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ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter
Electrical Engineering ( IF 1.8 ) Pub Date : 2021-02-17 , DOI: 10.1007/s00202-021-01231-7
B. Kavya Santhoshi , K. Mohanasundaram , L. Ashok Kumar

The multidimensional purposes of grid-tied hybrid renewable system such as tracking of maximum power, increasing the power conversion efficiency, reducing the harmonic distortions in the injected current and control over power injected into the grid are presented in this paper by developing a laboratory-scale setup. To ensure continuous current operation at the shoot through mode of grid connected inverter, a switched Z-source converter is utilized at the PV side. The PWM rectifier connected with the wind turbine transforms AC power into dc. Individual power converters with conventional PI controllers have been dedicated for each power source, and control strategy uses only one reference voltage so as to increase the maximum power tracking speed from both PV and wind sources. The battery energy management is performed by artificial neural network (ANN) to enhance the stable power flow and increase the lifespan of the storage system. Finally, the voltage at the point of common coupling is fed to ANN-based space vector-modulated three-phase inverter and the converted AC power is injected to the grid. The overall system performance is measured by estimating the quality of injected power. A stable operation of the proposed microgrid system is verified by varying input and load at the grid. A continuous-time simulation model is realized in MATLAB and is validated using experimental prototype. This benchmark system provides various research scopes for the future smart grids.



中文翻译:

通过开关Z源转换器馈入的并网混合可再生电力系统中逆变器和电池的基于ANN的动态控制和能量管理

通过开发实验室规模,本文提出了并网混合可再生系统的多维目的,例如跟踪最大功率,提高功率转换效率,减少注入电流中的谐波失真以及控制注入电网的功率。设置。为了确保在并网逆变器的直通模式下连续电流运行,在PV侧使用了一个开关Z源转换器。与风力涡轮机相连的PWM整流器将交流电转换为直流电。具有传统PI控制器的单个电源转换器专用于每种电源,并且控制策略仅使用一个参考电压,以提高来自PV和风能源的最大电源跟踪速度。电池能量管理通过人工神经网络(ANN)进行,以增强稳定的潮流并延长存储系统的使用寿命。最后,将公共耦合点的电压馈送到基于ANN的空间矢量调制三相逆变器,并将转换后的交流电注入电网。总体系统性能通过估算注入功率的质量来衡量。通过改变电网的输入和负载,可以验证所提出的微电网系统的稳定运行。在MATLAB中实现了连续时间仿真模型,并使用实验原型对其进行了验证。该基准系统为未来的智能电网提供了各种研究范围。将公共耦合点的电压馈送到基于ANN的空间矢量调制三相逆变器,并将转换后的交流电注入电网。总体系统性能通过估算注入功率的质量来衡量。通过改变电网的输入和负载,可以验证所提出的微电网系统的稳定运行。在MATLAB中实现了连续时间仿真模型,并使用实验原型对其进行了验证。该基准系统为未来的智能电网提供了各种研究范围。将公共耦合点的电压馈送到基于ANN的空间矢量调制三相逆变器,并将转换后的交流电注入电网。总体系统性能通过估算注入功率的质量来衡量。通过改变电网的输入和负载,可以验证所提出的微电网系统的稳定运行。在MATLAB中实现了连续时间仿真模型,并使用实验原型对其进行了验证。该基准系统为未来的智能电网提供了各种研究范围。在MATLAB中实现了连续时间仿真模型,并使用实验原型对其进行了验证。该基准系统为未来的智能电网提供了各种研究范围。在MATLAB中实现了连续时间仿真模型,并使用实验原型对其进行了验证。该基准系统为未来的智能电网提供了各种研究范围。

更新日期:2021-02-18
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