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The supplementary control signal is provided by means of Power System Stabilizer (PSS), will damp the low frequency oscillations. This paper presents the design of fuzzy logic based power system stabilizers using genetic algorithms in multimachine power system. In the proposed fuzzy expert system, generator speed deviation and its derivative are chosen as input signals to fuzzy logic based power system...
This paper presents robust tuning of Proportional Integral Derivative Power System Stabilizers (PID-PSS) using artificial intelligence (AI) techniques. Tow heuristic methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used to PID-PSS parameters tuning minimizing an objective function and results are compared with each other which Eigen value analysis is used for comparison. The...
This paper compares and analyzes the economics of alternative maintenance plans for generating stations. The usual life-cycle investment decisions for power plant equipment involve definition of alternative scenarios with specified refurbishment dates. The aim of the paper is to present a method for the selection of optimal investment dates that minimizes the life-cycle cost of the analyzed equipment...
This paper presents an strategy approach to solve the optimal power flow (OPF) problem for reactive power dispatch which generally requires many power flow calculations. Artificial neural networks are employed to learn in an offline mode and substitute the role of power flow in the OPF which is formulated as a mix integer nonlinear optimization with network loss minimization as the objective. This...
A comparative analysis using different intelligent techniques has been carried out for the economic load dispatch (ELD) problem considering line flow constraints for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of this paper is to minimize the total production cost of the thermal power generation. Economic load dispatch (ELD) has been applied...
The genetic algorithm is a self-adapting probabilistic iterated search method, which is based on a principle of the natural choice and the natural genetic mechanisms. And it can simulate the development law of biological evolution in the natural world and can be used in the complex nonlinear optimization problems in continuous variables and discrete variables mixed.This paper uses the genetic algorithm...
The paper presents an improved method for a 24-hour load forecasting in the power system by using self organizing map (SOM) of Kohonen neural network .In this paper two models are compared with each other. The main difference between these models is about determining the training patterns procedure. In the first basic model, the training of neural networks performs in similar patterns with the most...
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