Wireless Home Energy Network for Automated Demand Response
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Solution Overview
Problem
Current energy management systems lack transparency and active participation in residential energy management, relying on consumers to manually curtail usage and lacking real-time data infrastructure for utility companies to analyze demand and schedule energy production effectively.
Innovation Solution
An energy management system that includes a database for storing site report data, a processor to access and analyze energy usage patterns, and a network of devices such as smart thermostats and appliances, enabling real-time energy monitoring and scheduling through a wireless home energy network, along with a mobile application for user interface and control.
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 active energy management and must manually curtail usage
Solution Approach 1:
The energy management system enables appliances and devices to automatically adjust their operation based on real-time energy pricing and user-defined preferences. The system self-manages energy consumption by scheduling tasks during optimal pricing periods without requiring manual user intervention, while still providing full visibility of energy usage and costs through the interface.
Solution Approach 2:
Users pre-configure their energy consumption preferences, constraints, and priorities in advance. The system then uses these pre-set parameters to automatically make scheduling decisions when energy price signals are received, performing the curtailment action before the user would need to manually intervene.
2Productivity
If demand response systems force curtailment on customers to react to load levels, then utility load management is improved, but end users experience inconvenience
Solution Approach 1:
The system dynamically adjusts energy consumption schedules based on real-time pricing signals and grid conditions while respecting user-defined constraints. Instead of forcing fixed curtailment, the system flexibly optimizes appliance operation times within user-specified windows, maintaining convenience while achieving load management goals.
Solution Approach 2:
The system continuously receives feedback from both the utility (energy pricing signals, load conditions) and the user (preferences, constraints, priority settings) to adjust scheduling decisions. This closed-loop feedback mechanism ensures that load management actions align with both utility needs and user convenience requirements.
3Measurement precision
If smart meters are deployed to measure and report consumption data, then real-time energy measurement capability is improved, but communication and analytical infrastructure remains lacking for effective demand analysis
Solution Approach 1:
The energy management system acts as an intermediary layer between smart meters and utility companies, performing local analysis of consumption patterns and pricing signals. This intermediary functionality distributes the analytical burden, reducing the need for complex centralized infrastructure while enabling effective demand response.
Solution Approach 2:
The system segments the energy management function into distributed components at consumer premises rather than requiring a monolithic centralized analytical infrastructure. Each local system independently processes its own consumption data and pricing signals, reducing overall system complexity and communication requirements.
4Loss of information
If monthly billing is used to inform consumers of energy consumption, then consumers receive consumption information, but energy awareness is insufficient and real-time management is lost
Solution Approach 1:
The system continuously monitors energy consumption, pricing signals, and appliance status in real-time rather than providing periodic monthly updates. This continuous information flow enables ongoing optimization of energy usage and immediate response to changing pricing conditions, eliminating the time loss associated with monthly billing cycles.
Data Source
AI summary
According to an aspect of the disclosure, an energy management system and method includes managing energy use of a site comprising the steps of: acquiring a network device data from a network device joined to a wireless energy network; translating the network data into device report data comprised of at least one Java based object; detecting an interval to generate a site report of the wireless energy network; translating the device report data into site report data comprised of XML formatted data; and generating the site report including the site report data at the interval. A wireless energy network communication device is configured to communicate with a wireless energy network and a processor is operably coupled to the wireless energy communication device and configured to perform the steps of managing energy use of the site.