QLines Energy Intelligence
AI-Assisted Energy Optimization & Remote System Management. A unified platform vision connecting energy analysis, expert-informed renovation scenarios and remote management of connected energy systems.
Analyze & Plan
Bring building and consumption data together and compare renovation scenarios with transparent assumptions.
Consumption history per building and meter
Locations, electricity, water, gas and heating meters, readings and costs.
Utility bill ingestion and validation
Photos or PDFs of bills are read by OCR and checked against the recorded meter readings.
Building profiles
Building data such as area, year of construction, envelope and heating system as the basis for scenarios.
Renovation scenario comparison
Heat pump, PV, storage and insulation measures side by side, with investment, running cost, lifecycle cost and CO₂.
Financing and subsidy assumptions
Funding and financing entered as explicit, editable assumptions, never as promised amounts.
Explainable, human-reviewed summaries
AI-assisted plain-language summaries of the calculated results, reviewed by a qualified person before they are shared.
Transparent energy calculations
Heat pump versus gas running cost, PV yield and payback, heating load and more, with every formula and source shown.
Engineering first. Results come from traceable calculations with visible assumptions; AI explains them and never invents numbers. Energy Intelligence supports qualified energy advisors and does not issue official documents such as an iSFP.
Connect & Monitor
Connect devices and energy systems, follow their health and performance, and manage them remotely. This layer is EnergyOS.
Agent-based device connectivity
A lightweight agent (for example on a Raspberry Pi) connects each device over an encrypted connection with its own device token.
Energy system integration
Inverters, heat pumps, batteries, EV chargers and smart meters connect through standard energy protocols such as Modbus, SunSpec, EEBus and OCPP.
Device health telemetry
CPU, memory, disk, temperature, load and uptime, reported at a set interval and shown as history.
Energy telemetry
Power, energy, temperatures and operating states of connected energy systems, next to the device health data.
Network quality tests
Scheduled or on-demand latency, packet loss, DNS, HTTP and bandwidth tests per device.
Remote commands
Commands run on the device with a time limit; output and exit code come back to the dashboard and are logged.
Alerts
Threshold alerts for high CPU, temperature, disk use, latency, packet loss and devices going offline, in the dashboard and by e-mail if you turn it on.
Remote configuration
Heartbeat, telemetry interval and test schedule set from the dashboard.
Optimize & Improve
Compare what was predicted with what is measured, explain deviations and recommend the next step.
Forecast versus measured consumption
Compare the consumption a scenario predicted with what the meters and devices measure.
Deviation detection and explanation
Deviations are flagged with possible causes for a person to check.
Recommendations
Suggested adjustments or further measures, each with its assumptions.
Control and automation
Consented, safe control workflows for connected energy systems.
Scenario Comparison
Four options for the same house, side by side.
| Scenario | Investment after subsidies | Energy cost per year | Lifecycle cost (20 years) | CO₂ per year | Uncertainty |
|---|---|---|---|---|---|
| Current state: gas boiler20,000 kWh gas, 4,000 kWh household electricity | €0 | €3,480 | €69,600 | 5.5 t | ±10 % |
| Heat pump replaces the gas boilerAir-source, JAZ 3.3, 50 % subsidy | €16,000 | €2,750 | €71,100 | 3.6 t | ±15 % |
| Heat pump plus 10 kWp PV30 % self-use, feed-in 7.7 ct | €31,000 | €1,330 | €57,600 | 2.5 t | ±20 % |
| Insulation first, heat pump laterHeat demand −30 %, JAZ 3.6 | €46,000 | €2,230 | €90,500 | 2.9 t | ±25 % |
Sample figures for an example single-family house (150 m², 20,000 kWh gas and 4,000 kWh household electricity a year). Prices per kWh: gas 11 ct, electricity 32 ct, heat pump tariff 27 ct, feed-in 7.7 ct. CO₂: 0.20 kg per kWh gas, 0.38 kg per kWh grid electricity. Lifecycle cost = investment + 20 years of energy cost at constant prices. Not a quote: a real report uses your building's data.
Questions About Energy Intelligence
What is QLines Energy Intelligence?
A platform that connects three steps: analyzing building and consumption data to plan measures, managing devices and energy systems remotely, and comparing predicted with measured results to improve them.
How do I get access?
Request access on the contact page with a short description of your use case. We review every request and reply by e-mail with the next steps.
Does Energy Intelligence replace an energy advisor?
No. It supports qualified energy consultants and engineers. It does not produce official documents such as an individual renovation roadmap (iSFP), and results are reviewed by a qualified person.
Which devices and energy systems can be connected?
Remote devices such as a Raspberry Pi run the lightweight QLines agent; inverters, heat pumps, batteries, EV chargers and smart meters connect through standard energy protocols, listed on the Technology page.
Bring Energy Intelligence to Your Buildings
Tell us which data, devices or decisions you want to improve. We reply by e-mail.