Utility Management System with Weather Normalization
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Solution Overview
Problem
Traditional utility management systems fail to effectively store and utilize audit, supply, and efficiency information to formulate strategies for reducing utility costs for customers, leading to unsatisfactory cost management.
Innovation Solution
A system that stores utility invoices, supply data, and site data to determine strategies for reducing utility costs by processing invoices, site data, and market data, and generates graphical user interfaces to display these strategies, while indexing data by service point identifiers for efficient retrieval and normalizing utility usage with respect to weather.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional utility management systems store only basic invoice information, then the system simplicity is maintained, but the ability to formulate cost reduction strategies is insufficient
Solution Approach 1:
The system segments utility management data into multiple categories including audit information, supply information, efficiency information, and weather data, storing each in separate data structures that can be independently processed and analyzed to formulate comprehensive cost reduction strategies
Solution Approach 2:
The utility management system is designed to perform multiple functions: storing invoices, storing audit information, storing supply information, storing efficiency information, normalizing usage data, and formulating cost reduction strategies, thereby eliminating the need for multiple separate systems
2Device complexity
If utility usage data is stored without normalization, then data storage simplicity is maintained, but accuracy in identifying non-weather-related usage issues is reduced
Solution Approach 1:
The system performs preliminary normalization of utility usage data by adjusting for weather conditions before analysis, using weather data to calculate normalized usage values that remove weather-related variations, thereby preparing the data for more accurate identification of non-weather-related usage issues
Solution Approach 2:
Weather data serves as an intermediary element that mediates between raw utility usage data and analyzed usage patterns, allowing the system to separate weather-related fluctuations from actual usage behavior through normalization calculations
3Reliability
If the system processes comprehensive data for cost reduction strategies, then strategy accuracy is improved, but processing time and complexity increase
Solution Approach 1:
The system performs preliminary processing and normalization of data before strategy formulation, organizing audit information, supply information, and efficiency information into structured formats in advance, thereby reducing the computational burden during actual strategy generation and analysis phases
Data Source
AI summary
A system comprises a memory storing a plurality of usage values. A usage value may be based at least on usage of a utility resource measured by a utility meter having a meter identifier. The memory may store a plurality of service point identifiers and a plurality of account identifiers associated with one or more utility accounts. A service point identifier represents a physical location of at least one utility meter. Each service point identifier may be stored in association with one or more usage values. The system may comprise a processor communicatively coupled to the memory. In response to a request comprising a particular service point identifier, the processor may retrieve one or more usage values from the memory based at least on the particular service point identifier in the request. The processor may generate a graphical user interface that displays the one or more retrieved usage values.