Sizing Control and Hardware Implementation of a Hybrid Wind-Solar Power System, Based on an ANN Approach, for Pumping Water

Zarrad, Ons; Hajjaji, Mohamed Ali; Aymen, Jemaa; Mansouri, Mohamed

doi:10.1155/2019/5672032

Cited by 12 publications

(4 citation statements)

References 23 publications

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“…Xilinx always provides its designers with tools for the simplification of the digital systems' description phase. In fact, the XSG is a developed and excellent graphics tool for the creation, simulation, verification, implementation and validation of highly performant systems on Xilinx FPGA targets [61]. It is also a modeling tool for designing FPGA-based systems.…”

Section: Xsg Architectures Of Control Techniquesmentioning

confidence: 99%

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

Hermassi

Krim

et al. 2023

Electronics

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This paper presents a hardware implementation upon a Field Programmable Gate Array (FPGA) of improved Vector Control Strategies (VCSs) based on a Fuzzy Logic System (FLS) of a grid-connected wind energy conversion system. Usually, the classical VCS is based on fixed-gain Proportional Integral Derivative (PID) controllers, which are known to exhibit limited performance against the nonlinear behavior of wind systems, such as rapid fluctuations of the wind speed and uncertainties of the system parameters. In order to overcome this limitation, an improved VCS based on Fuzzy Gain Scheduling PID controllers (VCS-FGS-PID) is suggested in this work to guarantee good tracking, high accuracy and good robustness under system parameter variations. Indeed, the PID controller gains are tuned, in real-time, by the FLS. In addition, the proposed VCS-FGS-PID methods are implemented on the FPGA in order to reduce the delays and the period of the system of the control loop, thanks to its parallel processing. In fact, the performance of the suggested VCS-FGS-PID approaches are proved by digital simulation with the Xilinx system generator tool under Matlab/Simulink, in addition to an experimental hardware-in-the-loop implementation using the FPGA. The obtained results demonstrate that the proposed VCS-FGS-PID techniques offer better performance as regards good tracking and high accuracy and good robustness against stator resistance variability compared to VCS-PI.

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Section: Xsg Architectures Of Control Techniquesmentioning

confidence: 99%

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

Hermassi

Krim

et al. 2023

Electronics

Self Cite

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“…The first group includes classic strategies, like incremental conductance (INC) and Perturb and Observe (P&O). The second group covers intelligent strategies, like Fuzzy Logic (FLC), Artificial Neural Networks (ANN) [5]. The main requirements for maximum power point tracking are simple implementation and lower cost, fast tracking speed under rapid changes in solar irradiation and temperature changes, and fewer oscillations for operating points [6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the different maximum power point tracking strategies in a load-connected photovoltaic system

Zhao¹,

Farzaneh²

2022

Proceedings of International Exchange and Innovation Conference on Engineering &Amp; Sciences (IEICES)

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For the past few years, solar energy has been widely applied in renewable energy systems. Maximum Power Point Tracking (MPPT) indicates one of the essential techniques for enhancing the efficiency of photovoltaic (PV) systems. Therefore, a high-efficiency method that can be accurate and fast-track the maximum power point (MPP) of PV is eagerly desired. In this paper, four different MPPT methods are compared in MATLAB/Simulink, which include two conventional methods: Perturbation and observation (P&O) and Incremental conductance (INC), one advanced intelligent method: Fuzzy logic (FLC), and one improved fuzzy logic-based variable step INC (FL-INC). The goal of this study is to find the more superior MPPT. According to the simulation result, FL-INC can enhance the output power by more than 6%, reducing the convergence time with fewer oscillations.

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“…Also, cloud computing may provide an excellent way for processing large volumes of data without any hardware investment [60]. Once the training completes, the configuration (weights and activation functions) can be transferred to low-cost embedded systems based on FPGAs [61,62] or micro-controllers [63][64][65].…”

Section: Introductionmentioning

confidence: 99%

System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles

2021

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The integration of photovoltaic systems (PVS) in electric vehicles (EV) increases the vehicle’s autonomy by providing an additional energy source other than the battery. However, current solar cell technology generates around 200 W for a 1.4 m2 panel (to be installed on the roof of the EV) at stable irradiance conditions. This limitation in production and the sudden changes in irradiance produced by shadows of clouds, buildings, and other structures make developing a fast and efficient maximum power point tracking (MPPT) technique in this area necessary. This article proposes an artificial neural network (ANN)-based MPPT, called DS-ANN, that uses manufacturer datasheet parameters as inputs to the network to address this problem. The Bayesian backpropagation-regularization performs the training, ensuring that the MPPT technique operates satisfactorily on different PVS without retraining. We simulated the response of 20 commercial modules against actual irradiance data to validate the proposed method. The results show that our method achieves an average tracking efficiency of 99.66%, improving by 1.21% over an enhanced P&O method.

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Sizing Control and Hardware Implementation of a Hybrid Wind-Solar Power System, Based on an ANN Approach, for Pumping Water

Cited by 12 publications

References 23 publications

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

Analysis of the different maximum power point tracking strategies in a load-connected photovoltaic system

System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles

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