ADQUIO ANALYTICS · USE CASES
Energy tells only part of a hotel’s story. Occupied rooms and the services in operation provide the context needed to interpret it.
This article presents a use case with simulated data. The main image is a generated illustration; the screenshots show the Adquio Analytics interface.
The scenario: Solar Hotel
The example hotel has 80 rooms, 28 employees and 4,200 m². Solar generation and storage operate alongside HVAC, the kitchen, laundry, lifts and domestic hot water.
Combining hotel activity with energy demand helps compare days with different occupancy and investigate services that keep running even when fewer guests are present.
Questions this example helps answer
Visualisations become useful when they support a specific decision. This example helps explore the following questions:
How does demand change with hotel occupancy?
What roles do hot water, the kitchen and laundry play?
When does activity coincide with solar generation?
Technical reference for the example
These values define the reference scenario. They are simulation parameters, not a specification for a verified customer installation.
| Parameter | Model reference |
|---|---|
| Reference floor area | 4200 m² |
| Team | 28 people |
| Photovoltaics | 120 × 400 W modules = 48 kWp |
| Inverters | 3 × 20 kW |
| Nominal battery capacity | 120 kWh |
| Nominal storage voltage | 51.2 V |
| State-of-charge window | 20–90% |
| Storage efficiency | 96% in each direction |
| Simulator update interval | 60 seconds |
| Weather update interval | 60 minutes |
| Rooms | 80 · 2 guests per room |
| Model occupancy | 66% on weekdays · 82% at weekends |
| Laundry | 4 × 4.2 kW washers and 3 × 6.5 kW dryers |
| Domestic hot water | 4,000 l tank · 60 °C setpoint · 60 kW thermal output · COP 2.8 |
| Kitchen and lifts | 35 kW kitchen · 2 × 4.5 kW lifts |
The dashboards, explained
Each view answers a different question. Select a thumbnail to open a large image; use the viewer to move to the next dashboard or switch to full screen.
Energy overview
Read solar production, hotel demand, grid supply and storage together.
How to read it. Compare equivalent occupancy and service periods before judging a change in consumption.
Occupancy and services
Explore occupied and available rooms, guest and staff presence, and the relationship between activity and electricity demand.
How to read it. Occupancy provides context that a power curve alone cannot supply.
Hot water, water and laundry
Follow domestic hot water temperature, active washers and dryers, and water flow.
How to read it. Use the process context to investigate schedules and service demand; a variation alone is not proof of a fault.
These views were prepared in an isolated Analytics instance by running the supplied simulator. No connections or writes to real equipment were made. They are not recorded historical data from an installation.
From example to your installation
The same approach can be adapted to the variables and equipment available in your project. Start with the decision to support, then choose the appropriate measurements, units, periods and visualisations.
DataSource collects and prepares the data, and Adquio Analytics presents it in dashboards. Review measurement coverage and keep the same boundary when comparing days, areas or equipment.
The screenshots illustrate analytical possibilities. They do not verify savings, operational results or automatic control of equipment in this example.
What do you need to understand about your installation?
Tell us what you want to measure, compare or present, and we will help define a useful view for your team.
