Location-Based Energy Management System for Automated Demand Response
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Solution Overview
Problem
Current energy management systems are passive and lack transparency, failing to effectively engage consumers in energy conservation and lacking infrastructure for real-time energy consumption data analysis, leading to inefficient energy use and inconvenient demand response programs.
Innovation Solution
An energy management system that includes a database for storing site report data, a processor to analyze energy usage, and a network of devices such as smart thermostats and appliances, enabling real-time energy monitoring and scheduling to optimize energy consumption based on user behavior and energy pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If passive energy display technologies are provided to show current energy prices, then consumers gain energy price awareness, but consumers still lack motivation to actively reduce energy consumption
Solution Approach 1:
The system enables energy-consuming devices to automatically adjust their operation based on energy pricing signals and user-defined preferences without requiring manual intervention. The energy management system autonomously schedules device operation during lower-cost periods, allowing the system to serve itself in optimizing energy consumption patterns.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring energy consumption data, comparing it against pricing information and user preferences, and automatically adjusting device schedules. This feedback mechanism transforms static price displays into dynamic control actions that actively reduce energy costs.
2Productivity
If utility companies implement demand response systems that force curtailment on customers, then energy load management is achieved, but user convenience is significantly reduced
Solution Approach 1:
The system dynamically adjusts energy consumption schedules based on real-time pricing signals and grid conditions while respecting user-defined flexibility parameters. Users can specify which devices are flexible and under what conditions, creating a dynamic balance between load management and user convenience rather than static forced curtailment.
Solution Approach 2:
The system changes operational parameters of energy-consuming devices (timing, duration, intensity) based on energy pricing and grid conditions. Instead of binary on/off curtailment, the system optimizes multiple parameters to achieve load management while maintaining user comfort and convenience within acceptable ranges.
3Measurement precision
If smart meters are deployed to measure and report consumption data, then real-time energy measurement capability is provided, but communication and analytical infrastructure remains lacking
Solution Approach 1:
The system segments the complex analytical infrastructure into distributed components at consumer premises and centralized components at utility facilities. Local energy management systems perform preliminary analysis and scheduling, while utility systems aggregate data for broader optimization, dividing the complex infrastructure into manageable functional segments.
Solution Approach 2:
The system introduces an energy management software layer that acts as an intermediary between smart meters and utility systems. This intermediary layer handles data aggregation, analysis, and translation, simplifying the communication infrastructure requirements by providing standardized interfaces and processing capabilities without requiring complex direct connections between all components.
4Loss of information
If consumers manually monitor and curtail energy use based on monthly bills, then some energy awareness is achieved, but real-time energy optimization is lost
Solution Approach 1:
The system performs preliminary scheduling of energy-consuming devices based on forecasted pricing and user preferences before peak pricing periods occur. By pre-scheduling operations during lower-cost periods, the system proactively optimizes energy costs rather than reacting to monthly bills after consumption has already occurred.
Solution Approach 2:
The system continuously monitors energy pricing signals, consumption patterns, and device status to maintain optimal scheduling decisions in real-time. This continuous operation replaces the discontinuous monthly billing cycle with ongoing optimization, ensuring energy efficiency is maintained at all times rather than being reviewed periodically.
Data Source
AI summary
A demand response system includes a mobile application of a mobile device that is configured to initiate altering an operating condition of a network device disposed at a site using location based services. A demand response application interface module is configured to enable access between a utility company and the network device to communicate energy management information therebetween. The network device is configured to be remotely altered by each of the demand response application interface module and the mobile application separately based on the location based services and the energy management information. A method of managing a demand response system includes detecting a user being disposed away from a site, detecting energy management information from a utility company associated with the site, and initiating a reduction in energy use at the site in response to the relative location of the user and the energy management information.