Appliance Controller Load Shedding Without Smart Meters
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Solution Overview
Problem
Existing demand response systems require significant investments in advanced metering infrastructure and smart meters to manage peak load shedding and payback spikes, which can be costly and complex, and may not effectively distribute load reduction across a population to prevent power outages.
Innovation Solution
A method and system that uses a controller with a memory to generate a unique serial number for appliances, allowing for communication with utilities to alter operating parameters such as runtime and temperature setpoints, and randomize distribution among subsets of homes to independently manage energy usage during peak and off-peak periods, enabling load shedding and payback spike reduction without the need for smart meters or advanced infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advanced metering infrastructure and smart meters are installed to manage demand response, then load shedding and payback spike control can be achieved, but system cost and complexity increase significantly
Solution Approach 1:
The patent extracts the demand response control functionality from the complex smart meter infrastructure and relocates it to the appliance-level controller. The utility company's demand response signals are received and processed by existing appliance controllers, eliminating the need for advanced metering infrastructure while maintaining load shedding control capability.
Solution Approach 2:
The appliance controller autonomously manages its own operation during demand response events by interpreting utility signals and automatically adjusting runtime and temperature setpoints. The system self-regulates without requiring external smart meter intervention, with the controller making independent decisions about when to shed load based on received signals.
2Power
If load shedding is implemented during peak periods, then peak demand is reduced, but payback spikes occur when appliances return to normal operation
Solution Approach 1:
The patent implements periodic demand response events where appliances cyclically switch between normal operation and energy-saving modes. The controller receives periodic signals from the utility company and adjusts operation accordingly, creating a rhythm of load shedding that prevents continuous peak demand while managing the cumulative effect of payback periods.
Solution Approach 2:
The system performs preliminary load shedding during off-peak periods by pre-cooling or pre-heating spaces before peak demand occurs. The controller anticipates upcoming peak periods and adjusts temperature setpoints in advance, reducing the need for intensive cooling/heating during peak times and thereby minimizing payback spikes when normal operation resumes.
3Use of energy by moving object
If appliances operate at reduced runtime during demand response, then energy consumption decreases, but appliance performance and comfort may be compromised
Solution Approach 1:
The patent changes operational parameters such as temperature setpoints and runtime duration during demand response events. The controller adjusts these parameters dynamically based on the severity and duration of peak demand periods, finding optimal balances between energy reduction and maintaining acceptable appliance performance and user comfort.
Solution Approach 2:
The system dynamically adjusts appliance operation rather than applying fixed reduction rules. The controller continuously monitors utility signals, outdoor temperature, and appliance state to make real-time decisions about runtime and temperature adjustments, adapting to changing conditions to maintain performance while reducing energy consumption.
Data Source
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AI summary
An apparatus and methods are disclosed for controlling load shedding and payback spikes of a population by segregating the population (904) into subsets based on predicted energy consumption usage and peak load profiles (902). Subset populations (230, 232, 234) respond independently from another based on a communication message (200) sent to the population. Each subset population (230, 232, 234) of homes with one or more energy consuming devices responds based on a generated value generated from a randomizing distribution routine.