Energy Management Server for Predictive Utility Rate Selection
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Solution Overview
Problem
Consumers face challenges in managing and monitoring energy usage effectively in deregulated, partially deregulated, and regulated energy markets, lacking unbiased information and efficient tools for selecting, managing, and consuming energy from electric utility service providers.
Innovation Solution
A system comprising smart appliances and a resource management server that provides real-time, near real-time power monitoring and control, offering consumers with smart load-based consumption information, trend analysis, and self-performed energy audits, while facilitating energy savings and education, and enabling aggregation across communities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If consumers manually manage energy usage without automated systems, then device complexity is reduced, but energy management efficiency and monitoring capability deteriorate
Solution Approach 1:
The system enables automated energy management where the energy management server independently performs monitoring, analysis, and optimization of energy consumption patterns without requiring direct user intervention. The server automatically processes energy data from multiple providers, generates reports, and provides recommendations, allowing the system to serve itself in managing energy usage while improving efficiency.
Solution Approach 2:
An energy management server acts as an intermediary between consumers and multiple energy service providers. This intermediary consolidates complex information from various providers into unified, easy-to-understand reports and interfaces, shielding consumers from the complexity of multiple providers while improving energy management efficiency through centralized control and analysis.
2Loss of information
If consumers access multiple energy service providers directly, then information completeness improves, but ease of operation deteriorates due to managing multiple accounts and interfaces
Solution Approach 1:
The system merges multiple energy service provider interfaces and accounts into a single unified energy management interface. Consumers can access and compare energy usage data, pricing, and plans from multiple providers through one consolidated dashboard, maintaining complete information while dramatically improving ease of operation by eliminating the need to manage separate accounts and interfaces for each provider.
Solution Approach 2:
The energy management server provides universal access to multiple energy service providers through a single platform that performs multiple functions: monitoring energy consumption, comparing pricing from different providers, generating consolidated reports, and providing optimization recommendations. This multi-functional approach ensures complete information access while simplifying user interaction to a single easy-to-use interface.
3Loss of energy
If real-time monitoring and control systems are implemented, then energy efficiency improves, but device complexity and initial costs increase
Solution Approach 1:
The system implements continuous feedback loops where the energy management server constantly monitors energy consumption data from smart meters and appliances, analyzes patterns in real-time, and provides immediate feedback to consumers through reports and notifications. This feedback mechanism enables dynamic energy optimization by allowing consumers to adjust behavior based on real-time information, improving energy efficiency while using software-based solutions that minimize additional hardware complexity.
Data Source
AI summary
The disclosure includes methods, systems and apparatus for predictive management of efficient selecting and receiving of retail electric utility service to a facility for a period, by automated selecting of a retail utility service provider corresponding to a selected least cost path of predicted rate plan choices across the period, wherein costs of all possible, viable time-bounded predicted rate plan choices are determined for predicted consumer usage where a predicted market of retail rate formulas for the period are predicted in relation to at least one variable, such as weather.