Sensor-Driven Feedback Loops for Dynamic Energy Management
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Solution Overview
Problem
Current systems lack an effective method to dynamically manage energy usage and equipment operation based on asset-specific energy consumption data, leading to inefficiencies and potential equipment breakdowns, which are not adequately addressed by existing technologies.
Innovation Solution
A computer-implemented method and system that processes historical and current energy consumption data, breakdown frequency, and environmental characteristics to determine usage-based insurance premiums and generate alerts to adjust energy usage levels, operational characteristics, and sensor parameters, thereby optimizing energy management and reducing breakdown risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If energy consumption data is collected and processed for each physical asset, then energy management efficiency is improved, but system complexity increases
Solution Approach 1:
The system segments energy management by creating separate feedback loops for each physical asset or location. Each loop processes energy consumption data independently, allowing granular control and optimization at the asset level while maintaining overall system coordination through the insurance premium mechanism.
Solution Approach 2:
The system introduces an intermediary insurance premium mechanism that translates energy consumption data into financial incentives. This intermediary layer simplifies the control architecture by using economic signals rather than direct technical control, reducing system complexity while maintaining management efficiency.
2Reliability
If real-time energy consumption monitoring is implemented, then equipment breakdown risk is reduced, but energy costs increase
Solution Approach 1:
The system implements feedback loops that continuously monitor energy consumption data and provide real-time information about equipment status. This feedback enables early detection of abnormal patterns that may indicate impending breakdowns, allowing preventive actions that reduce equipment failure risk while optimizing energy usage timing.
Solution Approach 2:
The system dynamically adjusts insurance premiums based on real-time energy consumption patterns and equipment risk levels. This dynamic pricing mechanism aligns energy costs with actual equipment risk, incentivizing energy-efficient operations that also reduce breakdown risk, thereby balancing monitoring costs with reliability benefits.
Data Source
AI summary
In some embodiments, the present invention provides for an exemplary inventive system that may include executable program code and a computer processor which, when executing the particular program code, is configured to perform operations of: receiving, for a population of energy consuming physical assets, asset-specific historical data and asset-specific current energy consumption data from utility meter(s), sensor(s), or both; determining, for each respective physical asset category, each respective frequency of breakdowns and each respective average severity of each breakdown; determining, an adjusted breakdown loss value per each physical asset for each respective physical asset category; determining a respective average current energy consumption value per each physical asset for each respective physical asset category; associating each respective energy consuming location to a particular physical asset category; generating, based on usage-based breakdown insurance premium value of the respective energy consuming location, an electronic alert configured to affect the location-specific level of energy usage of the at least one energy consuming physical asset.