Multiple HVAC System Staging for Peak Demand Response Energy Control
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Solution Overview
Problem
HVAC systems face challenges in maintaining user comfort during peak demand response times while reducing energy consumption, as existing technologies lack efficient tools to effectively stage multiple HVAC systems for optimal energy-saving and comfort outcomes.
Innovation Solution
A multiple-system controller is used to determine a staging schedule for multiple HVAC systems based on anticipated power consumption and occupancy, turning off one system while turning on another to maintain comfort and satisfy energy-saving requirements during peak demand response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If HVAC systems operate at full capacity during peak demand response times, then user comfort is maintained, but energy consumption exceeds the upper limit specified by demand response requests
Solution Approach 1:
The system segments the HVAC infrastructure into multiple independent HVAC systems that can be individually controlled. Instead of operating a single HVAC system at full capacity, the controller divides the cooling/heating load across multiple systems, enabling selective staging where some systems operate at reduced capacity or are cycled off during peak demand response times, thereby reducing overall energy consumption while maintaining comfort through coordinated operation of remaining systems
Solution Approach 2:
The system dynamically adjusts the operation of multiple HVAC systems based on real-time conditions including outdoor temperature, humidity, occupancy, and forecasted weather. The controller continuously optimizes the staging schedule, adjusting which systems are on/off and their setpoints, to maintain comfort while minimizing energy consumption during demand response events. This dynamic adaptation allows the system to respond flexibly to changing conditions rather than using fixed operational patterns
2Use of energy by moving object
If multiple HVAC systems are staged to reduce energy consumption during demand response, then energy-saving requirements are satisfied, but system complexity increases
Solution Approach 1:
The demand response controller is designed as a universal platform that can manage any number of HVAC systems with varying capacities and characteristics. The system uses standardized data structures and control algorithms that adapt to different system configurations, eliminating the need for custom control logic for each specific setup. This multi-functional approach allows the same controller architecture to handle diverse HVAC system combinations, reducing overall system complexity despite managing multiple units
Solution Approach 2:
The system automatically determines optimal staging schedules without requiring manual intervention or complex user configuration. The controller self-adjusts based on enrollment data indicating which HVAC systems are participating in automatic demand response operation, and autonomously optimizes their operation. This self-service capability eliminates the need for complex user interfaces or manual programming, reducing operational complexity while achieving energy-saving goals
3Use of energy by moving object
If HVAC systems are turned off or reduced during peak demand response, then energy consumption is reduced, but temperature regulation and user comfort deteriorate
Solution Approach 1:
The system pre-cools or pre-heats spaces before peak demand response events using forecasted weather data and occupancy information. By lowering setpoints or increasing capacity in advance when electricity demand is lower, the system stores thermal energy in the building mass (walls, floors, furniture). During the peak demand response period, this stored thermal energy maintains comfortable temperatures even with reduced HVAC operation, allowing energy consumption to be reduced without sacrificing temperature regulation
Solution Approach 2:
The system continuously monitors indoor temperature, humidity, and occupancy conditions, using this feedback to dynamically adjust the operation of staged HVAC systems. When sensors detect that temperature is approaching comfort thresholds, the controller automatically increases capacity or activates additional systems. This closed-loop feedback ensures that energy reduction strategies do not compromise temperature regulation, as the system adapts in real-time to maintain comfort while minimizing energy use
Data Source
AI summary
A system includes multiple HVAC systems. After receiving a demand request, a multiple-system controller determines 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.