Water System Marginal Attribute Calculation
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Solution Overview
Problem
Conventional water supply systems lack the ability to accurately calculate and optimize the marginal attributes of water delivery, such as energy intensity, chemical use, and carbon emissions, at specific locations and times, leading to suboptimal resource allocation and management.
Innovation Solution
A method that calculates marginal attributes like energy intensity, chemical intensity, carbon intensity, and water quality by backtracking water flows from consumers to raw water sources, integrating values over location and time, and determining optimized operating schedules using heuristic or non-heuristic methods, incorporating devices like pumps and treatment equipment to quantify inputs and emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional system-level estimation methods are used to assess water attributes, then calculation simplicity is maintained, but measurement precision and resource allocation accuracy deteriorate
Solution Approach 1:
The patent segments the water supply system into discrete computational units (nodes, links, tanks, sources) and calculates marginal attributes for each segment individually. This allows precise tracking of energy, chemicals, and carbon emissions along specific water paths from sources to consumers, transforming a system-level estimation problem into manageable component-level calculations that can be aggregated for high precision results.
Solution Approach 2:
The patent introduces marginal attribute calculations as an intermediary layer between physical water flow and management decisions. By calculating marginal energy intensity, chemical intensity, and carbon intensity for each unit of water delivered to specific nodes, the system creates a detailed attribution mechanism that bridges the gap between complex system operations and actionable resource allocation insights without requiring complete system redesign.
2Productivity
If location-specific and time-specific marginal attributes are calculated, then resource allocation accuracy is improved, but computational complexity increases
Solution Approach 1:
The system divides the water network into discrete nodes and links, enabling independent calculation of marginal attributes for each segment. This segmentation allows the complex problem of location-specific resource allocation to be broken into manageable computational units, where energy, chemicals, and carbon emissions are tracked along specific paths from sources to individual nodes, improving allocation efficiency without overwhelming computational burden.
Solution Approach 2:
The patent dynamically calculates marginal attributes that change with location, time, and system operating conditions. By treating energy intensity, chemical intensity, and carbon intensity as variable parameters rather than fixed system averages, the system adapts to changing water demands and source conditions, enabling efficient real-time or near-real-time resource allocation decisions that reflect actual system state at each node and time period.
3Measurement precision
If detailed backtracking of water paths is performed, then accuracy of attribute attribution is improved, but loss of time in calculation increases
Solution Approach 1:
The patent pre-segments the water supply system into a fixed network topology of nodes and links before operation. This pre-established segmentation allows marginal attributes to be calculated and stored for each segment in advance or updated efficiently when system conditions change, eliminating the need for repeated full-path backtracking while maintaining accurate attribution of energy, chemicals, and carbon emissions to specific water deliveries at each node.
Solution Approach 2:
The system performs preliminary calculations of marginal attributes for each network segment based on source characteristics and path properties. By pre-calculating or pre-storing the energy intensity, chemical intensity, and carbon intensity for each link and node in the network, the system avoids time-consuming real-time backtracking when making allocation decisions, as the attribution data is already available from prior calculations or real-time monitoring at the node level.
4Adaptability or versatility
If multiple water sources and mixing at nodes are considered, then realism of model is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The patent uses marginal attribute calculations as an intermediary mechanism to track water sources and mixing without physically tracing individual water molecules. By assigning and propagating marginal energy, chemical, and carbon intensity values through the network nodes and links, the system indirectly detects and measures the contribution of each source to mixed water at any node, maintaining high model realism while avoiding the complexity of direct water path tracking.
Solution Approach 2:
The system models water mixing at nodes by tracking changes in marginal attribute parameters rather than physical water composition. When multiple sources mix at a node, the marginal energy intensity, chemical intensity, and carbon intensity parameters are updated to reflect the weighted combination of source contributions, providing a realistic representation of multi-source mixing while keeping detection and measurement straightforward through parameter monitoring rather than physical tracing.
Data Source
AI summary
Systems and methods for managing and operating a water supply system in accordance with embodiments on the invention are described. In an embodiment, the system calculates a set of one or more marginal values for a water supply system by: determining a set of transmission marginal values for a transmission stage, determining a set of treatment marginal values for a treatment stage, and determining a set of distribution marginal values for a distribution stage for a set of consumers, where the determining includes backtracking consumed water to a set of one or more raw water sources, identifying a set of one or more marginal paths of water supply from each raw water source to the consumer, and quantifying the intensity of inputs associated with the marginal paths.