85% of nominal capacity, before any battery-health derating.
Minimum SOC 15% The planner keeps a reserve floor instead of using the battery blindly.

Evidence readout: the house is not a laboratory ideal. It is a real home with normal modern ingredients: demand, PV, a usable battery window, a reserve floor and tariffs that make timing matter.

The headline result

The default baseline in this analysis is a flat import tariff with fixed export settlement and no GridPassport control: simple self-consumption. Over the period, that baseline produced a net cost of 415.19 EUR.

The best tested safe scenario was time-of-use import plus dynamic export with GridPassport safe mode. Its net cost was 154.70 EUR. That is 260.49 EUR lower, or 62.7%.

But the honest interpretation is more important than the big number. The 62.7% result combines tariff access and GridPassport control. If we compare within the same time-of-use import plus dynamic export scenario, GridPassport safe mode reduced net cost by 50.0%. In the dynamic import plus dynamic export scenario, it reduced net cost by 28.1%. In tariff setups where trading did not help, safe mode fell back to simple self-consumption.

How the scenario replay was set up

After the primer above, the replay combined three import shapes with two export shapes. The local tariff names matter less than the pattern homeowners will recognize in many markets as smart meters, dynamic pricing and solar export settlement evolve.

Tariff shapes used in the scenario replay
Shape How it behaves What GridPassport has to decide
Flat import One import price throughout the day. Use solar and battery primarily for self-consumption and reserve.
Time-of-use import Known cheaper and more expensive windows. Charge or avoid consumption in predictable windows without hurting comfort.
Dynamic import Import price can move with the market. React to changing prices without asking the homeowner to watch the curve.
Fixed export Export value is stable or monthly smoothed. Avoid over-optimizing exports when the reward is weak.
Dynamic export Export value changes by market interval. Decide when surplus should be used, stored or exported.

Evidence readout: the replay separates import shape from export shape. GridPassport is valuable when the home can use both sides of the tariff instead of optimizing only solar self-consumption.

Chart 1

Net cost by tariff scenario.

The best result came when the home had both useful import timing and dynamic export value. GridPassport safe mode avoided forced trading in scenarios where the model did not justify it.

Flat import + fixed export Fallback to self-consumption
Without GP 415.19 EUR
GP safe 415.19 EUR
Flat import + dynamic export Fallback to self-consumption
Without GP 431.88 EUR
GP safe 431.88 EUR
Time-of-use import + fixed export EMS + trading
Without GP 292.68 EUR
GP safe 274.98 EUR
Time-of-use import + dynamic export EMS + trading
Without GP 309.37 EUR
GP safe 154.70 EUR
Dynamic import + fixed export Fallback to self-consumption
Without GP 227.17 EUR
GP safe 227.17 EUR
Dynamic import + dynamic export EMS + trading
Without GP 243.78 EUR
GP safe 175.22 EUR

Evidence readout: the strongest safe result appears when predictable cheap import windows meet dynamic export value. Flat tariffs gave GridPassport less useful volatility to work with.

Period economics by scenario
Scenario Without GP net cost GP safe net cost Saving vs same tariff Readout
Flat import + fixed export 415.19 EUR 415.19 EUR 0.0% The safe planner did not force trading because the tariff shape did not reward it.
Flat import + dynamic export 431.88 EUR 431.88 EUR 0.0% Dynamic export alone was not enough when import stayed flat.
Time-of-use import + fixed export 292.68 EUR 274.98 EUR 6.0% The planner found value in import timing, even with fixed export.
Time-of-use import + dynamic export 309.37 EUR 154.70 EUR 50.0% The strongest scenario: cheap windows, dynamic export value and controlled battery use.
Dynamic import + fixed export 227.17 EUR 227.17 EUR 0.0% Dynamic import helped the base case, but fixed export limited trading value.
Dynamic import + dynamic export 243.78 EUR 175.22 EUR 28.1% A strong all-dynamic case, but lower than time-of-use + dynamic export in this period.

Evidence readout: the 50.0% figure is the within-scenario uplift for time-of-use import plus dynamic export. The 62.7% headline compares the best safe scenario with the flat-import, fixed-export baseline.

Why the best scenario is not just "use less grid"

A common mistake in home energy is treating grid import as the enemy. That is too simple. In the best scenario, GridPassport imported more energy than the no-GP case, but used the battery and export windows to make the total result better. The home did not win by minimizing one column. It won by optimizing the whole household outcome.

In the time-of-use import plus dynamic export scenario, the no-GP case imported 2,214 kWh and exported 3,482 kWh. GridPassport safe mode imported 4,090 kWh and exported 5,312 kWh. Import cost rose, but export revenue rose much more. Net cost fell from 309.37 EUR to 154.70 EUR.

Battery activity under GP safe mode
Scenario Grid charge Battery export Equivalent cycles
Flat import + fixed export 64 kWh 0 kWh 52.2
Flat import + dynamic export 454 kWh 481 kWh 77.1
Time-of-use import + fixed export 778 kWh 0 kWh 85.3
Time-of-use import + dynamic export 1,795 kWh 1,588 kWh 147.7
Dynamic import + fixed export 1,493 kWh 0 kWh 114.6
Dynamic import + dynamic export 1,779 kWh 989 kWh 143.8

Evidence readout: battery movement only matters if it improves the whole household result. GridPassport safe mode can use more cycles when the spread is meaningful, but it should not trade just because the battery is available.

Tariff prices

The useful decision is hidden inside the day.

A time-of-use import tariff gives predictable cheaper and more expensive windows. Dynamic export prices change by the market. GridPassport is useful because the home needs to read both price curves together with solar, load and battery reserve.

2026-01-21

High export spread afternoon

Dynamic export rose above the time-of-use import price in the afternoon. This is the kind of day where a battery can become an active home asset.

00 06 12 18 23
Time-of-use import price Dynamic export price
Lowest import: 0.121 EUR/kWh Highest export: 0.347 EUR/kWh

2026-02-25

High load, limited spread

The day was expensive mostly because the home needed a lot of energy and PV was not enough. Automation still protects the plan, but the price spread is less generous.

00 06 12 18 23
Time-of-use import price Dynamic export price
Lowest import: 0.121 EUR/kWh Highest export: 0.187 EUR/kWh

2026-05-05

Solar surplus, evening value

PV carried the day. The better question was what to store, what to export and what to keep for later, especially when export value improved in the evening.

00 06 12 18 23
Time-of-use import price Dynamic export price
Lowest import: 0.121 EUR/kWh Highest export: 0.189 EUR/kWh

Evidence readout: the price curves explain why daily automation is different from a timer. A useful action can depend on the spread inside a few hours, not only on whether the day is sunny.

Chart 2

Value was created across winter and spring.

The baseline was most expensive in January and February. Spring PV improved the picture for every scenario, but coordinated control still improved the outcome.

Jan 2026 129.13 EUR
Feb 2026 59.16 EUR
Mar 2026 36.39 EUR
Apr 2026 24.45 EUR
May 1-9 11.36 EUR

Evidence readout: January created the largest absolute improvement because the baseline cost was high. Spring still mattered because PV surplus created export and storage decisions.

Monthly net cost: baseline vs best safe scenario
Month Load PV Flat/fixed without GP Time-of-use/dynamic with GP safe Difference
Jan 2026 1,249 kWh 615 kWh 189.44 EUR 60.31 EUR 129.13 EUR
Feb 2026 1,144 kWh 701 kWh 158.05 EUR 98.89 EUR 59.16 EUR
Mar 2026 1,874 kWh 2,695 kWh 42.69 EUR 6.30 EUR 36.39 EUR
Apr 2026 1,800 kWh 2,840 kWh 37.63 EUR 13.18 EUR 24.45 EUR
May 1-9 341 kWh 852 kWh -12.61 EUR -23.97 EUR 11.36 EUR

Evidence readout: savings did not come from one lucky day. The improvement appears across winter and spring, with the largest EUR difference in January.

Chart 3

The problem changed with the season.

In January and February, the home needed to manage demand. In March, April and early May, PV surplus became the dominant operating question.

Jan 2026
Load 1,249 kWh
PV 615 kWh
Feb 2026
Load 1,144 kWh
PV 701 kWh
Mar 2026
Load 1,874 kWh
PV 2,695 kWh
Apr 2026
Load 1,800 kWh
PV 2,840 kWh
May 1-9
Load 341 kWh
PV 852 kWh

Evidence readout: by March and April, PV production overtook load. That does not remove the need for coordination; it changes the decision from buying less to routing surplus better.

Why this matters beyond this test home

The test was run in Central Poland, but the operating problem is not local. The same pattern appears wherever homes combine solar, batteries, heat pumps, cooling, EV charging, smart meters and time-varying prices. Tariff labels change by country. The household job is the same: decide when to buy, store, use, export and protect energy.

The old smart-home promise was convenience: turn things on and off. The new problem is heavier. A modern home needs to decide when to import, when to charge, when to export, when to protect reserve and when to leave comfort alone. That is why GridPassport describes the category as Home Power Automation rather than another dashboard for energy monitoring.

The takeaway

Before this deployment, the working question was whether coordination could move a real home into the 15-26% improvement range suggested by earlier research and modelling. The answer is directionally yes, but the bigger lesson is tariff freedom. Once the home can respond in short operating intervals, variable prices stop being only a risk and become something the home can use.

This is the practical version of becoming less fragile to volatility. Without automation, volatility usually means more uncertainty for the homeowner. With GridPassport, volatility can become a source of better timing: the home can buy, store, use or export when the conditions are worth it, while still respecting reserve and comfort.

GridPassport is not just trying to make today's tariff slightly cheaper. It is trying to make the home capable of choosing and surviving a better tariff. That is the bridge from ordinary HEMS to Home Power Automation.

Limits and next proof points

This is early evidence from one home and one operating period. It should be used as proof that the category is real, not as a promise that every customer will see the same economics. The next proof points should include more homes, more tariff structures, explicit degradation accounting, comfort outcomes, reserve outcomes and hardware compatibility data.

How to read the evidence
Question Responsible answer
Is this a guaranteed saving? No. It is a first V1 deployment and scenario analysis.
What is included? Import cost, export revenue, net cost, energy movement and tariff scenarios.
What is excluded? Hardware cost, installation, subsidies, tax treatment and explicit battery degradation cost accounting.
What is the practical lesson? The relevant question is not whether one device is smart. It is whether the whole home has enough context to make one good energy decision.
What does this mean for system design? PV, storage, heating, cooling and charging should be specified with coordination in mind, because the bill reflects the combined behavior.

Founding homes

If your home has PV and a home battery, this is the layer it is missing.

GridPassport is looking for early homes and partners who understand that the future of smart home is not more buttons. It is a home that can act on prices, solar and comfort without turning the homeowner into an operator.

Join founding members

FAQ

Questions this document should raise.

Does this case study prove every home will save 62.7%?

No. The 62.7% figure compares the best tested safe scenario with a flat import and fixed export baseline for one V1 home over one period. Results depend on hardware, tariff design, weather, household demand, export rules and battery economics.

Why did the best GridPassport scenario import more energy?

Because the useful metric is not minimum import. It is total household outcome. In the best tested scenario, the planner used the battery and tariff spread to create more export value while keeping the net cost lower.

Are battery degradation and hardware costs included?

Hardware, installation, subsidies and tax treatment are outside this calculation. The control logic does pay attention to battery round trips and round-trip losses: it should only add charging and discharging when the expected value is clearly better than preserving the simpler battery path.

Can GridPassport limit energy arbitrage if local rules require it?

Yes. GridPassport can be configured to avoid exporting more energy than the home produced over the relevant period. In this V1 data, the main conclusion did not depend on unlimited arbitrage. The bigger effect came from tariff shape and coordinated timing; the export cap matters more when a home has unusually large storage and wide market spreads.

Where was the test conducted?

The first V1 test home is in Central Poland, because that is where the founding team lives and can observe the system closely. The exact tariffs are local. The operating problem is broader: homes with PV, batteries, heating, cooling or EV charging need to decide when to buy, store, use, export and protect energy.

Sources

References and context.

The operational dataset used for this article is the internal GridPassport V1 marketing dataset generated for January 1-May 9, 2026. External sources provide tariff and market context.