Meter Data Management Workbin Segmentation
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Solution Overview
Problem
Utility companies face challenges in efficiently collecting, validating, and processing large volumes of data from numerous utility meters in an open operational framework, particularly due to the complexity of handling different meter types and communication protocols, which complicates meter reading and servicing events.
Innovation Solution
The solution involves organizing meter channels into workbins for efficient data processing, using asynchronous processes to manage receiver, validation, and estimation services, and minimizing database roundtrips through in-memory data structures, allowing for pre-configuration of metadata and historic data to streamline the parsing, validation, and estimation of incoming data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If meter data is collected from a large number of utility meters using multiple meter management techniques, then the quantity of data collected increases, but the complexity of handling different meter types and communication protocols increases
Solution Approach 1:
The system implements a universal data collection framework that can handle multiple meter types (electronic, mechanical, smart meters) and various communication protocols (RF, wired, wireless) through a single integrated platform. The receiver service is designed to accept data in different formats and convert them to a standardized internal representation, eliminating the need for separate handling logic for each meter type or protocol.
Solution Approach 2:
The patent introduces an intermediary layer consisting of receiver services, validation services, and estimation services that act as mediators between the diverse metering infrastructure and the core data management system. This intermediary layer handles the complexity of protocol translation, data validation, and anomaly detection, shielding the core system from the variability of different meter types and communication methods.
2Reliability
If meter reading and meter servicing events are handled separately by different technicians, then the specialization of tasks increases, but the coordination complexity and time consumption increase
Solution Approach 1:
The system merges meter reading events and meter servicing events into a unified data collection and processing framework. Both types of events are captured through the same receiver service infrastructure, and the workbin processing system handles both reading data and servicing data in an integrated manner, eliminating the need for separate coordination processes while maintaining task specialization through structured data handling.
3Reliability
If data processing is performed with frequent database roundtrips, then the data persistence reliability increases, but the system processing efficiency decreases
Solution Approach 1:
The system performs preliminary actions by pre-configuring workbins with all necessary metadata and historic data before data processing begins. This upfront preparation eliminates the need for repeated database queries during the actual data validation and estimation processes, as all required reference data is already loaded into memory when workbins are created.
Solution Approach 2:
The patent extracts frequently accessed data (metadata and historic data) from the database and loads it into in-memory data structures within the workbin objects. This extraction removes the bottleneck of repeated database roundtrips during data processing, allowing the system to operate primarily from in-memory data while maintaining data persistence through periodic commits to the database.
4Productivity
If asynchronous processes are used to manage receiver, validation, and estimation services, then the system throughput increases, but the coordination and synchronization complexity increases
Solution Approach 1:
The system segments the data processing workflow into distinct asynchronous components: receiver services that collect data, validation services that verify data quality, and estimation services that fill gaps. Each segment operates independently with its own event queue and processing logic, allowing parallel execution while maintaining clear boundaries between responsibilities. The workbin concept provides a natural segmentation unit that groups related meters and their data together.
Data Source
AI summary
A meter data management system includes one or more application servers configured to receive, validate and estimate received meter data. The one or more application servers may include various memory/media elements for storing raw and transformed meter data as well as software in the form of computer-executable instructions, which are executed by a processor to implement a variety of functions, including establishing a mapping between the plurality of external devices and a plurality of preconfigured processing workbins (e.g., collections of meter channels in the same time zones), transforming the received meter data into a plurality of data files identified by timing parameter and workbin, validating data provided in each data file, estimating missing or invalid data, and automatically writing validated (and optionally estimated) data as import files to a database server. Such clean data files are then imported to one or more dedicated databases installed on the database server.