Energy optimization
myCoreAI is a complete, scalable HVAC optimization system that optimizes heating, cooling, and ventilation. The system uses a combination of cutting-edge artificial intelligence technology and engineering insights from the real estate industry.
Electricity ≤ 25% Heating ≤ 15% Cooling ≤ 15%
Spot price optimization
myLoadShift is using the thermal capacities in buildings and consumes electricity when the price is lower.
Electricity cost savings ≤ 35%
Energy optimization
myCoreAI is a complete, scalable HVAC optimization system that optimizes heating, cooling, and ventilation. The system uses a combination of cutting-edge artificial intelligence technology and engineering insights from the real estate industry.
Electricity ≤ 25% Heating ≤ 15% Cooling ≤ 15%
Spot price optimization
myLoadShift is using the thermal capacities in buildings and consumes electricity when the price is lower.
Electricity cost savings ≤ 35%
Our core solution, myCoreAI, reads data from buildings as well as external sources like weather and social data, and creates a unique algorithm to optimize each building according to that building’s specific conditions. The optimization works a little like if a human did it, the big difference being the number of parameters used and that myCoreAI sends optimized signals to the steering system every 15 mins, a human would generally do it far less often than that.
The performance of myCoreAI is constantly monitored to show the technical performance of the algorithm, as well as the building’s energy and comfort levels. The user can also interact with the system and override it if circumstances change.
The performance of myCoreAI is constantly monitored to show the technical performance of the algorithm, as well as the building’s energy and comfort levels. The user can also interact with the system and override it if circumstances change.
1
BMS System
Buildings connected to Myrspoven’s scalable system for continuous and autonomous optimization of the buildings. These aggregated buildings are further also connected to the digital trading platform (no.3)
2
Database
Myrspoven integrates into the buildings existing BMS system. The integration is a two-way integration allowing Myrspovens system to read and write into the BMS in a way harmonizing with the existing logic. The integration also includes a fallback solution putting the system back to default in case of a planned or unplanned shutdown. The cloud database is the heart of Myrspoven’s system, storing and organizing all data.
3
Weather
Myrspoven harvests any open-source data available that might improve the model’s predictive power. Whether data and utility tariffs are always a part of the input
4
Artificial Intelligence
Cutting-edge AI algorithms are applied to the data stored in the database. The result is a virtual building model that can be used to predict future energy use and indoor climate. The models are re-trained every night and are always improving.
5
Optimization
The optimizer uses AI models to calculate how the building should be operated to achieve the best indoor climate at the lowest possible cost. The client only defines a good indoor climate and sets the set-point boundaries that the optimizer is allowed to operate within.
6
The control strategy and new set-points are updated every 15 minutes.
energy savings
Electricity ≤ 25% Heating ≤ 15% Cooling ≤ 15%
Before and after myCoreAI
Before myCoreAI
Energy companies’ tariff systems for electricity, heat and cooling have become more unstable and complex over time. In practice, this means that it has become more difficult to perform energy optimization at the lowest possible cost.
After myCoreAI
Myrspoven’s solution enables forecasting of both energy costs and climate, which enables control adjustments that takes into account energy tariffs, flow and return penalty fees, price cuts and daily variations.
indoor temperature
Before and after myCoreAI
Before myCoreAI
There is no real control nor optimization of energy usage. The indoor temperature fluctuates inconstantly without any planning implemented or informed solutions.
After myCoreAI
Our customizable algorithms ensure that the indoor temperature is kept within a predefined range while taking into consideration outdoor temperature, building configuration, energy tariffs, and other factors.
benefits with myCoreAI
You are in Control
Best indoor climate
The customer is able to define the indoor climate. myCoreAI uses data collected onsite to teach itself how to adjust heat, cooling, and ventilation depending on prevailing external conditions (such as weather or wind) and on how the specific buildings are designed, used, and configured.
Big Data
Unique Insights
All data collected in real-time is saved into a database and uploaded into the building’s digital twin. This data is combined with other datasets generated from different energy providers, weather forecasting systems, etc, to generate models. About once per hour, new control signals are sent back via the connector to the BMS based on these predictions.
Artificial Intelligence
Energy forecasting
myCoreAI enables forecasting of both energy costs and climate ahead of time, which enables control adjustments that take energy tariffs into account. The model is upgraded and optimized every day as it learns from the data collected.
Generic & Scalable Solution
Easy to implement
Myrspoven’s team has developed a scalable system that, with the help of modern AI, enables continuous and autonomous optimization of complex buildings. myCoreAI is based on scalability and flexibility and is independent of the manufacturer in terms of both sensors and control systems.
You are in Control
Best indoor climate
The customer is able to define the indoor climate. myCoreAI uses data collected onsite to teach itself how to adjust heat, cooling, and ventilation depending on prevailing external conditions (such as weather or wind) and on how the specific buildings are designed, used, and configured.
Big Data
Unique Insights
All data collected in real-time is saved into a database and uploaded into the building’s digital twin. This data is combined with other datasets generated from different energy providers, weather forecasting systems, etc, to generate models. About once per hour, new control signals are sent back via the connector to the BMS based on these predictions.
Artificial Intelligence
Energy forecasting
myCoreAI enables forecasting of both energy costs and climate ahead of time, which enables control adjustments that take energy tariffs into account. The model is upgraded and optimized every day as it learns from the data collected.
Generic & Scalable Solution
Easy to implement
Myrspoven’s team has developed a scalable system that, with the help of modern AI, enables continuous and autonomous optimization of complex buildings. myCoreAI is based on scalability and flexibility and is independent of the manufacturer in terms of both sensors and control systems.
Spot price optimization
myLoadShift is an add on solution to myCoreAI which optimizes your building to consume electricity when the price is favorable. The spot prices are determined the day before, and myLoadShift predicts the building’s needs 48h in advance. The thermal inertia of the building can then be used to shift the consumption of electricity to when prices are favorable.
Some electricity needs cannot be shifted, such as lighting and most fans, but heating generally can. The thermal mass of buildings usually is 2-12h. myCoreAI, together with myLoadShift, will know the thermal mass of your individual buildings, which depends on, for example, materials, the behavior of the occupants, and the outdoor temperature. Therefore, the system can optimize consumption as well as your cost without jeopardizing the indoor climate.
To fully benefit from myLoadShift you must have heat pumps and/or cooling machines, and to make financial savings, you also have to be buying parts of your electricity from the spot market.
Electricity cost savings ≤ 35%
Benefits with myLoadShift
For you
myLoadShift saves you money since it allows your buildings to consume electricity at favorable prices. Given you have heat pumps and cooling machines, we see cost reductions exceeding 35% when we optimize them.
The size of your savings depends on the size of your buildings, how many heat pumps and/or cooling machines you have in your stock, and the inertia which decides how much energy we can shift.
The size of your savings depends on the size of your buildings, how many heat pumps and/or cooling machines you have in your stock, and the inertia which decides how much energy we can shift.
For the planet
By deploying myLoadShift together with myCoreAI in buildings, the real estate sector can be a significant part of the solution to the capacity problems in the electricity network.
Lowering consumption during peak hours when the demand is high, will result in lower peaks and reduced need for “bad” energy sources like oil and coal. Dynamic consumers also allow for a higher share of intermittent energy production like solar and wind.
Lowering consumption during peak hours when the demand is high, will result in lower peaks and reduced need for “bad” energy sources like oil and coal. Dynamic consumers also allow for a higher share of intermittent energy production like solar and wind.
For you
myLoadShift saves you money since it allows your buildings to consume electricity at favorable prices. Given you have heat pumps and cooling machines, we see cost reductions exceeding 35% when we optimize them.
The size of your savings depends on the size of your buildings, how many heat pumps and/or cooling machines you have in your stock, and the inertia which decides how much energy we can shift.
The size of your savings depends on the size of your buildings, how many heat pumps and/or cooling machines you have in your stock, and the inertia which decides how much energy we can shift.
For the planet
By deploying myLoadShift together with myCoreAI in buildings, the real estate sector can be a significant part of the solution to the capacity problems in the electricity network.
Lowering consumption during peak hours when the demand is high will result in lower peaks and reduced need for “bad” energy sources like oil and coal. Dynamic consumers also allow for a higher share of intermittent energy production like solar and wind.
Lowering consumption during peak hours when the demand is high will result in lower peaks and reduced need for “bad” energy sources like oil and coal. Dynamic consumers also allow for a higher share of intermittent energy production like solar and wind.
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Be part of the solution to the energy capacity problem
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