Utility portals for managing demand-response events
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Solution Overview
Problem
Utility companies face challenges in managing peak electricity demand due to limited tools for intuitive and flexible management of demand response events, leading to consumer discomfort and potential undermining of demand response programs.
Innovation Solution
The development of utility portals that enable utility companies to communicate with energy management systems to implement demand response events through network-connected thermostats, allowing for parameter assignment, scheduling, and energy reduction management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If utility companies build additional power plants to satisfy peak demand, then the ability to meet peak demand is improved, but the cost and efficiency worsen due to prohibitive construction costs and underutilization of capacity
Solution Approach 1:
The system performs pre-cooling of residences 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 thermal mass of the building stores cooling energy, allowing the cooling system to be reduced or shut off during peak demand without compromising comfort. This preliminary action shifts energy consumption away from peak periods, eliminating the need for additional power plant capacity.
2Productivity
If utility companies implement traditional load shedding by directly controlling cooling systems, then peak demand is reduced, but consumer comfort and program acceptance worsen due to inadequate cooling during hot periods
Solution Approach 1:
The system pre-cools residences before the load shedding interval by lowering the temperature setpoint during off-peak hours. This creates a thermal buffer that maintains comfortable temperatures during the peak demand period when cooling is reduced or stopped, thereby preserving consumer comfort while achieving peak demand reduction.
Solution Approach 2:
The system dynamically changes the temperature setpoint parameter of the cooling system based on the timing relative to peak demand events. During pre-cooling, the setpoint is lowered below the normal comfort level; during the load shedding interval, the setpoint is raised or cooling is curtailed; after the event, the setpoint returns to normal. These parameter changes are optimized based on individual residence characteristics such as thermal mass, insulation, and occupancy patterns.
3Productivity
If utility companies use direct load control with periodic on-and-off cycling of cooling systems, then peak demand is reduced, but consumer comfort and program reliability worsen due to loss of control and communication failures
Solution Approach 1:
The system continuously monitors residence temperature, cooling system status, and outdoor conditions, using this feedback to adjust control strategies in real-time. If the residence temperature approaches the upper comfort threshold during a load shedding event, the system can modify the pre-cooling duration or intensity, or extend pre-cooling into the event period, ensuring comfort is maintained while achieving demand reduction goals.
Solution Approach 2:
The control strategy transitions from static, fixed-duration load shedding to dynamic, adaptive control that responds to real-time conditions. The system adjusts pre-cooling duration, intensity, and timing based on predicted peak demand events, residence thermal characteristics, outdoor temperature forecasts, and actual temperature measurements, optimizing both comfort and energy reduction outcomes.
4Measurement precision
If utility companies provide detailed group information and availability status in the portal, then the precision of demand response event scheduling is improved, but the complexity of the portal interface worsens
Solution Approach 1:
The portal interface is segmented into distinct functional modules: a scheduling module for defining event parameters, a participant management module for assigning residences to groups, and a status display module for showing group availability. Each module presents only the relevant information and controls for its specific function, allowing detailed scheduling precision while maintaining interface simplicity through organized separation of concerns.
Data Source
AI summary
A method includes generating a utility portal interface in response to a request from a utility computer system that receives parameters that specify a demand response event; providing a display of groups of energy-consuming locations that are available to be selected to participate in the demand response event; providing a display of an energy demand profile for the utility during the demand response event; receiving a selection of a subset of the groups of energy-consuming locations to participate in the demand response event; causing the display of the energy demand profile for the utility during the demand response event to be dynamically updated as the subset of the groups of energy-consuming locations are selected or deselected by the utility computer system to participate; and sending transmissions to thermostats associated with the subset of the groups of energy-consuming locations to execute the demand response event.