2018
DOI: 10.1504/ijaac.2018.10008724
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Load frequency control of multi-area interconnected thermal power system: artificial intelligence-based approach

Abstract: In the current work, an ant colony optimisation (ACO) optimisation technique for load frequency control was proposed for tuning the performance of the proportional-integral-derivative (PID) controller gain values. This led to oscillations suppression in the power system response. A system consisted of three equal thermal generating units equipped with (PID) controller was investigated. The PID controller gain values are obtained by using three different cost functions such as the integral square error (ISE), i… Show more

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Cited by 6 publications
(2 citation statements)
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“…Considerable support has been made by the researchers in order to tackle the frequency regulation issue in the PS. For instance, the authors has examined Load Frequency Control (LFC) in single-area systems (referenced as [8,9]), deregulated energy grids (referenced as [10,11]) , and multi-zone systems with non-linearities (referenced as [12][13][14]) To manage load frequency in power systems, numerous control mechanisms have been implemented, including robust sliding mode controllers [15], model predictive control reference in [16], linear-matrix inequality [17], artificial intelligence-based LFC [18], resilient control methodologies [19], data-driven controllers [20], and robust virtual inertia control [21] and fuzzy logic control (FLC) referenced as [21]. Historically, the PID controller has been the predominant choice for regulating the frequency of interconnected power systems owing to its straightforwardness and economical nature.…”
Section: Literature Studymentioning
confidence: 99%
“…Considerable support has been made by the researchers in order to tackle the frequency regulation issue in the PS. For instance, the authors has examined Load Frequency Control (LFC) in single-area systems (referenced as [8,9]), deregulated energy grids (referenced as [10,11]) , and multi-zone systems with non-linearities (referenced as [12][13][14]) To manage load frequency in power systems, numerous control mechanisms have been implemented, including robust sliding mode controllers [15], model predictive control reference in [16], linear-matrix inequality [17], artificial intelligence-based LFC [18], resilient control methodologies [19], data-driven controllers [20], and robust virtual inertia control [21] and fuzzy logic control (FLC) referenced as [21]. Historically, the PID controller has been the predominant choice for regulating the frequency of interconnected power systems owing to its straightforwardness and economical nature.…”
Section: Literature Studymentioning
confidence: 99%
“…Various control mechanisms have been introduced in PSs to address the issue of load frequency management. A few examples include model predictive control [14], robust sliding mode controllers [15], artificial intelligence-based LFC approach [16], linear matrix inequality [17], resilient control methodologies [18], data-driven controllers [19], fuzzy logic control (FLC) [20,21], and robust virtual inertia control [22]. To control the frequency of connected PSs, the classic PID controller has been the principal focus of academic research because of its ease of use and low cost.…”
Section: Introductionmentioning
confidence: 99%