Power System Stabilizer Auto-Tuning Using PSO and Frequency Response
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Solution Overview
Problem
Current power generating systems require manual tuning of integral of accelerating power type Power System Stabilizers (PSS), which is time-consuming, costly, and requires expertise, leading to high costs and inefficiencies in commissioning generators.
Innovation Solution
A system and method for automatically tuning PSS parameters using particle swarm optimization (PSO) and digital excitation control systems, which includes sensors, an automatic voltage regulator, and a control module to determine lead-lag phase compensation time constants and gain values, reducing the need for manual processes and trial-and-error methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual tuning of PSS parameters is performed, then expertise and experience can be utilized to achieve stable system performance, but the commissioning process becomes time-consuming and costly
Solution Approach 1:
The system performs self-tuning by automatically determining PSS parameters through computational algorithms (particle swarm optimization and frequency response analysis) without requiring external expert intervention. The control module autonomously analyzes system characteristics and configures optimal parameters, enabling the system to serve itself during commissioning.
Solution Approach 2:
The patent replaces manual mechanical tuning processes with automated computational methods. Instead of experts manually adjusting parameters based on experience, the system uses digital algorithms including particle swarm optimization and frequency response analysis to automatically determine optimal PSS parameters.
2Manufacturing precision
If manual tuning processes are used, then detailed expert knowledge can be applied, but the complexity and cost of the commissioning process increases
Solution Approach 1:
The system automatically determines optimal PSS parameters (lead-lag time constants and gain values) through computational analysis of system frequency response characteristics. The control module calculates parameters such as T1, T2, T3, and Ks based on measured system behavior, replacing manual parameter adjustment with automated parameter optimization.
Solution Approach 2:
The system uses feedback from system measurements (terminal voltages, frequency responses) to automatically adjust and determine PSS parameters. The control module analyzes the measured frequency response and iteratively optimizes parameters to achieve desired system performance, creating a closed-loop commissioning process.
3Reliability
If trial-and-error methods are employed for PSS tuning, then system performance can be empirically optimized, but the commissioning cost and duration increase significantly
Solution Approach 1:
The system performs preliminary automated analysis of system characteristics before actual PSS implementation. The control module pre-determines optimal parameters through frequency response analysis and computational optimization, eliminating the need for subsequent trial-and-error adjustments and enabling direct deployment of optimized settings.
Data Source
AI summary
A system and method for automatically tuning/configuring a power system stabilizer (PSS) in a power system digital excitation control system having an automatic voltage regulator (AVR) that includes providing a control input to the AVR as a function of generating a set of tuning PSS lead-lag phase compensation time constants as a function of received generated terminal voltages, generating an uncompensated frequency response as a function of the received set of generated terminal voltages and using particle swarm optimization (PSO) as a function of the generated uncompensated frequency response, generating a tuning PSS gain value as a function of a determined open loop frequency response of the power system, determining a PSS gain margin, determining a tuning PSS gain; and transmitting the determined set of tuning phase compensation time constants and the determined tuning PSS gain value to the control interface of the PSS.