AI Utility Matching System for Energy Optimization
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Solution Overview
Problem
Conventional utilities face challenges in optimizing energy consumption and deepening relationships with consumers, integrating distributed resources, and adapting to business model transformations due to the underutilization of AI systems and the complexity of energy choices available to consumers.
Innovation Solution
A system and method for matching utility consumers with providers using a communication device, processing device, and storage device that analyze utility consumption, environmental, and premises information to generate recommendations for energy optimization and supplier selection, integrating AI and behavioral science to create personalized energy profiles and optimize energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional utilities use traditional methods for managing energy consumption, then operational simplicity is maintained, but energy optimization and consumer relationship depth are insufficient
Solution Approach 1:
The patent introduces an AI-based intermediary system that acts as a mediator between utility consumers and energy sources. This system processes consumption data, environmental information, and premises data to generate optimized energy recommendations, thereby achieving energy optimization without requiring direct complex interactions between consumers and multiple energy providers.
Solution Approach 2:
The system enables consumers to automatically receive personalized energy recommendations based on their own consumption patterns and preferences. The AI system self-adjusts and learns from consumer behavior data to provide optimized energy management without requiring manual intervention or complex consumer actions.
2Loss of information
If utilities integrate AI systems for data analysis, then consumer insights and energy optimization improve, but implementation complexity and resource requirements increase
Solution Approach 1:
The patent segments the complex AI system into distinct functional modules: data collection from multiple sources, consumer behavior analysis, recommendation generation, and delivery through communication devices. This segmentation allows utilities to implement AI capabilities incrementally and manage complexity through modular architecture.
Solution Approach 2:
The AI system is designed to perform multiple functions: analyzing consumption data, processing environmental information, evaluating premises data, generating recommendations, and communicating with consumers. This multi-functionality consolidates what would otherwise require multiple separate systems into a single unified platform.
3Adaptability or versatility
If consumers are provided with multiple energy choices, then energy independence and sustainability improve, but decision complexity and consumer confusion increase
Solution Approach 1:
The system provides consumers with feedback in the form of personalized recommendations that synthesize multiple energy options based on their specific consumption patterns and preferences. This feedback mechanism translates complex energy choice data into actionable, easy-to-understand recommendations, maintaining energy independence while simplifying consumer decision-making.
Solution Approach 2:
The AI system dynamically adjusts recommendation parameters based on changing consumer behavior, environmental conditions, and energy availability. This allows the system to present the most relevant energy choices at any given time, reducing decision complexity while maintaining adaptability to various consumer needs and preferences.
Data Source
AI summary
A system for matching at least one utility consumer to at least one utility provider is provided. The system may include a communication device, a processing device and a storage device. The communication device may be configured for receiving utility consumption information from a utility consumption information source, receiving environmental information from an environmental information source, receiving premises information from a premises information source, receiving utility provider information from utility provider information source and transmitting a utility recommendation to an electronic device. Further, the processing device may be configured for analyzing each of the utility consumption information, the environmental information and the premises information and the utility provider information, and generating the utility recommendation based on the analyzing. Further, the storage device may be configured for storing each of the utility consumption information, the environmental information, the premises information, the utility provider information and the utility recommendation.