Solar · Storage · Flexible loads
HyPBriQ uses research-grade models to turn uncertainty in solar, storage and flexible loads into decisions you can take to the board: where to build, how big, and what it earns.
Built on research-grade methods and research-based insights.
Quantifying uncertainty. Elevating confidence.
Sizing · one question, 16 answers
Both, and that's the trap. We ran the same spring day through 16 storage designs. Add megawatts or megawatt-hours alone and the result stalls.
What if? · try it
Move the two inputs that matter most. In the base case, a modelled 1 MW / 2 MWh battery pays back in 8.0 years after discounting, and revenue moves the result more than any other assumption.
Model: net revenue is an assumption you set, not a measured result. It falls 2% a year in this model. €12k O&M a year, 7% discount rate, 15-year life, no battery replacement. Illustrative, not a forecast.
Technology choice
It depends on how long you need to store the energy.
How many hours do you need to store?
Investment per kW of power
Indicative costs per kW: batteries €300 + €250/kWh, pumped hydro €1,500 + €60/kWh, hydrogen €3,000 + €10/kWh. Actual costs vary by project. This compares investment only. It leaves out energy losses, lifetime and running costs: for example, a Li-ion battery returns about 88% of the electricity stored, and hydrogen about 29%.
Research-based insights
One data point rarely settles a decision. These parameter sweeps show where each answer holds and where it breaks. Open a card to see the map and its 16 cases.
Investment
8.0 years in the base case. At low revenue and high capex, it isn't repaid in 15.
Cost
6.3 hours at €250/kWh. Cheap enough, they skip pumped hydro altogether.
Curtailment
22% with 1 GW / 3 GWh. Reaching the top corner takes both.
Surplus
1,898 hours a year with 6 GW solar and 4 GW wind. Solar crowds into the same middays.
Duck curve
10 GW daily swing with 12 GW of solar and no storage, on a 6.7 GW peak system.
Battery ageing
9.9 → 3.2 years of life going from 25 °C to 45 °C, at one full cycle a day.
Grid frequency
49.4 Hz with 5% fast battery power. Without it, 48.9 Hz: below the 49 Hz load-shedding limit.
Hydrogen
29% of the electricity comes back, where a Li-ion battery returns 88%.
Electric vehicles
0% extra feeder peak for 400 EVs, against +29% with plug-in-and-charge.
Demand response
−20% evening peak. Past about 15% shifted, the night hours form a new peak.
Solar homes
35% → 85% self-sufficiency with a 10 kWh battery on 5 kWp of panels.
Smart buildings
23.8 °C indoor peak with the AC off 18:00–21:00, after pre-cooling a well-insulated home.
All maps are illustrative HyPBriQ models. Each states its assumptions in its footer.
Advisory · optimization · execution
We help energy, industrial and infrastructure clients turn technical uncertainty into investment-grade decisions, operational savings and new revenue streams.
For projects that need a rigorous case before capital is committed.
For owners who want more value from what is already installed.
For operators turning flexibility into savings and income.
For teams that want the capability in-house.
For teams bridging analytics, operations and investment.
In development
We're building a browser workspace for European power market intelligence, without waiting for a custom report. It isn't open yet. Planned features:
About
HyPBriQ was founded by Dr. Panagiotis Barmpoutis, an award-winning data scientist and AI engineer, and an elected Assistant Professor in the Department of Mechanical Engineering at the International Hellenic University.
The team includes experienced engineers and specialists who combine advanced data simulation with practical operational strategy, to de-risk renewable investments, optimize dispatch and turn complex energy systems into high-yielding assets.
Contact
Share your project context and we'll help quantify and mitigate the risk.
