Microgeneration Data Analysis for Grid Load Management
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Solution Overview
Problem
Utilities face challenges in incorporating microgeneration capacity into load forecasting and generation response incentive programs due to a lack of detailed data on microgenerating entities' power output timing and amounts, which hinders efficient grid management during peak and off-peak periods.
Innovation Solution
A system and method for analyzing electrical generation data by collecting and processing data from microgenerating devices at metered locations to identify preferred times for outputting power to the grid, using a database to store and associate usage data with time periods, and providing notifications for generation response incentives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If utilities collect and store detailed microgeneration data in databases, then grid management efficiency improves, but data processing complexity increases
Solution Approach 1:
The patent segments microgeneration data into distinct categories including generation data, consumption data, and net export data. Each data type is stored in separate database tables with specific schemas, allowing utilities to process and analyze different data types independently while maintaining overall grid management efficiency
Solution Approach 2:
The patent introduces a data processing system that acts as an intermediary between data collection from microgenerating devices and grid management applications. This intermediary system standardizes data formats, validates data integrity, and prepares data for analysis, thereby reducing processing complexity while improving grid management efficiency
2Adaptability or versatility
If utilities analyze microgeneration usage patterns to identify preferred time periods, then generation response incentive programs improve, but data analysis requirements increase
Solution Approach 1:
The patent implements preliminary data processing steps that pre-calculate and store key usage patterns and preferences before incentive programs are executed. By pre-analyzing microgeneration data to identify preferred time periods and patterns, the system reduces the computational burden during actual incentive program implementation while maintaining program effectiveness
Solution Approach 2:
The patent establishes feedback loops where analyzed usage patterns from the database inform and refine generation response incentive programs. The system continuously processes microgeneration data, identifies patterns, and uses this information to optimize incentive structures, creating an adaptive system that improves effectiveness while managing analysis requirements through iterative refinement
Data Source
AI summary
A method for analyzing electrical generation data includes receiving data associated with a generating device at a metered location and storing the data associated with the generating device in a database, receiving data associated with time periods that the generating device is used at the metered location and storing the data in the database, associating the received data associated with a generating device with the data associated with time periods that the generating device is used at the metered location, processing the received data associated with a generating device with the data associated and the time periods that the generating device is used at the metered location to identify time periods that the generating device outputs electrical power to an electrical grid, and identifying a preferred time period that the generating device may be used to output power to the grid.