Predictive building control system and method for optimizing energy use and thermal comfort for a building or network of buildings
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Solution Overview
Problem
Existing building HVAC control systems lack granular thermal zone-level comfort control while optimizing overall energy use, failing to meet the complex thermal comfort requirements of modern buildings and networks.
Innovation Solution
A predictive building control method and system that uses a processor to determine set points for HVAC systems based on desired temperature ranges, forecast ambient temperatures, and historical data, while also considering demand response signals to minimize energy use and optimize energy management across thermal zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional BEMS uses predefined set points scheduled by building operator, then the system is simple to operate, but it cannot optimize energy use based on anticipated operating conditions and weather changes
Solution Approach 1:
The system performs preliminary actions by using weather forecasts and predictive models to determine optimal HVAC set points in advance before actual weather conditions occur. The predictive model anticipates future operating conditions and pre-calculates energy-efficient set point trajectories, allowing the building to proactively adapt to upcoming weather changes rather than reactively responding to them.
Solution Approach 2:
The system transitions from static predefined set points to dynamic predictive set points that continuously adapt to changing weather conditions and building operating conditions. The predictive model generates time-varying set point trajectories that optimize energy use throughout the forecast period, making the control system flexible and responsive to real-time conditions while maintaining simplicity through automated calculations.
2Reliability
If the system controls each thermal zone independently with granular comfort requirements, then thermal comfort is improved, but energy optimization becomes more difficult
Solution Approach 1:
The system merges the control of multiple thermal zones into a unified predictive optimization problem. Instead of independently controlling each zone, the predictive model simultaneously considers all thermal zones and their interconnections, generating coordinated set point trajectories that optimize overall building energy use while satisfying the thermal comfort requirements of each individual zone. This integrated approach simplifies the control architecture while maintaining granular comfort control.
3Productivity
If predictive modeling with weather forecasts is implemented, then energy optimization is improved, but the system requires more complex modeling and computation
Solution Approach 1:
The system introduces a predictive model as an intermediary between weather forecasts and HVAC control. This intermediary component processes weather forecast data and building operating conditions through trained predictive models to generate optimal set point trajectories. The predictive model acts as a mediator that translates complex weather and operational data into simplified control recommendations, making the overall system more manageable despite the complexity of underlying models.
Data Source
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AI summary
A method for controlling temperature in a thermal zone within a building, comprising: using a processor, receiving a desired temperature range for the thermal zone; determining a forecast ambient temperature value for an external surface of the building proximate the thermal zone; using a predictive model for the building, determining set points for a heating, ventilating, and air conditioning ("HVAC") system associated with the thermal zone that minimize energy use by the building; the desired temperature range and the forecast ambient temperature value being inputs to the predictive model; the predictive model being trained using respective historical measured value data for at least one of the inputs; and, controlling the HVAC system with the set points to maintain an actual temperature value of the thermal zone within the desired temperature range for the thermal zone.