Networked Thermostat Verification for Peak HVAC Demand Reduction
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Solution Overview
Problem
Current residential peak demand reduction systems face challenges such as hardware and communication complexities, potential damage to air conditioning systems from hard cycling, and lack of verification for utility compliance, making them costly and inefficient.
Innovation Solution
A system comprising a thermostat connected to a local network and a server that predicts temperature changes based on outside conditions, allowing bi-directional communication to verify if the HVAC system is turned off by comparing predicted and actual temperature changes, thereby confirming demand reduction without additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional peak demand reduction systems are implemented, then demand reduction can be achieved, but hardware and communication complexities increase
Solution Approach 1:
The system uses the thermostat itself to verify demand reduction by monitoring temperature changes and comparing them against predicted values. The thermostat leverages its own sensing capabilities and the existing HVAC system to generate verification data, eliminating the need for separate verification hardware or complex communication protocols.
Solution Approach 2:
The system introduces a server as an intermediary that receives temperature data from thermostats, predicts expected temperature changes based on outdoor conditions, and compares predicted versus actual temperatures to verify demand reduction. This centralizes verification logic and simplifies individual thermostat functionality.
2Reliability
If hard cycling of air conditioning systems is used for demand reduction, then peak demand can be reduced, but damage to air conditioning systems occurs
Solution Approach 1:
The system predicts the temperature trajectory before demand reduction events and pre-cools spaces to higher temperatures within comfort ranges, or pre-heats in winter, to create a buffer that allows demand reduction without immediate cycling. This preliminary action prevents the thermal shock that causes hard cycling damage.
Solution Approach 2:
The system uses thermal mass and predicted temperature models to cushion against rapid temperature changes during demand reduction events. By understanding the thermal characteristics of buildings and equipment, the system can allow temperature drift within safe margins that prevent equipment damage while still achieving demand reduction goals.
3Measurement precision
If verification systems are implemented to ensure utility compliance, then accurate verification is achieved, but system complexity and cost increase
Solution Approach 1:
The system implements feedback by continuously monitoring indoor temperature, comparing it against predicted temperature trajectories based on outdoor conditions and building characteristics, and using this comparison to verify whether demand reduction actually occurred. This feedback loop provides accurate verification without complex hardware by leveraging existing thermostat sensors and computational modeling.
Data Source
AI summary
The invention comprises systems and methods for estimating the rate of change in temperature inside a structure. At least one thermostat located is inside the structure and is used to control an climate control system in the structure. At least one remote processor is in communication with said thermostat and at least one database stores data reported by the thermostat. At least one processor compares the outside temperature at least one location and at least one point in time to information reported to the remote processor from the thermostat. The processor uses the relationship between the inside temperature and the outside temperature to determine whether the climate control system is “on” or “off”.