Apps

SHED

Schedule – simplest possible  .controls-algorithms application

Function: The system is controlled by switching the systems on and off based on a predefined schedule.

Added value:

 - Energy savings through reduced operation

- Switching off the systems, e.g. at weekends, on public holidays or during company holidays

CURV

Heating / cooling curve incl. night setback

Function: The heating curve algorithm dynamically adjusts the flow temperature setpoints to the outside temperature and weather forecasts. This achieves energy savings, avoids inefficient static setpoints and improves room comfort. 

Added value:

• Optimisation: Adjustment of indoor temperatures based on weather conditions. 
• Energy saving: Night setback for inactive schedules. 
• Predictive control: Particularly effective for systems with high thermal inertia, such as underfloor heating, to prevent overshoots and increase efficiency

FROG (Free cooling)

Optimised operation of ventilation systems

Function: The free-cooling algorithm uses cool night air to reduce the building temperature and minimise energy consumption while ensuring the comfort of users.

Added value:

- Energy saving: Activates fans for night cooling when this is more cost-effective than using more energy-intensive chillers (like compression chillers) during the day.

- Comfort: Prevents uncomfortably cold or warm offices in the morning.

- Environmentally friendly: Practical solution for buildings with high cooling requirements in summer. 

HERO (Heat Recovery Optimisation)

Optimised operation of ventilation systems

Function:

The HERO algorithm calculates the most efficient supply air temperature for a ventilation unit that can be used for both heating and cooling a building. The supply air temperature is dynamically adjusted to optimise the extract air temperature:

              - If the extract air temperature is too low, the supply air temperature is increased.

- If the extract air temperature is too high, the supply air temperature is lowered.

This control loop continues until heat recovery is utilised to the maximum and active heating or cooling can be avoided.

Added value:

- Energy saving: Minimises heat loss and reduces energy consumption through optimised heat recovery.

- Cost efficiency: Avoids unnecessary heating or cooling processes and reduces operating costs.

- Comfort: Ensures an even temperature in the building without additional strain on radiators or cooling systems.

WASP (Weather-predictive Temperation-Mode Setter)

Optimised operation of cooling/heating systems

Function: The WASP algorithm optimises heating and cooling systems with high thermal inertia by dynamically adjusting thresholds based on 48-hour weather forecasts. 

- Prevents inefficient heating and cooling cycles through precise decision making between modes. 

- Decisions are fixed for 24 hours and then re-evaluated based on new forecasts. 

- Night setback limits operation outside working hours (8am-6pm), except in extreme weather conditions. 

Added value: 

- Increased efficiency: Reduces frequent changes between heating and cooling, which minimises energy losses, especially in systems such as concrete cores. 

- Cost reduction: Reduces unnecessary heating and cooling system activity through predictive control. 

- Improved comfort: Ensures stable temperatures during working hours and prevents temperature fluctuations.

ARA (Adaptive indoor climate algorithm)

Optimised operation of schedule-based systems

Function:

The ARA algorithm learns how long a room needs to reach the desired temperature and adjusts the schedule accordingly.

- Ensures that rooms reach the target temperature exactly at the desired time.

- Optimises operation by precisely timing the heating or cooling process.

Added value:

- Improved comfort: Rooms are at the right temperature at the right time, without delay.

- Energy savings: Minimises energy losses compared to fixed schedules.

- Reduced peak loads: Prevents all consumers from becoming active at the same time by switching to operation at staggered times.

BEE: Blind Control Algorithm

Function:
The Blind Control Algorithm determines the optimal position of blinds in a building to enhance energy efficiency and comfort.

• Uses blinds at night to retain heat during winter or release heat during summer.
• Adjusts blinds to optimize solar gains by increasing or decreasing sunlight exposure.
• Maintains user input by delaying automated changes after manual adjustments.

Added value:

• Energy Efficiency: Reduces heating and cooling demands by leveraging solar gains and insulation.
• Comfort Improvement: Ensures consistent indoor temperatures by minimizing unwanted heat gains or losses.
• Versatility: Suitable for any building with controllable blinds integrated into our platform.

DODO: Decentralized Occupancy-Driven Optimization

Function:
The DODO algorithm optimizes buildings equipped with occupancy detection or counting mechanisms.

• Reacts in real-time to occupancy changes, making it ideal for systems with short reaction times, such as ventilation systems.
• Combines multiple occupancy detection zones into one value if the ventilation zone is larger than a single occupancy zone.
• Each combined occupancy zone can have its own occupancy limit, above which the ventilation activates or increases its volume flow.

Added value:

• Efficient Ventilation: Activates ventilation only when needed, saving energy and enhancing comfort.
• Flexibility: Adapts to differently sized occupancy zones with individual thresholds.
• Real-Time Optimization: Dynamically adjusts the system to current building usage.

ORC: Optimized Room Climate Control Algorithm

Function:
The ORC algorithm addresses the issue of user-set temperature settings that result from discomfort due to short-term weather conditions.

• Automatically halves user settings after a predetermined time period to reset inappropriate adjustments.
• Operates within fixed standard setpoints provided by room control units, where users can only increase or decrease within a defined range.

Added value:

• Energy Efficiency: Prevents long-term inefficiencies caused by improper settings, saving energy.
• Enhanced Comfort: Ensures the room climate returns to an optimal and efficient level.
• User-Friendly: Automatically adjusts settings without requiring user intervention.

PRAWN: Predictive Heating Curve Weather Compensation

Function:
The PRAWN algorithm dynamically adjusts the flow temperature setpoint based on historical data and weather forecasts to optimize energy use in heating and cooling systems.

• Learns heating and cooling demands at different outdoor temperatures from at least 3 months of 15-minute-resolution data during the heating season.
• Adjusts the flow temperature to minimize simultaneous heating and cooling, improving overall system efficiency.
• Can operate in a simplified variant when sufficient training data is unavailable or incorporate room temperature measurements for enhanced accuracy.

Variants:

• Uses room temperature sensors to automatically increase flow temperature if one room’s temperature drops below a defined threshold.
• Can be implemented in projects with room temperature sensors, even without sufficient historical data.

Added value:

• Energy Efficiency: Prevents energy loss due to simultaneous heating and cooling (e.g., floor heating and ventilation).
• Optimized System Performance: Enhances the efficiency of chillers and heat pumps.
• Flexibility: Adapts to data availability and system configurations, offering simplified or advanced variants.
• Comfort Improvement: Maintains indoor comfort by using real-time room temperature feedback where available.