Home Energy Management via Thermostat Scheduling and Demand Response
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Solution Overview
Problem
Current energy management systems are passive and lack transparency, failing to provide consumers with real-time energy consumption data and analytical infrastructure for utility companies to manage demand and energy production effectively, leading to inefficient energy use and inconvenience to end-users.
Innovation Solution
An energy management system that includes a database for storing site report data, a processor for analyzing energy usage, and a network of devices such as smart thermostats and appliances, which can detect temperature set-points, operating modes, and schedules to optimize energy consumption based on real-time pricing and user proximity, using wireless communication protocols like Zigbee and Wi-Fi.
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 automated energy management and must manually curtail usage
Solution Approach 1:
The energy management system enables appliances and devices to automatically manage their own energy consumption based on real-time pricing signals and user-defined preferences. The system self-adjusts operation schedules without requiring manual user intervention, while still achieving energy conservation goals. This resolves the contradiction by making the system serve itself rather than requiring continuous manual operation from users.
Solution Approach 2:
Users pre-configure their energy management preferences, constraints, and priorities before energy consumption events occur. The system then automatically executes energy management decisions based on these pre-set parameters when real-time pricing signals are received. This preliminary configuration eliminates the need for manual curtailment decisions during energy consumption events while maintaining user control over energy management behavior.
2Productivity
If demand response systems force curtailment on customers to react to load levels, then utility load management is improved, but end-user convenience is significantly reduced
Solution Approach 1:
The energy management system dynamically adjusts appliance operation schedules and energy consumption patterns in real-time based on changing energy prices, grid conditions, and user preferences. Rather than forcing fixed curtailment schedules, the system flexibly optimizes energy usage to balance utility load management needs with user convenience requirements. This dynamic adaptation resolves the contradiction by making curtailment flexible rather than mandatory.
Solution Approach 2:
The system continuously receives feedback from multiple sources including real-time energy pricing signals, grid load conditions, and user preference updates. This feedback loop enables the system to automatically adjust energy management strategies to achieve utility load management goals while respecting user convenience constraints. The feedback mechanism ensures that curtailment actions are taken only when necessary and acceptable to users, resolving the contradiction between utility efficiency and user convenience.
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 for effective demand analysis
Solution Approach 1:
The energy management system is segmented into distributed components at user premises and centralized components at utility facilities. Each segment performs specific analytical functions locally or remotely, eliminating the need for a single complex centralized infrastructure. The segmentation allows smart meters to provide precise measurement while analytical capabilities are distributed across multiple simpler components, resolving the contradiction between measurement precision and infrastructure complexity.
Solution Approach 2:
An energy management server acts as an intermediary between smart meters and utility company systems, performing data aggregation, analysis, and translation functions. This intermediary layer simplifies the communication infrastructure by handling complex analytical tasks centrally while allowing smart meters to focus on precise measurement. The intermediary resolves the contradiction by absorbing the analytical complexity away from the measurement devices and utility systems.
Data Source
AI summary
A system and method migrating virtualized environments is disclosed. According to an aspect of the disclosure, a home energy management system and method includes a database configured to store site report data received from a plurality of residential sites using a wireless home energy network at each site. Each residential site includes a thermostat accessible to the wireless home energy network. A processor is operably coupled to the database and configured to access the site report data and detect a current temperature set-point of the thermostat at a first residential site; detect a first seasonal profile of the thermostat; detect a current operating mode of a HVAC system operably coupled to the thermostat; and determine a thermostat schedule of the thermostat using the first seasonal profile and the current operating mode of the HVAC system.