Utility Asset Management System for Weather Risk Prediction
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Solution Overview
Problem
Utilities face challenges in effectively managing resources and making decisions during severe weather events due to the lack of integrated systems that can predict and visualize the impact of weather on their assets, leading to inefficiencies in crew deployment and restoration efforts.
Innovation Solution
The Utility Resource Asset Management System (URAMS) integrates real-time and historical weather data with utility asset data to provide dynamic response plans and optimized resource allocation, using advanced analytics and predictive models to assess threats and support decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If utilities use traditional separate weather monitoring and asset management systems, then system simplicity is maintained, but decision-making effectiveness and resource optimization deteriorate
Solution Approach 1:
The patent merges weather monitoring systems with utility asset management systems into a unified integrated platform. This integration combines weather data collection, asset inventory, risk assessment, and resource allocation capabilities into a single cohesive system, enabling utilities to make informed decisions about crew deployment and restoration efforts during severe weather events.
Solution Approach 2:
The integrated system performs multiple functions including real-time weather monitoring, historical weather data analysis, asset risk assessment, resource allocation optimization, and decision support. This multi-functional approach allows a single system to address various utility needs during weather events without requiring separate specialized systems.
2Productivity
If utilities lack integrated weather and asset data, then system complexity is minimized, but resource allocation efficiency and restoration speed deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing historical weather data and utility asset information in an integrated database before severe weather events occur. This pre-prepared data enables rapid risk assessment and resource allocation decisions when weather events actually impact the utility network.
Solution Approach 2:
The integrated system continuously feedbacks weather data with asset information to update risk assessments and optimize resource allocation in real-time. This feedback loop allows the system to adapt to changing weather conditions and utility needs, improving restoration speed through dynamic decision-making.
3Reliability
If utilities do not have predictive weather impact models, then system simplicity is maintained, but crew deployment optimization and loss reduction deteriorate
Solution Approach 1:
The system develops and maintains predictive models that forecast weather impact on utility assets before severe weather events occur. These models use historical weather data, asset characteristics, and weather patterns to predict potential damage, enabling utilities to pre-position resources and deploy crews to high-risk areas in advance.
Solution Approach 2:
The predictive modeling component operates autonomously to process weather data, analyze asset vulnerabilities, and generate threat predictions without requiring manual intervention. This self-service capability allows the system to continuously improve its predictions by learning from historical weather events and utility responses.
Data Source
AI summary
The UTILITY RESOURCE ASSET MANAGEMENT SYSTEM APPARATUSES, METHODS AND SYSTEMS (“URAMS”) transform weather, terrain, and utility asset parameter data via URAMS components into damage predictions with confidence metrics, alerts, and asset allocation and response plans.