Digital Twin Traffic Control for Peak Power Reduction in Buildings
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Solution Overview
Problem
Modern infrastructure faces challenges in anticipating and mitigating disruptions such as extreme weather events and human pathogens, leading to cascading failures in interconnected systems, resulting in significant economic, health, and environmental impacts, as seen during events like Winter Storm Uri.
Innovation Solution
A digital twin-based system and method are implemented to predict traffic flow information and redirect traffic, identifying impediments and displaying user-selectable alternatives to manage peak power and energy consumption, utilizing pre-trained conditions and real-time data to optimize traffic flow and vehicle departure schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If infrastructure systems operate at full capacity to meet service delivery requirements, then productivity and service delivery are improved, but peak power consumption and energy usage increase
Solution Approach 1:
The system dynamically adjusts infrastructure operation modes based on real-time conditions and predictions. The digital twin continuously monitors system state and enables flexible switching between different operational configurations to optimize the balance between service delivery and energy consumption, rather than operating at fixed full capacity
Solution Approach 2:
The system performs preliminary actions by predicting future traffic flow and system conditions using the digital twin model. This allows advance planning of energy consumption patterns and proactive adjustment of operational parameters before peak demand occurs, reducing the need for high peak power consumption
2Reliability
If infrastructure systems are designed with high capacity to prevent disruptions, then reliability is improved, but energy consumption and operational costs increase
Solution Approach 1:
The system changes operational parameters dynamically based on predicted conditions rather than maintaining fixed high-capacity configuration. The digital twin enables adjustment of traffic flow patterns, vehicle scheduling, and infrastructure utilization parameters to maintain reliability while optimizing energy consumption under varying conditions
3Productivity
If real-time monitoring and control systems are implemented to manage traffic flow, then productivity and service delivery are improved, but device complexity and implementation costs increase
Solution Approach 1:
The system uses a digital twin - a virtual copy of the physical infrastructure system - to perform monitoring, analysis, and prediction functions. This digital replica enables complex simulations and optimizations without requiring equivalent physical complexity, reducing implementation costs while maintaining high productivity benefits
Data Source
AI summary
A method includes identifying a route for passengers seeking to enter a building. The route includes at least one section of road for automobiles to access a building; or at least one access point inside the building for pedestrians to pass through. The method includes receiving traffic flow information corresponding to the route. The method includes determining whether the received traffic flow information corresponds to a condition that impedes the route, from among a set of pre-trained conditions. The method includes identifying and displaying a list of user-selectable state alternatives related to the condition that impedes the route, based on a determination that the received traffic flow information corresponds to the condition.