Prosumer Energy System Model for Technology Selection
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Solution Overview
Problem
Existing models fail to adequately characterize and evaluate energy technology options in prosumer energy systems by not combining multiple interacting technologies and behavioral responses, making it difficult for prosumers to select optimal technologies and for policymakers and technology providers to demonstrate their benefits effectively.
Innovation Solution
A computer-implemented method that collects energy data from smart grids, selects microgrid technologies, and performs real-time analytics to provide energy balance evaluations, incorporating factors like battery capacity, efficiency ratings, solar system costs, behavioral responses, and energy sales options, allowing for informed technology selection and system design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing models evaluate energy technologies in prosumer systems, then technology selection is simplified, but the models fail to adequately characterize multiple interacting technologies and behavioral responses
Solution Approach 1:
The patent combines multiple previously separate evaluation components into a unified prosumer energy system model that simultaneously evaluates solar panels, wind turbines, batteries, and behavioral responses. This integration allows the model to capture technology interactions and behavioral responses that were previously lost when evaluating technologies in isolation.
2Measurement precision
If the model incorporates multiple interacting technologies and behavioral responses, then evaluation accuracy improves, but model complexity increases
Solution Approach 1:
The patent creates a universal evaluation model that can assess multiple technology configurations and behavioral scenarios through a single integrated framework. The model handles solar panels, wind turbines, batteries, and various pricing structures using common evaluation principles, reducing the need for separate specialized models while maintaining high evaluation accuracy.
Solution Approach 2:
The model manages complexity by systematically varying key parameters such as energy storage capacity, solar panel size, wind turbine capacity, and behavioral response factors. By changing these parameters in controlled ways, the model can evaluate numerous scenarios without requiring a fundamentally more complex structure, allowing accurate assessment across different prosumer configurations.
3Measurement precision
If real-time analytics are performed with multiple technology permutations, then energy balance accuracy improves, but computational time increases
Solution Approach 1:
The patent performs preliminary calculations of energy production and consumption patterns before conducting the full energy balance analysis. By pre-computing baseline values for solar generation, wind generation, and load profiles, the model reduces the computational burden during the actual energy balance calculation, enabling accurate results across multiple technology permutations without excessive processing time.
Solution Approach 2:
The model implements a tiered analysis approach where it first performs partial energy balance calculations for key technology components, then progressively adds more detailed analyses only where needed. This allows the system to provide accurate energy balance information for critical decisions while avoiding unnecessary computational overhead in areas where approximate values suffice.
Data Source
AI summary
A model for balancing energy loads in a prosumer energy system, wherein the method combines multiple interacting technologies, behavioral responses and real-time energy interactions to offer a better evaluation of the prosumer energy system.