Abstract

Standard frequency and voltage levels need to be maintained when the electric power system is running in order to keep it in a satisfactory state of operation. Between AC power generation and use, there should be a balance between active and reactive power. However, due to variations in active and reactive power requirements, the frequency and voltage provided may fluctuate from their rated values. Any unwelcome change in frequency or voltage can have an immediate effect on how the power system operates and may even cause harm to linked devices. These parts are intended to operate at certain rated frequencies and voltage levels, and any variation could trip connected loads and power producing equipment. For maintaining a constant frequency, an effective load frequency control (LFC) design is required. A proportional-integral-derivative (PID) controller is used by a load frequency control (LFC) to keep the frequency near the rated values. By adjusting its proportional, integral, and derivative gains, the PID controller lowers the absolute errors of the frequency deviation that make up its integral. This study suggests two techniques for adjusting the PID controller parameters: tuning for artificial neural networks and Particle Swarm Optimization (PSO). On a single-area system, both tuning techniques are used in the LFC loop, and their performance is contrasted in terms of overshoot, undershoot, and settling time. The suggested tuning strategies outperform more traditional methods in terms of transient stability and steady-state stability.

Library of Congress Subject Headings

Intelligent control systems; Electric power=plants--Load dispatching; Electric current converters

Publication Date

1-2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Electrical Engineering (MS)

Advisor

Abdulla Ismail

Campus

RIT Dubai

Plan Codes

EEEE-MS

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