基于自适应 bonobo 优化的混合储能光伏系统的增强型控制策略和能源管理

Ahmed G. Khairalla, Hossam Kotb, K. Aboras, Muhammad Ragab, Hesham B. ElRefaie, Y. Ghadi, Amr Yousef
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摘要

为了提高严重依赖可再生能源(RES)的电网的可靠性,需要能够对能量波动做出快速反应并存储多余能量的大型储能系统(ESS)。混合系统结合了电池和超级电容器等不同的储能技术,正变得越来越流行,因为没有一种单一技术能满足所有要求。在本研究中,超级电容器用于稳定快速变化的突发电力,而电池则用于稳定逐渐波动的电力流。本文提出了一种用于管理直流(DC)总线电压的稳健控制器,以优化 ESS 的性能。所提出的控制器结合了分数阶比例积分(FOPI)和经典 PI 控制器,这在直流微电网领域尚属首次。与其他传统控制器相比,混合(FOPI-PI)控制器在所有瞬态和动态响应指标上都表现出色,性能优越。建议控制器的参数与自适应 bonobo 优化器(SaBO)相结合,以确定最佳值。此外,还对模型采用了各种优化技术,通过最小化最佳目标函数,SaBO 的输出优于其他技术。此外,目前的研究还采用了一种新颖的电源管理策略,其中包括电池和超级电容器的两个闭合电流回路。通过使用这种方法,可以延长电池的使用寿命,同时保持最佳的系统性能。建议的控制器在 MATLAB/Simulink 2022b 中实现,并报告了几个案例研究的结果。研究结果表明,该控制技术显著改善了瞬态响应,如瞬态持续时间、过冲/过冲和稳定时间。带有 SaBO 优化器的拟议控制器(FOPI-PI)能在负载和太阳能系统变化的情况下有效维持直流母线电压。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced control strategy and energy management for a photovoltaic system with hybrid energy storage based on self-adaptive bonobo optimization
Large-scale energy storage systems (ESSs) that can react quickly to energy fluctuations and store excess energy are required to increase the reliability of electricity grids that rely heavily on renewable energy sources (RESs). Hybrid systems, which combine different energy storage technologies such as batteries and supercapacitors, are becoming increasingly popular because no single technology can satisfy all requirements. In this study, a supercapacitor is used to stabilize quickly shifting bursts of power, while a battery is used to stabilize gradually fluctuating power flow. This paper proposes a robust controller for managing the direct current (DC) bus voltage to optimize the performance of ESS. The proposed controller combines a fractional-order proportional integral (FOPI) with a classical PI controller for the first time in the DC microgrid area. The hybrid (FOPI-PI) controller achieves an outstanding and superior performance in all transient and dynamic response specifications compared to other traditional controllers. The parameters of the suggested controller are incorporated with the self-adaptive bonobo optimizer (SaBO) to determine the optimal values. Furthermore, various optimization techniques are applied to the model and the SaBO’s output outperforms other techniques by minimizing the best objective function. In addition, the current study has utilized a novel power management strategy that includes two closed current loops for both batteries and supercapacitors. By using this method, batteries’ lifespans may be increased while still retaining optimal system performance. The suggested controller is implemented in MATLAB/Simulink 2022b, and the outcomes are reported for several case studies. The findings demonstrate that the control technique remarkably improves the transient response, such as transient duration, overshoot/undershoot, and the settling time. The proposed controller (FOPI-PI) with the SaBO optimizer is effective in maintaining the DC bus voltage under load and solar system variation.
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