Fuzzy Logic-Based Load Frequency Control in an Island Hybrid Power System Model Using Artificial Bee Colony Optimization

Kumar, Neelamsetti Kirn; Rahul, S G; Kuppusamy, Ramya; Nikolovski, Srete; Teekaraman, Yuvaraja; Indragandhi, V.; Venkateswarulu, Siripireddy

doi:10.3390/en15062199

Cited by 25 publications

(9 citation statements)

References 29 publications

(39 reference statements)

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“…Additionally, they offer the ability to control nonlinear systems to a level that surpasses the capabilities of conventional linear control systems. [24].…”

Section: Modelling Of Pv Systemmentioning

confidence: 99%

Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation

Nireekshana,

Ramachandran,

Narayana

2024

E3S Web Conf.

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The main objective of Load Frequency Control (LFC) is to effectively manage the power output of an electric generator at a designated site, in order to maintain system frequency and tie-line loading within desired limits, in reaction to fluctuations. The adaptive neuro-fuzzy inference system (ANFIS) is a controller that integrates the beneficial features of neural networks and fuzzy networks. The comparative analysis of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Proportional-Integral-Derivative (PID)-based methodologies demonstrates that the suggested ANFIS controller outperforms both the PID controller and the ANN controller in mitigating power and frequency deviations across many regions of a hybrid power system. Two systems are analysed and represented using mathematical models. The initial system comprises a thermal plant alongside photovoltaic (PV) grid-connected installations equipped with maximum power point trackers (MPPT). The second system comprises hydroelectric systems. The MATLAB/Simulink software is employed to conduct a comparative analysis of the outcomes produced by the controllers.

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“…Additionally, they offer the ability to control nonlinear systems to a level that surpasses the capabilities of conventional linear control systems. [24].…”

Section: Modelling Of Pv Systemmentioning

confidence: 99%

Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation

Nireekshana,

Ramachandran,

Narayana

2024

E3S Web Conf.

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“…A novel meta heuristic, derivative-free method named as a quasi-oppositional harmony search algorithm was used to improve the frequency stability in hybrid power systems [11]. Furthermore, sliding mode control [12,13], the bacterial foraging algorithm [14], artificial bee colony algorithm [15], etc., are used to overcome the FD problems in isolated hybrid power systems.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Frequency Regulation Support through Several Synthetic Inertial Approaches for WDPS

Asad,

Sanchez-Fernandez

2024

Electronics

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The aim of this paper is to propose an enhancement to the primary frequency control (PFC) of the San Cristobal Island hybrid wind–diesel power system (WDPS). Naturally, variable speed wind turbines (VSWT) provide negligible inertia. Therefore, various control strategies, i.e., modified synthetic inertial control, droop control and traditional inertial control, if introduced into VSWT, enable them to release hidden inertia. Based on these strategies, a WDPS has been simulated under seven different control strategies, to evaluate the power system performance for frequency regulation (FR). Furthermore, the student psychology-based algorithm (SBPA) methodology is used to optimize the WDPS control. The results show that modified synthetic inertial control is the most suitable approach to provide FR. However, further exhaustive research validates that droop control is a better alternative than modified synthetic inertial control due to the negligible system performance differences. In addition, droop control does not require a frequency derivative function in the control system. Therefore, the hybrid system is more robust. Moreover, it reduces the steady state error, which makes the power system more stable. In addition, a pitch compensation control is introduced in blade pitch angle control (BPAC) to enhance the pitch angle smoothness and to help the power system to return to normal after perturbations. Moreover, to justify the performance of hybrid WDPS, it is tested under certain real-world contingency events, i.e., loss of a wind generator, increased wind speed, fluctuating wind speed, and simultaneously fluctuating load demand and wind speed. The simulation results validate the proposed WDPS control strategy performance.

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“…A type 2 fuzzy PID controller for frequency control in hybrid distributed power systems was presented by the authors in [17]. A model of an island hybrid power system that uses artificial bee colony optimization for fuzzy logic-based load frequency management was described by the authors in [18]. The authors in [19] suggested a novel scaling factorbased fuzzy logic controller for frequency regulation of an isolated hybrid power system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

et al. 2023

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In this paper, the electrical parameters of a hybrid power system made of hybrid renewable energy sources (HRES) generation are primarily discussed. The main components of HRES with energy storage (ES) systems are the resources coordinated with multiple photovoltaic (PV) cell units, a biogas generator, and multiple ES systems, including superconducting magnetic energy storage (SMES) and pumped hydro energy storage (PHES). The performance characteristics of the HRES are determined by the constant power generation from various sources, as well as the shifting load perturbations. Constant power generation from a variety of sources, as well as shifting load perturbations, dictate the HRES’s performance characteristics. As a result of the fluctuating load demand, there will be steady generation but also fluctuating frequency and power. A suitable control strategy is therefore needed to overcome the frequency and power deviations under the aforementioned load demand and generation conditions. An integration in the environment of fractional order (FO) calculus for proportion-al-integral-derivative (PID) controllers and fuzzy controllers, referred to as FO-Fuzzy-PID controllers, tuned with the opposition-based whale optimization algorithm (OWOA), and compared with QOHSA, TBLOA, and PSO has been proposed to control the frequency deviation and power deviations in each power generation unites. The results of the frequency deviation obtained by using FO-fuzzy-PID controllers with OWOA tuned are 1.05%, 2.01%, and 2.73% lower than when QOHSA, TBLOA, and PSO have been used to tune, respectively. Through this analysis, the algorithm’s efficiency is determined. Sensitivity studies are also carried out to demonstrate the robustness of the technique under consideration in relation to changes in the sizes of the HRES and ES system parameters.

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Fuzzy Logic-Based Load Frequency Control in an Island Hybrid Power System Model Using Artificial Bee Colony Optimization

Cited by 25 publications

References 29 publications

Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation

Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation

Enhancing Frequency Regulation Support through Several Synthetic Inertial Approaches for WDPS

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

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