Wireless Energy Network Interface for XML-Based 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 effective tools for energy conservation, leading to inefficient energy use and inconvenience in demand response programs.
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, seasonal profiles, and HVAC operating modes to schedule energy use and adjust consumption based on real-time pricing and user proximity.
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 conservation 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 low-cost periods without requiring manual user intervention, thus resolving the contradiction between providing energy information and requiring manual curtailment.
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. Unlike forced curtailment, the system adapts flexibly to both utility needs and user preferences, maintaining convenience while achieving load management goals through automated scheduling of appliances and devices.
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 automatically adjust energy consumption patterns. This closed-loop feedback mechanism ensures load management effectiveness while maintaining user convenience through automated, preference-based scheduling.
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 utility companies to analyze future demand
Solution Approach 1:
The energy management system performs analytical functions locally at the consumer premises, processing real-time pricing signals and scheduling decisions without requiring complex centralized analytical infrastructure. The system self-determines optimal scheduling based on received data, reducing the burden on utility company infrastructure while fully utilizing smart meter measurement capabilities.
Solution Approach 2:
The energy management system acts as an intermediary between smart meters and utility companies, performing local analysis and scheduling while communicating only essential scheduling decisions and consumption data to the utility. This intermediary function reduces the complexity requirements for utility analytical infrastructure while maintaining real-time measurement effectiveness.
4Quantity of substance
If consumers evaluate monthly bills to determine energy consumption, then billing information is provided, but consumers lack real-time energy awareness and transparency into leading causes of consumption
Solution Approach 1:
The system continuously monitors, measures, and reports energy consumption data in real-time rather than providing periodic monthly summaries. This continuous feedback enables consumers to understand their consumption patterns as they occur, identify leading causes of energy use by appliance or device, and make immediate adjustments to optimize energy management.
Data Source
AI summary
According to an aspect of the disclosure, an energy management apparatus for a home energy management system and method includes a processor operable to manage energy use at a site. The processor is configured to convert an incoming message received from a wireless energy network into XML enabled output data and format an outgoing message to be output to the wireless energy network using XML enabled input data. A communication interface is configured to enable access to a communication device having access to the wireless energy network, wherein the communication interface is further configured to detect the outgoing message formatted by the processor to be output using the wireless energy network; configure the outgoing message to a message bus format, detect the incoming message received from the wireless energy network, and convert the incoming message from the message bus format to access the incoming network device data.