Smart Grid Routing Optimization via Battery and Noise Metrics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current smart-grid communication systems face challenges in efficiently monitoring and controlling utility grid components due to limitations in routing optimization, battery-powered node management, and ambient noise impact on network efficiency, leading to suboptimal data transmission and reliability.
Innovation Solution
An integrated network platform with wireless networks and gateways that utilize optimized routing information, battery-aware route selection, and ambient noise consideration to enhance data transmission efficiency and reliability, allowing for multi-egress/multi-ingress configurations and intelligent packet routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional routing protocols are used in smart-grid wireless networks, then network coverage and connectivity are maintained, but network efficiency and reliability deteriorate due to lack of optimization for battery-powered nodes and ambient noise conditions
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting routing decisions based on multiple variables including battery charge levels of intermediate nodes, ambient noise conditions, and link quality metrics. The routing protocol changes parameters such as path selection, hop count preferences, and transmit power levels to optimize both reliability and efficiency simultaneously
Solution Approach 2:
The routing system implements dynamics by continuously adapting route selections based on real-time network conditions. Battery-powered nodes dynamically adjust their participation in routing paths based on charge levels, and the system dynamically reroutes traffic around nodes with low battery or poor link conditions, ensuring both reliability and efficiency
2Adaptability or versatility
If battery-powered intermediate nodes are used to extend network coverage, then network reachability is improved, but network efficiency deteriorates due to battery charge depletion and unreliable transmission
Solution Approach 1:
The system changes the parameter of node selection by incorporating battery charge level as a critical routing criterion. Routing decisions dynamically adjust based on real-time battery status, excluding nodes below threshold charge levels from being selected as intermediate hops, thereby maintaining coverage while ensuring transmission reliability
Solution Approach 2:
Battery-powered nodes provide feedback about their charge status to the routing system. This feedback mechanism enables the network to continuously monitor and adjust routing paths, preventing selection of nodes with insufficient battery charge and maintaining reliable transmission while preserving network coverage
3Reliability
If higher transmit power levels are used to overcome ambient noise, then link quality is improved, but network efficiency deteriorates due to increased energy consumption and ambient noise generation
Solution Approach 1:
The system changes the parameter of transmit power by dynamically adjusting power levels based on ambient noise conditions and link quality requirements. Instead of using fixed high power, the system optimizes power consumption by transmitting at the minimum necessary power level to maintain reliable links, thereby improving energy efficiency while preserving link quality
Solution Approach 2:
Transmit power levels are dynamically adjusted based on real-time ambient noise measurements and link conditions. The system transitions from static high-power transmission to adaptive power control, reducing energy consumption when conditions permit and increasing power only when necessary to maintain link quality
4Productivity
If centralized routing control is implemented at the gateway, then routing optimization is improved, but network complexity increases due to information collection and propagation overhead
Solution Approach 1:
The gateway implements multi-functionality by combining routing optimization, information collection, analysis, and propagation capabilities in a single centralized entity. This universal approach simplifies the overall network architecture while maintaining routing optimization benefits, as the gateway handles multiple functions that would otherwise require separate distributed intelligence
Data Source
AI summary
A wireless utility network contains a plurality of utility nodes that communicate within a wireless utility network. A gateway to the wireless utility network communicates with the utility nodes in the wireless utility network, and connects the wireless utility network to at least one other network. A packet is transmitted from one utility node to another utility node according to a route included in the transmitted packet. The route included in the transmitted packet is updated with received network information to determine an updated path cost of the included route and compared to alternate routes to select a preferred route based upon path cost. The selected preferred route is included in the packet and the packet is transmitted to another node according to the selected preferred route.