PV Fault Alert Prioritization Using Root-Cause Mapping
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Solution Overview
Problem
Photovoltaic (PV) systems face challenges in identifying and addressing faults effectively, leading to reduced power generation potential due to factors like panel shading, component degradation, and configuration issues, which existing fault analysis systems struggle to monitor and notify users about in a timely and accurate manner.
Innovation Solution
The implementation of a fault identification and notification system that uses mapping techniques, lookup tables, and impact value calculations to convert technical fault data into actionable notifications, prioritizing maintenance resources based on severity and user-specific policies, and utilizing machine learning to adapt to user needs and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fault identification system is implemented to monitor PV system components, then system reliability and power generation efficiency are improved, but device complexity and implementation cost increase
Solution Approach 1:
The fault identification system divides the PV system into discrete monitorable components (panels, inverters, converters) with individual fault identification codes for each component type and failure mode. This segmentation allows targeted monitoring without requiring system-wide complexity
Solution Approach 2:
The patent introduces an intermediary processing system that receives raw fault data from various PV components, processes it through standardized mapping tables, and generates simplified notifications. This intermediary layer abstracts the complexity from both the physical PV components and the user interface
2Loss of information
If comprehensive fault monitoring is implemented across all PV system components, then loss of information about system faults is reduced, but device complexity and data processing requirements increase
Solution Approach 1:
The patent implements a universal fault notification system that handles multiple component types (panels, inverters, converters) and various fault modes through a single standardized processing framework. The mapping tables and notification procedures are universally applicable across different PV system configurations
Solution Approach 2:
The system transforms raw fault parameters from various components into standardized notification parameters using mapping tables. This parameter transformation consolidates diverse fault data into a unified notification format, reducing information loss while simplifying processing
3Loss of time
If real-time fault notification is implemented, then loss of time for fault response is reduced, but use of energy and computational resources increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring mapping tables that associate fault identification codes with notification parameters and severity levels. When a fault occurs, the system simply looks up the pre-defined notification parameters rather than computing them in real-time, reducing computational energy consumption while maintaining fast response times
Data Source
AI summary
A fault identification may be triggered by a component of a power generation system (PGS), such as a hardware component, a controller of a hardware component, a device of the PGS, a computer connected to the PGS, a computer configured to monitor the PGS, and/or the like. The fault identification may be the result of a failure of a component of the PGS, a future failure of a component of the PGS, a routine maintenance of the PGS, and/or the like. The fault is converted to a notification on a user interface using a mapping of faults, root-causes, notification rules, and/or the like. The conversion may use one or more lookup tables and/or formulas for determining the impact of the fault on the PGS, and/or the like.