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基于弹性数学启发的电距离分析法优化模糊自适应指数控制器用于电动汽车集成微电网的负荷频率控制改进

Resilient math inspired EDA optimized fuzzy adaptive exponent controller for LFC improvement of an EV integrated microgrid.

作者信息

Sahu Prakash Chandra, Sahoo Buddhadeva, Swain Sarat Chandra, Tejani Ghanshyam G, Bassir David

机构信息

School of Electrical & Computer Science, Indian Institute of Technology, Bhubaneswar, 752050, India.

Department of Electrical & Electronics Engineering, SR University, Warangal, 506371, Telangana, India.

出版信息

Sci Rep. 2025 Aug 5;15(1):28635. doi: 10.1038/s41598-025-12275-1.

Abstract

This study aims to stabilize the frequency of an electric vehicle-integrated AC microgrid in different electrical uncertainties. The recommended microgrid is built by incorporating different distributed generation (DG) oriented power plants. The DG system includes a wind power plant, solar PV plant, diesel generator, fuel cell and geothermal plant. The microgrid frequency goes on oscillating under the action of few uncertainties like dynamics in applied load, fluctuation in wind power and variability in solar power intensity. Further, the charging of electric vehicles extremely disturbs the grid frequency and causes frequency instability issues in the microgrid. This proposed study has anticipated a Fuzzy adaptive exponent PID (Fuzzy PI-D) controller to obtain stability in microgrid frequency under different disturbances. Further, the microgrid is associated with different energy-storing devices for improving overall power quality of the system. The Fuzzy PI-D parameters are selected in optimum by incorporating an advanced Math inspired-Exponential distribution algorithm (Mi-EDA) in different operations. The potential of the optimal Fuzzy PI-D controller is compared with fractional ordered fuzzy PID (FO-FPID), Fuzzy PID and PID controllers in concern to the microgrid's frequency stabilization. The research findings conclude that, the anticipated Fuzzy PI-D approach promptly advances the settling time of frequency by 72.72% and 136.32% and 345.46% to that of FO-FPID, Fuzzy PID and PID controllers respectively. The optimal property of the recommended Mi-EDA technique is compared with the typical sine cosine algorithm (SCA), GA and PSO techniques for validating the potential of the technique.

摘要

本研究旨在稳定不同电气不确定性情况下电动汽车集成交流微电网的频率。所推荐的微电网通过并入不同的面向分布式发电(DG)的发电厂构建而成。DG系统包括风力发电厂、太阳能光伏电站、柴油发电机、燃料电池和地热发电厂。在诸如施加负载的动态特性、风力发电波动以及太阳能强度变化等一些不确定性因素的作用下,微电网频率会持续振荡。此外,电动汽车的充电会极大地干扰电网频率,并在微电网中引发频率不稳定问题。本拟议研究预期采用一种模糊自适应指数PID(Fuzzy PI-D)控制器,以在不同干扰下实现微电网频率的稳定。此外,微电网与不同的能量存储装置相关联,以提高系统的整体电能质量。通过在不同运行中纳入一种先进的受数学启发的指数分布算法(Mi-EDA)来优化选择Fuzzy PI-D参数。将最优Fuzzy PI-D控制器的潜力与分数阶模糊PID(FO-FPID)、模糊PID和PID控制器在微电网频率稳定方面进行比较。研究结果表明,预期的Fuzzy PI-D方法分别将频率的稳定时间相对于FO-FPID控制器、模糊PID控制器和PID控制器迅速缩短了72.72%、136.32%和345.46%。将所推荐的Mi-EDA技术的最优性能与典型的正弦余弦算法(SCA)、遗传算法(GA)和粒子群优化算法(PSO)技术进行比较,以验证该技术的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6239/12325654/ffa6b45fac4b/41598_2025_12275_Fig1_HTML.jpg

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