Optimal Tuning of PID Controllers for Hydrothermal Load Frequency Control Using Ant Colony Optimization

Abstract

This paper proposes a novel Artificial Intelligence technique known as Ant Colony Optimization (ACO) for optimal tuning of PID controllers for load frequency control. The design algorithm is applied to a hydrothermal power system consisting of two control areas one hydro and the other is thermal with reheat stage. To make the system in realistic form, the system nonlinearities represented by Generation Rate Constraint (GRC), Dead Band, wide range of parameters are introduced. Three different cost functions have been suggested for tuning the PID controllers. The system has been tested for various load changes to reveal the effectiveness and robustness of the proposed technique.

Artificial Intelligence in Performance Analysis of Load Frequency Control in Thermal-Wind-Hydro Power Systems

“…Based on the quality and quantity of the food, pheromone quantity laid in the ground varied, it will guide to other ants to find the food source from their nest. This indirect communication between real ants through pheromone chemical is used to find the shortest path between food source and nest [24,31,32,34,41,42].…”

Cuckoo Search algorithm based load frequency controller design for nonlinear interconnected power system

“…EA is visualized to be very effective to deal with LFC problem due to its ability to treat nonlinear objective functions. Among the EA techniques, GA [24][25][26][27][28][29], PSO [30][31][32][33], Bacteria Foraging [34][35][36][37][38], Artificial Bee Colony [39], and Ant Colony Optimization [40] have attracted the attention in LFC controller design. Although these algorithms appear to be efficient for the design problem, they suffer from slow convergence problem in refined search stage, weak local search ability, which may lead them to get trapped in local minimum solution.…”

“…are represented in Generation Rate Constraint (GRC) and communication time delay. GRC illustrates the limitation on the generation rate of change in the output generated power due to the limitation of thermal and mechanical movements [4], for thermal stations it is taken to be 0.1 Pu Mw per minute [40]. On the other hand, communication time delay is introduced by many signal processing and data exchanging operations.…”

Load frequency control of two area power system with AC-DC tie line using PSO optimized controller

“…Authors of [5] observed that classical PID controller fails to give desirable performance in the presence of nonlinear and time-variant components even in the reduced mathematical order. Recently to tackle this problem of nonlinearity and time variance, lots of research has been done for designing robust controller using artificial intelligence (AI) techniques such as ant colony optimization [6], tabu search algorithm [7], genetic algorithm [8], neural networks [9] and fuzzy logic [10]. Moving in the same direction, authors of this present work made an attempt in using PSO based PID controller to get the best performance of LFC.…”