Genetic algorithm based controller for Load-Frequency Control of interconnected systems

Abstract

The main objective of this paper is to analyze the Load Frequency Control(LFC) of a two-area interconnected hydrothermal system considering a Thyristor Controlled Phase Shifter(TCPS) in series with the tie-line . The proposed controller are tested for a two area hydrothermal system considering the practical aspect of the problem such as Deadband and Generation Rate Constraint (GRC) etc. First of all, modeling of the two area hydrothermal system is performed and then there is a installation of TCPS incorporated with Tie-Line. After it, TCPS control scheme is implemented in the given two area power system. Here we consider the ISE (Integral Square Error) as a objective function which is to be minimize and by using optimization technique via Genetic Algorithms, hence, minimize the system error and corresponding integral gain of the system is obtained for stabilization of system frequency deviation as well as net tie-line power flow of the two area hydrothermal system kept within the normal operating range.

Analysis of LFC in PV‐thermal‐thermal interconnected power system using fuzzy gain scheduling

“…Jagatheesan et al analyzed LFC for hydro‐hydro power system using FLC. Shankar et al analyzed genetic algorithm–based LFC in two‐area interconnected power system. Zamee et al discussed differential evolution algorithm, which is an advanced form of genetic algorithm for LFC in two‐area power plant.…”

Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms

“…In addition, many of meta-heuristic-based optimisation methods such as genetic algorithm [13,14], particle swarm optimisation (PSO) [2,15], ant colony optimisation [16], artificial bee colony (ABC) algorithm [17], firefly algorithm [18], teaching learningbased optimisation [19], ant lion optimiser [20], water cycle algorithm (WCA) [21] and other methods [1,[22][23][24][25][26][27][28][29] were proposed to attain the same target.…”

“…Improved performance does not absolutely mean that these methods have not any restrictions. A number of limitations and some weaknesses of the aforementioned techniques have been found and reported in [13,27,28], such as the possibility of trapping into local minima, tedious efforts for tuning the algorithm control parameters and so on. Therefore, performance enhancement of the AGC of interconnected power systems represents a greater challenge for the control designers.…”

Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System

“…For micro grid networks with photovoltaic (PV) systems, battery units, micro wind turbines (MWT), and fuel cells, the most suitable control method is a self-adjusting control method [11,13,14]. Hence, Shankar et al realized a genetic algorithm (GA) for LFC in a two area interconnected hydro-thermal power system [15]. Additionally, another comparative study presented a controller employing linear matrix inequalities (LMI) and a controller optimized GA (GALMI) for a three area interconnected power system, simulated by Rerkpreedapong et al [16].…”