Improved performance of LQR controller in CSC based STATCOM using genetic optimization

Abstract

The static synchronous compensator (STATCOM) is the multiple input and multiple output system with versatile FACTS device for the enhancement of its dynamic performance in power systems. A novel method based on genetic algorithm is proposed to find the positive definite matrices (Q, R) for LQR based CSC-STATCOM. In this paper, the CSC based STATCOM is controlled by the LQR. But the best constant values for LQR controller's parameters are laboriously obtained through trial and error method, although time consuming. So the objective function of the genetic optimization problem is designed such that to find the optimal values of the LQR controller's parameters in a very short time with the desired criterion for the test system. Applicability of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results show an improvement in the outcomes of CSC-STATCOM.

Detecção De Avarias Em Isoladores De Potência: Uma Pesquisa Da Literatura Correlata À Utilização De Sistemas Inteligentes

“…Mesmo com inúmeras vantagens, o desempenho do LQR depende fortemente de dois componentes essenciais, suas matrizes de ponderação Q e R. Elas permitem que o controlador atenda as especificações do projeto, entretanto, tratam-se de valores com um grande espaço de busca, e definir essas matrizes pode se tornar um desafio tedioso e complexo, comprometendo os prazos definidos no projeto por conta da paralisia gerada (Gbaupe, 1972;Stein, 1979;Medanic, Tharp e Perkins, 1988). Visando minimizar os percalços causados por essa problemática, vem se consolidando o uso de diversos algoritmos de Inteligência Computacional (IC) para otimizar essa busca, tais como Algoritmo Genético (Gupta e Tripathi, 2014), Recozimento Simulado (Jaleel e Francis, 2013), entre outros.…”

Modelagem, Simulação E Análise De Movimento Do Robô Manipulador Scara T3 401ss Fabricante Epson

“…Mesmo com inúmeras vantagens, o desempenho do LQR depende fortemente de dois componentes essenciais, suas matrizes de ponderação Q e R. Elas permitem que o controlador atenda as especificações do projeto, entretanto, tratam-se de valores com um grande espaço de busca, e definir essas matrizes pode se tornar um desafio tedioso e complexo, comprometendo os prazos definidos no projeto por conta da paralisia gerada (Gbaupe, 1972;Stein, 1979;Medanic, Tharp e Perkins, 1988). Visando minimizar os percalços causados por essa problemática, vem se consolidando o uso de diversos algoritmos de Inteligência Computacional (IC) para otimizar essa busca, tais como Algoritmo Genético (Gupta e Tripathi, 2014), Recozimento Simulado (Jaleel e Francis, 2013), entre outros.…”

Controller parameter optimization for a 13‐level cascaded H‐bridge medium voltage static synchronous compensator

“…One of the member of the second generation FACTS devices is the “Static Synchronous Compensator (STATCOM),” which is used to compensate the reactive power and control system voltage dynamically . STATCOM control is challenging and thus there are different control methods, such as PI controllers, linear quadratic regulator, nonlinear passivity‐based control (PBC), clustered balancing control, and model predictive controller, in the literature. The fixed‐gain PI controllers are generally used in systems, which experience nominal load conditions, and therefore, the systems are linearized at the operation point before the application of the fixed‐gain PI controllers .…”

“…Particle swarm optimization is a widely used meta‐heuristic method for the optimization problems . It has been applied to fine‐tune the gains of the controllers .…”

“…This issue is addressed in some studies such as Zhang 11,33 Particle swarm optimization is a widely used meta-heuristic method for the optimization problems. 10 It has been applied to fine-tune the gains of the controllers. [34][35][36] PSO-based PI controller can be used to self-tune the gains of the controller as the system conditions and load change.…”