Power Grid Asset Forecasting for Inventory and Maintenance Planning
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Solution Overview
Problem
Existing resource distribution systems face challenges in accurately forecasting the timing of component replacements due to changing demands and varying usable lifespans of grid components, leading to inefficiencies in asset management and inventory management.
Innovation Solution
A system utilizing a processor and non-transitory computer-readable memory executes operations to receive queries, access data, and apply forecasting models to generate asset inventory and maintenance forecasts, leveraging historical data, sensor information, and growth trends to control ordering and scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional asset management methods are used based on fixed average usable lifespans, then inventory management is simplified, but forecasting accuracy deteriorates due to changing demands and varying component lifespans
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing data during asset operation (sensor data, maintenance history, operational conditions) to predict future asset behavior and failures before they occur, enabling proactive inventory and maintenance planning
Solution Approach 2:
The system implements feedback loops where actual asset performance data and maintenance outcomes are continuously fed back into the predictive models, allowing the system to learn from past predictions and improve forecasting accuracy over time while adapting to changing operational conditions
2Reliability
If inventory levels are increased to ensure component availability, then network downtime is reduced, but excess inventory costs increase
Solution Approach 1:
The system predicts which components will fail or need replacement in the near future and triggers inventory replenishment actions beforehand, ensuring critical components are available when needed without maintaining excessive inventory of all component types
Solution Approach 2:
The system dynamically adjusts inventory levels based on predicted asset lifespans, operational conditions, and failure probabilities, optimizing the balance between component availability and inventory costs by maintaining different inventory levels for different asset categories
3Reliability
If maintenance is performed frequently to ensure asset reliability, then asset failures are reduced, but productivity is decreased due to increased maintenance interruptions
Solution Approach 1:
The system enables assets to effectively monitor and report their own condition through embedded sensors and diagnostic capabilities, allowing maintenance to be performed based on actual asset needs rather than fixed schedules, thereby optimizing the balance between reliability and productivity
Data Source
AI summary
A system includes a processor and a non-transitory, computer-readable memory that includes instructions executable by the processor for causing the processor to perform operations. The operations include receiving a query including an asset inventory or maintenance question of an asset of a power distribution network. The operations further include accessing data of the power distribution network that is associated with the asset and applying a forecasting model to the query and the data of the power distribution network that is associated with the asset to generate an asset inventory or maintenance forecast. Additionally, the operations include controlling an ordering operation of the asset or a maintenance scheduling of the asset using the asset inventory or maintenance forecast.