Fuzzy Logic Power System Event Identification

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Solution Overview

Problem

Conventional methods for monitoring electrical power systems require human experts and may not effectively handle uncertainties and inaccuracies in data, leading to inefficiencies and increased costs in identifying and classifying power system events.

Innovation Solution

A method utilizing fuzzy logic to analyze data from power systems, including monitoring signals, applying fuzzy logic rules to detect and classify power system events, and integrating this analysis into a computer program for automated processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If human experts are used to analyze power system data, then measurement precision and reliability of event identification can be maintained, but loss of time and increased costs occur due to expert unavailability and high expenses

Engineering Contradiction:

Improvereliability of power system event identificationVSAvoidtime loss due to expert unavailability

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces the mechanical system of human expert analysis with an automated fuzzy logic-based computer system. The fuzzy logic engine processes power system data automatically, eliminating the need for human experts to be physically present and available for real-time analysis, thus resolving the time loss issue while maintaining reliable event identification through sophisticated computational algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service analysis where the fuzzy logic engine autonomously processes power system data, identifies events, and classifies them without requiring human intervention. The system serves itself by automatically learning from patterns and making decisions based on predefined fuzzy logic rules, thereby eliminating dependency on expert availability

Inventive Principle:

Principle #25Self-service

2Productivity

If automated analytical systems using classical logic are implemented, then productivity increases by eliminating human experts, but reliability decreases due to inability to handle uncertainties and inaccuracies in data

Engineering Contradiction:

Improveproductivity of power system monitoringVSAvoidreliability of event classification under uncertainty

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent changes the fundamental parameter of logic from classical binary logic to fuzzy logic. This parameter change allows the system to handle uncertainties and inaccuracies in power system data by using degrees of truth between 0 and 1, thereby maintaining high reliability in event classification while preserving the productivity benefits of automation

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The fuzzy logic system introduces dynamic adaptability to handle varying levels of data quality and uncertainty. The system can dynamically adjust its analysis based on the degree of certainty in input data, allowing it to maintain reliable performance across different operating conditions while remaining fully automated

Inventive Principle:

Principle #15Dynamics

3Loss of time

If automated analytical systems are implemented, then loss of time is reduced by eliminating human experts, but device complexity increases due to need for sophisticated algorithms to handle uncertainties

Engineering Contradiction:

Improvetime reduction through automationVSAvoidcomplexity of analytical system

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The patent introduces fuzzy logic as an intermediary layer between raw power system data and event classification decisions. This intermediary handles the complexity of uncertainty management in a structured way, allowing the system to maintain time efficiency through automation while managing computational complexity through standardized fuzzy logic processing frameworks

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9336491B2Identification of power system events using fuzzy logic

Publication Date: 2016.05.10 TEXAS A&M UNIVERSITY

AI summary

A method for analyzing an electrical power system using fuzzy logic includes: (a) acquiring data representing a signal of interest of the power system; (b) analyzing the signal using at least one fuzzy logic rule; and (c) based on the analysis, detecting and classifying at least one power system event within the power system.