Modeling and Design of a Grid-Tied Renewable Energy System Exploiting Re-Lift Luo Converter and RNN Based Energy Management

被引:0
作者
Paulsamy, Kavitha [1 ]
Karuvelam, Subha [1 ]
机构
[1] Govt Coll Engn, Dept Elect & Elect Engn, Tirunelveli 627007, Tamil Nadu, India
关键词
PV system; WECS; GWO-HCO algorithm; PI controller; Re-lift Luo converter; RNN; CONTINUOUS INPUT; FAULT LOCATION; VOLTAGE; MPPT;
D O I
10.3390/su17010187
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The significance of the Hybrid Renewable Energy System (HRES) is profound in the current scenario owing to the mounting energy requirements, pressing ecological concerns and the pursuit of transitioning to greener energy alternatives. Thereby, the modeling and design of HRES, encompassing PV-WECS-Battery, which mainly focuses on efficient power conversion and advanced control strategy, is proposed. The voltage gain of the PV system is improved using the Re-lift Luo converter, which offers high efficiency and power density with minimized ripples and power losses. Its voltage lift technique mitigates parasitic effects and delivers improved output voltage for grid synchronization. To control and stabilize the converter output, a Proportional-Integral (PI) controller tuned using a novel hybrid algorithm combining Grey Wolf Optimization (GWO) with Hermit Crab Optimization (HCO) is implemented. GWO follows the hunting and leadership characteristics of grey wolves for improved simplicity and robustness. By simulating the shell selection behavior of hermit crabs, the HCO adds diversity to exploitation. Due to these features, the hybrid GWO-HCO algorithm enhances the PI controller's capability of handling dynamic non-linear systems, generating better control accuracy, and rapid convergence to optimal solutions. Considering the Wind Energy Conversion System (WECS), the PI controller assures improved stability despite fluctuations in wind. A Recurrent Neural Network (RNN)-based battery management system is also incorporated for accurate monitoring and control of the State of Charge (SoC) and the terminal voltage of battery storage. The simulation is conducted in MATLAB Simulink 2021a, and a lab-scale prototype is implemented for real-time validation. The Re-lift Luo converter achieves an efficiency of 97.5% and a voltage gain of 1:10 with reduced oscillations and faster settling time using a Hybrid GWO-HCO-PI controller. Moreover, the THD is reduced to 1.16%, which indicates high power quality and reduced harmonics.
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页数:33
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共 41 条
  • [1] Abd Ali J, 2016, J TEKNOL, V78, P27
  • [2] Al-Saeedi A.A.K., 2018, Int. J. Appl. Eng. Res, V13, P9549
  • [3] Analysis and Implementation of a Nonisolated Bidirectional DC-DC Converter With High Voltage Gain
    Ardi, Hossein
    Ajami, Ali
    Kardan, Faezeh
    Avilagh, Shahla Nikpour
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2016, 63 (08) : 4878 - 4888
  • [4] Control of Wind Energy Conversion Systems Based on the Modular Multilevel Matrix Converter
    Diaz, Matias
    Cardenas, Roberto
    Espinoza, Mauricio
    Rojas, Felix
    Mora, Andres
    Clare, Jon C.
    Wheeler, Pat
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 64 (11) : 8799 - 8810
  • [5] A New SEPIC-Based Step-Up DC-DC Converter With Wide Conversion Ratio for Fuel Cell Vehicles: Analysis and Design
    Elsayad, Nour
    Moradisizkoohi, Hadi
    Mohammed, Osama
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (08) : 6390 - 6400
  • [6] Renewable Energy-Aware Machine Scheduling Under Intermittent Energy Supply
    Ertem, Mehmet
    [J]. IEEE ACCESS, 2024, 12 : 23613 - 23625
  • [7] A Hybrid of Grey Wolf Optimization and Genetic Algorithm for Optimization of Hybrid Wind and Solar Renewable Energy System
    Geleta, Diriba Kajela
    Manshahia, Mukhdeep Singh
    [J]. JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF CHINA, 2022, 10 (04) : 749 - 762
  • [8] Design and Implementation a Single-Switch Step-Up DC-DC Converter Based on Cascaded Boost and Luo Converters
    Gholizadeh, Hossein
    Shahrivar, Reza Sharifi
    Hashemi, Mir Reza
    Afjei, Ebrahim
    Gorji, Saman A.
    [J]. ENERGIES, 2021, 14 (12)
  • [9] Enhanced energy harvesting from shaded PV systems using an improved particle swarm optimisation
    Gopalakrishnan, Satheesh Krishnan
    Kinattingal, Sundareswaran
    Simon, Sishaj Pulikottil
    Ark Kumar, Kevin
    [J]. IET RENEWABLE POWER GENERATION, 2020, 14 (09) : 1471 - 1480
  • [10] Improved Grey Wolf Optimization Algorithm and Application
    Hou, Yuxiang
    Gao, Huanbing
    Wang, Zijian
    Du, Chuansheng
    [J]. SENSORS, 2022, 22 (10)