Energy management method
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Solution Overview
Problem
Current energy management systems lack active engagement with consumers, lack transparency in energy consumption causes, and lack infrastructure for real-time energy analysis and demand scheduling, leading to inefficient energy use and inconvenience in demand response programs.
Innovation Solution
An energy management system that includes a database to store site report data, a processor to analyze thermostat settings and HVAC systems, and modules for energy pricing, demand response, and scheduling to optimize energy use based on real-time data and user preferences.
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 their use
Solution Approach 1:
The energy management system enables devices to automatically adjust their operation based on energy pricing and user-defined preferences. The system self-manages energy consumption by scheduling HVAC systems, water heaters, and other appliances without requiring manual consumer intervention, thus providing both information awareness and automated management.
Solution Approach 2:
The system continuously monitors energy consumption, pricing signals, and device status, then provides real-time feedback to automatically adjust device operation. This closed-loop feedback mechanism allows the system to respond dynamically to changing energy prices and consumption patterns, optimizing energy use without manual input from consumers.
2Productivity
If demand response systems force curtailment on customers to react to load levels, then energy load management is achieved, but end users experience inconvenience
Solution Approach 1:
The system dynamically adjusts device operation schedules based on real-time energy pricing, user preferences, and comfort constraints. Rather than forcing fixed curtailment, the system flexibly schedules energy-consuming devices to operate during optimal pricing periods while maintaining user-defined comfort levels, thus achieving load management without inconvenience.
Solution Approach 2:
The system applies different control strategies to different devices and locations based on user-specific preferences and requirements. Each device can be individually configured with its own operational constraints and priorities, allowing customized energy management that respects local user needs while achieving overall load reduction.
3Measurement precision
If smart meters are deployed to measure and report consumption data, then real-time consumption measurement is enabled, but communication and analytical infrastructure is lacking for utility companies to analyze future demand
Solution Approach 1:
The energy management system acts as an intermediary between smart meters and utility companies, performing local analysis and scheduling of energy consumption. The system processes consumption data and pricing signals locally to generate optimized schedules, reducing the need for complex centralized analytical infrastructure while enabling sophisticated demand management.
Solution Approach 2:
The system divides the energy management function into distributed components at consumer premises rather than requiring centralized processing. Each local system independently analyzes its own consumption patterns and schedules devices, segmenting the analytical workload and reducing infrastructure complexity while maintaining precise real-time measurement capabilities.
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 and reports energy consumption 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 device, and make immediate adjustments to optimize energy management.
Data Source
AI summary
A method of managing energy use at a site includes opening a session with a first remote server and then communicating with the at least one remote server at a periodic interval. The method proceeds by determining whether energy management information is located at the at least one remote server and then receiving the energy management information at a controller located at the site. The method then includes processing the energy management information.