Utility Marketplace Platform for Real-Time Demand Response
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Solution Overview
Problem
Consumers lack visibility and control over their energy consumption, and transmission distribution service providers face challenges in managing peak demand due to slow consumer reactions to price changes, leading to unnecessary infrastructure investments.
Innovation Solution
An automated marketplace platform that provides consumers with real-time visibility into energy prices and sources, allowing them to manage demand and make informed choices, while incorporating machine learning and gamification to shape consumer behavior and reduce peak demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time pricing information and energy source visibility are provided to consumers, then consumer awareness and control over energy consumption improve, but system complexity increases
Solution Approach 1:
The patent introduces an automated marketplace platform as an intermediary between consumers, utility providers, and energy sources. This platform consolidates complex data from multiple sources (pricing, consumption, renewable energy credits, weather conditions) and presents simplified real-time information to consumers through user interfaces, thereby providing comprehensive visibility without exposing consumers to the underlying system complexity.
Solution Approach 2:
The patent replaces traditional manual energy trading and information dissemination mechanisms with automated electronic systems. Machine learning algorithms, real-time data processing, and automated matchmaking between consumers and energy providers substitute for complex human-mediated negotiations and information gathering, reducing the perceived complexity for end users while maintaining comprehensive information flow.
2Ease of operation
If consumers are given control over energy purchasing decisions, then consumer autonomy and satisfaction improve, but response time to price changes may be insufficient
Solution Approach 1:
The patent implements preliminary action by enabling consumers to set their energy preferences, constraints, and automatic bidding parameters in advance. The system pre-calculates optimal energy purchasing strategies based on forecasted pricing and consumer profiles. When price changes occur, the system automatically executes decisions based on pre-established rules, eliminating deliberation time while maintaining consumer autonomy through the initial configuration phase.
Solution Approach 2:
The patent enables self-service through automated decision-making systems that allow consumers to program their own energy purchasing preferences. The system automatically monitors pricing, evaluates options, and executes purchases without requiring real-time consumer intervention. Consumers retain control by configuring their preferences upfront, while the system handles time-sensitive decisions autonomously.
3Reliability
If infrastructure is expanded to meet peak demand, then reliability during high demand periods improves, but capital investment costs increase significantly
Solution Approach 1:
The patent applies dynamics by enabling flexible, real-time adjustment of energy supply and demand matching. Instead of static infrastructure expansion, the system dynamically optimizes energy allocation based on current pricing, consumption patterns, and available resources. This allows the grid to adapt to peak demand through intelligent routing and temporary sourcing adjustments rather than permanent infrastructure additions.
Solution Approach 2:
The patent utilizes parameter changes by allowing consumers to adjust their energy consumption parameters (timing, amount, source preferences) in response to varying prices and conditions. The system changes operational parameters such as pricing signals, availability indicators, and matching algorithms to optimize energy distribution during peak periods, achieving reliability improvements through software-based adjustments rather than physical infrastructure expansion.
Data Source
AI summary
A platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.