Automatic staging of multiple HVAC systems during a peak demand response
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Solution Overview
Problem
Existing HVAC systems struggle to maintain user comfort during peak demand response times while reducing power consumption, as they lack efficient methods to stage operations of multiple HVAC systems effectively.
Innovation Solution
A system comprising a multiple-system controller that communicatively couples with multiple HVAC systems, enabling intelligent staging of operations by determining a staging schedule based on anticipated power consumption and occupancy, to optimize comfort and energy savings during peak demand response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If HVAC systems operate at full capacity to maintain user comfort, then comfort level is improved, but power consumption increases during peak demand response times
Solution Approach 1:
The system segments the HVAC fleet into multiple controllable groups and implements staged shutdown sequences, where different HVAC units are turned off at different times rather than all at once, allowing continuous operation of sufficient capacity to maintain comfort while reducing total power consumption
Solution Approach 2:
The system dynamically adjusts HVAC operation schedules based on real-time conditions including outdoor temperature, occupancy patterns, and predicted peak demand timing, optimizing the balance between comfort maintenance and power reduction
2Use of energy by moving object
If multiple HVAC systems are staged during peak demand response, then power consumption is reduced, but system complexity increases
Solution Approach 1:
The system employs automated algorithms that independently determine optimal shutdown schedules based on input parameters, eliminating the need for complex manual coordination and reducing operational complexity while achieving power reduction goals
Solution Approach 2:
The system changes operational parameters such as setpoint temperatures and operational schedules of individual HVAC units during demand response events, allowing flexible power management without requiring physical system modifications
3Use of energy by moving object
If HVAC systems are turned off during peak demand response, then power consumption is reduced, but user comfort deteriorates
Solution Approach 1:
The system pre-cools or pre-heats spaces before anticipated peak demand periods when possible, and uses predictive algorithms to determine optimal shutdown timing that minimizes comfort impact, ensuring HVAC systems are restarted before comfort degradation becomes significant
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively maintains user comfort by intelligently distributing the operation of multiple HVAC systems, ensuring that energy-saving requirements are met during peak demand response times, thereby improving system performance and occupant comfort.
Implementation Method 1
Air is cooled via heat transfer with refrigerant flowing through the HVAC system and returned to the enclosed space as conditioned air
Data Source
AI summary
A system includes multiple HVAC systems. After receiving a demand request, a multiple-system controller a first anticipated power consumption associated with operating a first HVAC system at a first temperature setpoint during a future period of time of the demand response request and a second anticipated power consumption associated with operating a second HVAC system at a second temperature setpoint during the future period of time. Based at least in part on the first and the second anticipated power consumptions, a staging schedule is determined that indicates when to operate the first and second HVAC systems.