HVAC Setpoint Trajectory Control for Building Energy Budgets
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Solution Overview
Problem
Building management systems (BMS) face challenges in efficiently managing power consumption, particularly during peak usage times, as they lack integrated solutions to optimize energy use across various subsystems like HVAC, lighting, and elevators, leading to increased energy costs and greenhouse gas emissions.
Innovation Solution
A smart building management system that integrates with smart grid components, using a controller to observe and calculate cooling power use, apply linear operators to transform temperature setpoints, and optimize energy use by transforming observed power usage into target power usage, thereby reducing energy consumption during peak hours.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If demand limiting is utilized during peak usage times to reduce energy costs, then energy consumption and costs are reduced, but building comfort and temperature control deteriorate
Solution Approach 1:
The system performs pre-cooling of the building during off-peak hours before the anticipated peak demand period. By lowering the temperature setpoint in advance (e.g., from 72°F to 68°F), the building's thermal mass stores cooling energy, allowing the HVAC system to reduce or shut off during peak hours while maintaining comfort. This preliminary action resolves the contradiction by preparing the system in advance to handle peak demand without compromising comfort.
Solution Approach 2:
The system dynamically changes the temperature setpoint parameter based on the demand limiting schedule. During pre-cooling, the setpoint is lowered below the normal comfort level; during the demand limiting period, the setpoint is raised or the system is shut off; and after the period, the setpoint returns to normal. These parameter changes allow the system to trade temporary temperature deviations for reduced peak energy consumption while maintaining overall comfort standards.
2Use of energy by stationary object
If temperature setpoints are adjusted to reduce cooling power use during limited power periods, then energy costs are reduced, but temperature control precision and comfort deteriorate
Solution Approach 1:
The system adjusts temperature setpoints in advance of the limited power period to pre-cool the building. By lowering the setpoint before the demand limiting period begins, the building's thermal mass accumulates cooling energy, which compensates for the reduced cooling capacity during the limited power period. This preliminary action maintains temperature control precision during the critical period when power is limited.
Solution Approach 2:
The system creates a thermal cushion by pre-cooling the building structure and contents before the demand limiting period. This thermal cushion acts as a buffer that maintains comfortable temperatures during the period when cooling power is reduced or shut off, thereby preserving temperature control precision without requiring continuous full-capacity cooling operation.
3Power
If pre-cooling is performed before peak usage times, then peak demand is reduced, but energy consumption during pre-cooling period increases
Solution Approach 1:
The system optimizes the pre-cooling temperature setpoint parameter to balance the trade-off between peak demand reduction and pre-cooling energy consumption. By carefully selecting the pre-cooling setpoint (e.g., 68°F rather than excessively low temperatures), the system achieves sufficient thermal storage to cover peak periods while minimizing the energy required for pre-cooling. This parameter optimization resolves the contradiction by finding the optimal balance point.
Solution Approach 2:
The system extends the beneficial cooling effect from the pre-cooling period through the demand limiting period by utilizing the building's thermal mass. The cooling action initiated during pre-cooling continues to provide thermal comfort during the peak period without requiring additional energy input, thereby reducing peak demand while keeping total energy consumption manageable through continuous utilization of the stored thermal energy.
Data Source
AI summary
Systems and methods for limiting power consumption by a heating, ventilation, and air conditioning (HVAC) subsystem of a building are shown and described. A mathematical linear operator is found that transforms the unused or deferred cooling power usage of the HVAC system based on pre-determined temperature settings to a target cooling power usage. The mathematical operator is applied to the temperature settings to create a temperature setpoint trajectory expected to provide the target cooling power usage.


