Maroua Bouziane, Laid Zarour, Benbouhenni Habib, Elbarbary Z M S, Colak Ilhami, Alammar Mohammed M
Department of Electrical Engineering, Laboratory of Electrical Constantine (LEC), Mentouri University of Constantine 1, Constantine, Algeria.
Ecole Nationale Polytechnique d'Oran, Laboratoire LAAS, Bp 1523, EL M'naouer, Algeria.
Sci Rep. 2025 Feb 21;15(1):6318. doi: 10.1038/s41598-025-90239-1.
This paper presents a hybrid approach that combines a genetic algorithm (GA)-optimized type-2 fuzzy logic controller (T2FLC) with a fractional-order technique for enhanced control of a microgrid system. The T2FLC approach is employed to handle the inherent uncertainties in the microgrid due to fluctuating renewable energy inputs and varying loads. The GA optimizes the parameters of the designed FO-T2FLC approach, ensuring optimal performance under different operational conditions. This developed strategy is a modification and development of the traditional approach, as it is characterized by rapid dynamic response, high durability, distinctive performance, ease of application, and inexpensive. Also, this designed strategy does not depend on the mathematical model of the studied system, which gives satisfactory results if the system parameters change. The microgrid system on the direct current side features a photovoltaic array with battery storage. In contrast, the alternating current section comprises a multi-functional voltage source inverter integrated with a shunt active power filter. This setup delivers energy to the connected loads and the network. To manage the system effectively; traditional power control methods (direct power control and space vector modulation) are used for the alternating current section. Additionally, the proposed regulator control the direct current bus voltage loop, regulate the reactive and active power loops of the network, and compensate for the total harmonic distortion in the source streams. It also injects the required active power into the network to enhance the competence of the power network. In this work, the efficiency of the proposed FO-T2FLC-GA approach is verified using MATLAB, comparing it to the T2FLC-GA approach and some existing strategies such as third-order sliding mode control. The results obtained highlight the effectiveness and strength of the FO-T2FLC-GA approach in improving power quality and reducing the total harmonic distortion value, as it reduces the total harmonic distortion value of the current by percentages estimated at 80%, 33.87%, and 32.50% in all cases. The FO-T2FLC-GA approach also reduces the steady-state error, undershoot, fluctuations, and overshoot of direct current link voltage compared to the T2FLC-GA approach by percentages estimated at 1.54%, 33.04%, 25%, and 33.04%, respectively. Compared with other works, the proposed approach improves the response time, overshoot, and ripples of direct current link voltage by 59.38%, 50%, and 75%, respectively, compared to the third-order sliding mode control approach. These results could make the designed FO-T2FLC-GA approach a prominent solution in the future in other industrial applications such as propulsion and traction.
本文提出了一种混合方法,该方法将遗传算法(GA)优化的二阶模糊逻辑控制器(T2FLC)与分数阶技术相结合,以增强对微电网系统的控制。采用T2FLC方法来处理微电网中由于可再生能源输入波动和负载变化而固有的不确定性。GA对所设计的分数阶T2FLC方法的参数进行优化,确保在不同运行条件下具有最佳性能。这种开发的策略是对传统方法的改进和发展,其特点是动态响应快、耐久性高、性能独特、易于应用且成本低廉。此外,这种设计的策略不依赖于所研究系统的数学模型,当系统参数变化时也能给出令人满意的结果。直流侧的微电网系统具有带电池储能的光伏阵列。相比之下,交流部分包括一个集成了并联有源电力滤波器的多功能电压源逆变器。这种设置将能量输送到连接的负载和电网。为了有效管理系统,传统的功率控制方法(直接功率控制和空间矢量调制)用于交流部分。此外,所提出的调节器控制直流母线电压回路,调节电网的无功和有功功率回路,并补偿源流中的总谐波失真。它还向电网注入所需的有功功率,以提高电网的性能。在这项工作中,使用MATLAB验证了所提出的分数阶T2FLC-GA方法的效率,并将其与T2FLC-GA方法以及一些现有策略(如三阶滑模控制)进行了比较。获得的结果突出了分数阶T2FLC-GA方法在改善电能质量和降低总谐波失真值方面的有效性和优势,因为在所有情况下,它将电流的总谐波失真值降低了估计为80%、33.87%和32.50%的百分比。与T2FLC-GA方法相比,分数阶T2FLC-GA方法还分别将直流链路电压的稳态误差、下冲、波动和过冲降低了估计为1.54%、33.04%、25%和33.04%的百分比。与其他工作相比,与三阶滑模控制方法相比,所提出的方法分别将直流链路电压的响应时间、过冲和纹波提高了59.38%、50%和75%。这些结果可能使所设计的分数阶T2FLC-GA方法在未来成为推进和牵引等其他工业应用中的突出解决方案。