Probabilistic Sewer Flow Control for Overflow Prevention

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Solution Overview

Problem

Sewer systems face challenges in managing complex fluid flow and treatment processes, particularly due to unpredictable weather conditions that impact load on the systems, necessitating innovative management solutions.

Innovation Solution

The implementation of probabilistic forecast-based agent control systems for sewer management, which include storage chambers, flow condition attribute measuring devices, flow controllers, and flow-modifying devices to optimize fluid flow and treatment processes by using probabilistic weather forecasts to minimize differences between potential outcomes and current flow conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional sewer management systems are used, then system simplicity is maintained, but the ability to handle unpredictable weather-related loads is insufficient

Engineering Contradiction:

Improveability to handle unpredictable weather loadsVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by using probabilistic weather forecasts to predict future sewage loads before they occur. The controller proactively adjusts pump operations and storage chamber usage in advance of predicted heavy rainfall events, rather than reacting after overflow occurs. This allows the system to prepare adequate storage capacity beforehand.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops where sensors monitor actual flow conditions, storage chamber levels, and pump operations. This real-time data feeds back to the controller, which compares actual conditions against forecasted conditions and dynamically adjusts operations. The feedback mechanism enables the system to adapt to both predicted and actual weather-related load variations.

Inventive Principle:

Principle #23Feedback

2Reliability

If real-time flow monitoring and control is implemented, then overflow risk is reduced, but measurement and control complexity increases

Engineering Contradiction:

Improveoverflow prevention capabilityVSAvoidflow condition measurement complexity

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system replaces complex mechanical flow control mechanisms with an intelligent controller that uses probabilistic forecasts and real-time sensor data to make control decisions. Instead of relying on purely mechanical devices like float valves or overflow weirs, the controller dynamically adjusts electrically actuated pumps based on predictive algorithms, simplifying the mechanical components while improving reliability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the operational parameters of pumps and storage chambers dynamically based on forecasted weather conditions and real-time flow measurements. The controller adjusts pump speed, storage chamber filling levels, and flow distribution ratios as variable parameters rather than maintaining fixed settings. This allows adaptive optimization of overflow prevention without requiring overly complex measurement systems.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If probabilistic forecast-based control is implemented, then treatment process optimization is achieved, but energy consumption increases

Engineering Contradiction:

Improvetreatment process efficiencyVSAvoidpump and treatment energy consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system uses periodic probabilistic weather forecasts (e.g., hourly or daily updates) to guide control decisions rather than continuous real-time adjustment. The controller operates in cycles, updating its predictions and control strategy based on new forecast data and actual performance, which reduces computational energy requirements while maintaining treatment efficiency.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system applies partial treatment or full treatment selectively based on forecasted load conditions. During low-load periods predicted from weather forecasts, the system may use partial treatment processes that consume less energy. During high-load periods, full treatment is activated. This partial/excessive action approach optimizes energy usage by matching treatment intensity to actual needs rather than operating at constant capacity.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11781306B2Systems and methods using probabilistic forecast for agent-based control of sewers

Publication Date: 2023.10.10 XYLEM VUE INC

AI summary

Fluid stream management systems and methods relating thereto are described. The fluid management system includes: (1) one or more storage chambers; (2) two or more flow condition attribute measuring devices configured to measures certain flow condition attribute values; (3) one or more flow controllers that are communicatively coupled to receive the flow condition attribute values and use them to establish certain cost functions; and (4) one or more flow-modifying devices, each of which is coupled to at least one of the flow controllers, and based upon instruction received from at least one of the flow controllers, the flow-modifying device is capable of modifying flow of fluid through one or more of the flow-modifying devices to minimize a difference between the established cost functions.