Digital Controller for Reservoir Recharge Forecasting
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Solution Overview
Problem
Utility grids face challenges in controlling recharges from plants to reservoirs to compensate for discharges due to random adverse events, especially when discharges are large and rare, or extend beyond the initial time period, requiring effective management to balance utility supply and demand.
Innovation Solution
A digital controller system that uses input devices, sensors, and microprocessors to determine and control recharges based on historical data and exposure size classes, employing transfer functions to ensure recharges cover discharges while capping individual plant capacities and motivating sustainable practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If recharges are set equal to discharges from each plant, then the reservoir level is maintained, but individual plants cannot handle large rare discharges that exceed their recharge capacity
Solution Approach 1:
The patent combines the recharge responsibilities of multiple plants to collectively cover discharges from any single plant. When one plant experiences a large discharge, other plants contribute to its recharge, merging their capacities to handle events that would exceed individual plant limits.
Solution Approach 2:
The system creates a universal recharge mechanism where any plant can both receive recharges and provide recharges to others. This multi-functional approach allows plants to serve dual roles, enabling the system to handle various discharge scenarios that would be impossible for any single plant to manage alone.
2Ease of operation
If recharges are capped at individual plant capacity, then plants are protected from excessive demands, but the reservoir cannot be fully replenished after large discharges
Solution Approach 1:
The patent merges the recharge contributions of multiple plants to achieve total recharge volumes that exceed any single plant's capacity. By combining resources from multiple sources, the system can fully replenish the reservoir after large discharges while keeping individual plant demands manageable.
3Reliability
If transfer functions are adjusted to motivate sustainable practices, then long-term reliability improves, but short-term recharge flexibility is reduced
Solution Approach 1:
The transfer function is designed to be dynamic, automatically adjusting recharge requirements based on each plant's discharge history and performance. This dynamic adjustment motivates sustainable practices by making recharges contingent on actual plant behavior, while the automated nature preserves flexibility without requiring manual intervention.
Solution Approach 2:
The system incorporates feedback mechanisms where transfer functions are continuously updated based on plant performance data. This feedback loop motivates sustainable practices by linking future recharge requirements to past performance, while the automated feedback process maintains operational flexibility.
Data Source
AI summary
A digital controller controls discharges of a utility from a reservoir to a plant during a first time period and recharges of said utility from the plant back to the reservoir during a second time period. The reservoir can be any storage device. When the utility is electric power, the discharges make up for the power not generated by the plant due to an accident. The digital controller may use a balanced nonlinear transfer function to control the recharges based on the discharges. If there is a long duration discharge that extends beyond the end of the first time period, the digital controller may use a Monte Carlo simulation along with a tail distribution for the long duration discharge and the balanced transfer function to forecast the recharge required during the second time period.