Fluid Consumption Estimation Using Dynamic Control Group Weighting
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Solution Overview
Problem
Current methods for estimating deleted fluid consumption during peak hours are inaccurate due to linear consumption assumptions and biases in control group selection, leading to over- or under-estimation and unacceptable errors, especially when deletion leads to payment or real-time adjustments.
Innovation Solution
A method using computer means to collect and analyze consumption data from two groups of fluid meters, one subscribed to deletion and one not, to calculate weighting coefficients that construct a control group comparable to the deletion group, allowing for precise real-time estimation of deleted fluid consumption by minimizing distance between groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If linear interpolation is used to estimate baseline consumption between deletion start and end, then the estimation method is simple to implement, but the precision of deletion estimation deteriorates due to incorrect assumption of linear consumer behavior
Solution Approach 1:
The patent applies preliminary action by collecting and analyzing consumption data from the control group before the deletion phase begins. This pre-collected data is used to establish a predictive model that accurately estimates baseline consumption during deletion, avoiding the need for simple linear interpolation and thereby improving estimation precision while maintaining implementation feasibility.
2Productivity
If a control group is selected to estimate baseline consumption, then the estimation can be performed in real-time, but the precision deteriorates due to bias between the control group and deletion group behaviors
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the composition and characteristics of the control group based on observed consumption patterns. The system modifies control group parameters (such as selecting facilities with similar profiles or adjusting weighting factors) to minimize behavioral differences between the control and deletion groups, thereby reducing estimation bias while maintaining real-time capability.
3Device complexity
If traditional deletion estimation methods are used, then the calculation process is simple, but the error rate increases making the results unacceptable for payment and market adjustments
Solution Approach 1:
The patent introduces an intermediary element - a carefully constructed control group of facilities that serve as a mediator between the deletion group and the baseline consumption reference. This control group acts as an intermediate reference that more accurately reflects what deletion group consumption would have been without deletion, thereby reducing error rates while keeping the overall system complexity manageable through automated data collection and analysis.
Data Source
AI summary
A device for estimating a deleted fluid consumption during a deletion phase, where said device comprises: a collection module configured to collect: a) first consumption data comprising information about the consumption of fluid from n fluid meters coming from a first group, and b) second consumption data comprising information about the consumption of fluid from m fluid meters coming from a second group, a computer analysis module which is configured for calculating, as a function of the first and second consumption data weighting coefficients βi minimizing the distance between the fluid consumptions of the first and second groups, where i is a positive integer included between 1 and m.