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Proceedings ArticleDOI

Load Frequency Control using PID tuned ANN controller in power system

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TLDR
In this article, a self-tuning ANN-based PID controller is applied to self tune the parameters of the PID controller to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading.
Abstract
The main objective of Load Frequency Control(LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that the compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take in to account possible changes in operating condition and non-linearities in the generator unit. Moreover, it lacks in roubustness. Therefore the simple neural networks can alleviate this difficulty. The ANN is applied to self tune the parameters of PID controller. Multi area system, have been considered for simulation of the proposed self tuning ANN based PID controller. The performance of the PID type controller with fixed gain, Conventional integral controller, and ANN based PID controller have been compared through MATLAB Simulation results. Comparison of performance responses of integral controller & PID controller show that the neural-network controller has quite satisfactory generalization capability, feasibility and reliability, as well as accuracy in multi area system. The qualitative and quantitative comparison have been carried out for Integral, PID and ANN controllers. The superiority of the performance of ANN over integral and PID controller is highlighted.

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Citations
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Robust Control for Microgrid Frequency Deviation Reduction With Attached Storage System

TL;DR: This work considers a microgrid where fossil fuel generators and renewable energy sources are combined with a reasonably sized, fast acting battery-based storage system, and develops robust control strategies for frequency deviation reduction, despite the presence of significant (model) uncertainties.
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Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units

TL;DR: In this article, the authors investigated a renewable energy resource's application to the Load-Frequency Control of interconnected power system, where the Proportional-Integral (PI) controllers are replaced with Proportral-Integrals Plus (PI+) controllers in a two area interconnected thermal power system without/with the fast acting energy storage devices and are designed based on Control Performance Standards (CPS) using conventional/Beta Wavelet Neural Network (BWNN) approaches.
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Load frequency control using battery energy storage system in interconnected power system

TL;DR: The qualitative and quantitative comparison of conventional controllers and BES system in Load Frequency Control of a typical two area interconnected power system is presented and the superiority of the performance of BES over conventional controllers is highlighted and discussed.
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Salp swarm algorithm-based model predictive controller for frequency regulation of solar integrated power system

TL;DR: The simulation result analysis shows that the proposed optimal MPC outpaces the conventional controllers with respect to peak overshoot, undershoot and settling time of the time responses, and a comparative study of various objective functions indicates that integral square error is better for the considered test system.
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Mitigating the Load Frequency Fluctuations of Interconnected Power Systems Using Model Predictive Controller

TL;DR: In this paper, a photovoltaic (PV) connected thermal system is discussed and analyzed by keeping PV to operate at maximum power point (MPP), where the main problem in the interconnection of these systems is load frequency fluctuations due to different load changing conditions.
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TL;DR: In this second edition the introductory chapters have been strengthened to improve appeal to students, and new problems and material has been added on system protection.
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Understanding automatic generation control

TL;DR: In this paper, the authors describe what automatic generation control (AGC) might be expected to do, and what may not be possible or expedient for it to do; the purposes and objectives of AGC are limited by physical elements involved in the process and the relevant characteristics of these elements are described.
Journal ArticleDOI

Adaptive fuzzy gain scheduling for load frequency control

TL;DR: An adaptive fuzzy gain scheduling scheme for conventional PI and optimal load frequency controllers and a Sugeno type fuzzy inference system is used in the proposed controller.
Journal ArticleDOI

An adaptive controller for power system load-frequency control

Abstract: An adaptive controller is presented for load-frequency control of power systems. It uses a PI (proportional-integral) adaptation to satisfy the hyperstability condition for taking care of the parameter changes of the system. Only the available information on the states and output are required for the control. No explicit parameter identification is needed. The controller can be designed by using a reduced plant model to simplify the design without degrading the performance much, so it is very easy to implement practically. The simulation results indicate that good control performance can be obtained and that the performance is sensitive to the plant parameter changes. The control remains effective in the presence of generation rate constraints. >