Optimal load frequency control of multi-area multi-source deregulated power system with electric vehicles using teaching learning-based optimization: a comparative efficacy analysis

Kumar, Rajan; Prasad, Lal Bahadur

doi:10.1007/s00202-023-02027-7

Cited by 2 publications

(2 citation statements)

References 39 publications

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“…Simulation results validate the proposed controller's effectiveness in various scenarios. In [7], the research analyzes the effectiveness of electric vehicle (EV) charging/discharging as a distributed energy source in a multi-area multi-source deregulated power system. It evaluates the role of EVs in mitigating frequency deviations, using an optimal control scheme based on the TLBO algorithm.…”

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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“…A two-area two-source power system for LFC with EVs using different optimization controllers is presented in [21]. In the context of the MAMS-DPS LFC problem, the effectiveness analysis of EV charging and discharging as a sink or DES is presented in [22]. A LFC scheme using type-2 fuzzy system PID control for MGs with EVs is presented in [23].…”

Section: Introductionmentioning

confidence: 99%

Application of TLBO for Optimal AGC of Interconnected Multi-Area Multi-Source Hybrid Power System with DRC

Kumar,

Prasad

2024

Preprint

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As a first attempt this article investigates the load frequency regulation, an automatic generation control (AGC) problem of an interconnected multi-area multi-source hybrid power system (MAMS-HPS) with demand response contribution (DRC) using the teaching learning-based optimisation (TLBO) algorithm. Here, the MAMS-HPS is configured containing the micro-hydro, biogas, biodiesel, solar-thermal, and wind turbine generating units arranging in interconnected two-unequal areas. Due to the increased presence and penetration of RES in power system, a high degree of unpredictability and dependence on the nature significantly introduces the difficulty in balancing the generation and load demand. To address this problem, an approach is taken to optimize proportional-integral-derivative (PID) controller gains using optimisation algorithms namely the particle swarm optimisation (PSO) and TLBO to accessing the responses under various realistic scenarios of availability and variations of RES as well as load variations. The responses are accessed by adding a DRC system also. The MATLAB-Simulink model is developed for the system simulation and comparative performance analysis of control schemes in terms of time domain specifications observing the responses of the system states.

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Optimal load frequency control of multi-area multi-source deregulated power system with electric vehicles using teaching learning-based optimization: a comparative efficacy analysis

Cited by 2 publications

References 39 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

Application of TLBO for Optimal AGC of Interconnected Multi-Area Multi-Source Hybrid Power System with DRC

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