Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

Izadbakhsh, Maziar; Rezvani, Alireza; Gandomkar, Majid

doi:10.2478/aee-2014-0038

Cited by 18 publications

(4 citation statements)

References 41 publications

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“…Izadbakhsh developed an ANFIS-based MPPT controller for solar PV and pitch angle regulators for the wind turbine generator in a grid-tied MG system [52]. A set of 360 data points from solar PV irradiance and the temperature was collected by using GA to train the ANFIS.…”

Section: Anfis-based Mpptmentioning

confidence: 99%

Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

et al. 2020

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The penetration of distributed generators (DGs) in the existing power system has brought some real challenges regarding the power quality and dynamic response of the power systems. To overcome the above-mentioned issues, the researchers around the world have tried and tested different control methods among which the computational intelligence (CI) based methods have been found as most effective in mitigating the power quality and transient response problems intuitively. The significance of the mentioned optimization approaches in contemporary ac Microgrid (MG) controls can be observed from the increasing number of published articles and book chapters in the recent past. However, literature related to this important subject is scattered with no comprehensive review that provides detailed insight information on this substantial development. As such, this research work provides a detailed overview of four of the most extensively used CI-based optimization techniques, namely, artificial neural network (ANN), fuzzy logic (FL), adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) as applied in ac MG controls from 42 research articles along with their basic working mechanism, merits, and limitations. Due to space and scope constraints, this study excludes the applications of swarm intelligence-based optimization methods in the studied field of research. Each of the mentioned CI algorithms is explored for three major MG control applications i.e., reactive power compensation and power quality, MPPT and MG’s voltage, frequency, and power regulation. In addition, this work provides a classification of the mentioned CI-based optimization studies based on various categories such as key study objective, optimization method applied, DGs utilized, studied MG operating mode, and considered operating conditions in order to ease the searchability and selectivity of the articles for the readers. Hence, it is envisaged that this comprehensive review will provide a valuable one-stop source of knowledge to the researchers working in the field of CI-based ac MG control architectures.

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Section: Anfis-based Mpptmentioning

confidence: 99%

Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

et al. 2020

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“…ANFIS can be used as an intelligent controller for several types of power issues [7][8][9]. ANFIS approach has been used for solving the resource allocation problem in a smart grid [10].…”

Section: Related Workmentioning

confidence: 99%

Optimization of Hybrid Power Systems Performance Based on Adaptive Neuro-Fuzzy Inference System

Al-mahjari

Al-Dobhany

2016

J. sci. technol.

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Hybrid Power Systems (HPSs) is a promising solution for the shortages of electricity in several situations. However, HPSs are still facing several problems. These problems are the cost of electrical kilowatt-hour and repetitive breaking in the utility grid with existence varying loads. Besides the problem of non-optimal utilization of available renewable energy resources and the problems associated with the operation of large generators along small loads, which are the high cost of generation and the minimize in lifetime of the generator. This paper presents study and analyze the load profile and power system generation for a selected case. A fuzzy control system based on ANFIS has been proposed to optimize the performance of the HPS. The proposed system has ten ANFIS models, which linked to the outputs of the proposed control system. All models have been trained to achieve the minimum root mean square error (RMSE). The proposed system has been built and simulated using MATLAB.

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“…To synchronize the converter with grid, a three phase lock loop (PLL) is used. PLL reduces the difference between grid phase angle and the inverter phase angle to zero using PI controller, thereby synchronizing the line side inverter with the grid [41]. …”

Section: P-q Control Strategymentioning

confidence: 99%

Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

Izadbakhsh¹,

Rezvani²,

Gandomkar³

2015

Archives of Electrical Engineering

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Abstract:In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator.

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Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

Cited by 18 publications

References 41 publications

Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

Optimization of Hybrid Power Systems Performance Based on Adaptive Neuro-Fuzzy Inference System

Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

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