Frequency Stability Analysis of Power System Using Competition Over Resources Technique Optimized PIDA Controller

Patel, Sunita; Mohanty, Banaja; Simhadri, Kumaraswamy

doi:10.1007/s40998-021-00460-7

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…Sensitivity analysis confirms the controller's ability to handle significant system changes. In [10], the research analyzes the impact of renewable energy sources and energy storage devices on AGC in power systems, focusing on a new PIDA controller. The controller parameters are optimized using the competition over resources (COR) algorithm and compared with other optimization techniques.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

2023

IJFMR

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In the rapidly evolving landscape of power systems, achieving a stable and efficient Automatic Generation Control (AGC) remains paramount. The exigency for this research stems from the critical role AGC plays in maintaining frequency and power balance amidst dynamic system changes. The consequences of inadequacies in AGC manifest as frequency deviations, system instabilities, and potential blackouts, with widespread socio-economic implications for different use cases. Historically, various controllers have been proposed and implemented to address AGC challenges. However, existing methodologies have displayed inherent limitations. Predominant issues include lack of adaptability to non-linearities, slow response times, inability to cater to the multifaceted nature of modern power grids with renewable integrations, and susceptibility to uncertainties and disturbances. This comprehensive review delves deep into the spectrum of controllers available for AGC, encompassing conventional PI/PID controllers, robust controllers, adaptive controllers, intelligent controllers, and the more recent forays into neural network-based and fuzzy logic controllers. Each controller's salient features, operational dynamics, advantages, and shortcomings are meticulously dissected. Furthermore, this paper elucidates the contexts in which each controller type excels or is found wanting, providing invaluable guidance for system designers and operators. In essence, this review serves as a holistic compass for stakeholders involved in power system operation and design. It offers both a retrospective understanding and prospective insights, assisting decision-makers in choosing the most suitable controller for a given scenario. Whether one aims to optimize AGC for a traditional grid, a grid with high renewable penetration, or a hybrid system, this paper promises to be an indispensable reference for researchers.

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Section: Literature Reviewmentioning

confidence: 99%

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

2023

IJFMR

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“…It is also obvious from the literature that various contributions mention mostly linear models of power systems in the form of transfer functions. The proportionalintegral-derivative (PID) controllers are primarily developed to regulate the overall system [4], [5], [12], [15]- [20], since transfer functions are used to describe the power systems investigated. Other kind of PID controllers include proportional-integral (PI) [21], integral-double derivative (IDD) [22], proportional-integral-double derivative (PIDD) [23], proportional-derivative cascaded proportional-integral (PD-PI) [24], and cascaded PI-PD [25], cascaded PID-PID [26] controllers.…”

Section: Introductionmentioning

confidence: 99%

“…Optimization techniques utilized are meta-heuristic approaches to minimise the objective function specified for controller tuning. Genetic algorithm [27], [28], gravitational search algorithm [29], [30], bacteria foraging optimization [31], [32], bat algorithm [33], [34], teaching learning based optimization [35], [36], firefly algorithm [37], [38], particle swarm optimization [39], [40], artificial bee colony [41], [42], jaya algorithm [19], [43], and whale optimization [15], [44] are some of the algorithms used in literature for tuning PID controllers for AGC.…”

Section: Introductionmentioning

confidence: 99%

Rank-Sum-Weight Method Based Systematic Determination of Weights for Controller Tuning for Automatic Generation Control

et al. 2022

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The design and performance evaluation of a grey wolf optimizer (GWO) aided rank-sumweight method based proportional-integral-derivative regulator with derivative filter (PIDn) for automatic generation control (AGC) of two-area interconnected power systems are presented in this research. The derivative gain filter is used to lessen the impacts of noise in the input signal. Sub-objectives based on integral of time multiplied square error (ITSE) of frequency deviations, tie-line power deviation, and areacontrol errors (ACEs) are used to formulate the objective function for adjusting regulator settings. A single overall objective function is formed by combining these sub-objectives. ITSEs of two areas, ITSEs of tieline power deviation, and ITSEs of ACEs of two areas comprise up the overall objective function. In the control design, the weights in the overall objective function are used to evaluate relative significance of each sub-objective. In contrast to previous techniques, where weights are either considered equal by ignoring the relative relevance of sub-objectives or selected randomly, the weights in this article are obtained using the rank-sum-weight method systematically. Using the GWO algorithm, the overall objective function is minimized. For six different circumstances including different load disturbances in interconnected areas, the effectiveness of the proposed GWO aided rank-sum-weight method based controller is examined. The performance of the GWO-tuned controller is also compared to those of other controllers tuned using the differential evolution, elephant herding optimization, Nelder-Mead simplex, membrane computing, and Luus-Jaakola algorithms. Time domain specifications are tabulated for each of the six circumstances. The findings are also plotted to demonstrate the frequency and tie line power fluctuations. A statistical analysis is also performed in order to assess the overall efficacy of the suggested controller.

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Student Psychology-Based Optimization Tuned PIDA Controller for Improved Frequency Regulation of a Two-Area Microgrid

Gupta,

Mukhopadhyay,

Banerji

et al. 2024

Arab J Sci Eng

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Frequency Stability Analysis of Power System Using Competition Over Resources Technique Optimized PIDA Controller

Cited by 6 publications

References 28 publications

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

Comparative Analysis of Various Controllers used for Automatic Generation Control in Electrical Power Systems

Rank-Sum-Weight Method Based Systematic Determination of Weights for Controller Tuning for Automatic Generation Control

Student Psychology-Based Optimization Tuned PIDA Controller for Improved Frequency Regulation of a Two-Area Microgrid

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