Frequency regulation of interconnected hybrid power system with Assimilation of electrical vehicles

被引:4
|
作者
Daraz, Amil [1 ]
Khan, Irfan Ahmed [2 ]
Basit, Abdul [1 ]
Malik, Suheel Abdullah [3 ]
AlQahtani, Salman A. [4 ]
Zhang, Guoqiang [1 ]
机构
[1] NingboTech Univ, Sch Informat Sci & Engn, Ningbo 315100, Peoples R China
[2] Univ Malaya, Fac Engn, Dept Elect Engn, Kuala Lumpur 50603, Malaysia
[3] Int Islamic Univ, Dept Comp & Elect Engn, FET, Islamabad 44000, Pakistan
[4] King Saud Univ, Coll Comp & Informat Sci, Comp Engn Dept, Riyadh, Saudi Arabia
关键词
Renewable energy sources; Load frequency control; White shark optimization; Electrical vehicles; Hybrid power system and fractional order; controller; AUTOMATIC-GENERATION CONTROL; FRACTIONAL ORDER CONTROLLER; AGC;
D O I
10.1016/j.heliyon.2024.e28073
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent widespread connections of renewable energy resource (RESs) in place of fossil fuel supplies and the adoption of electrical vehicles in place of gasoline-powered vehicles have given birth to a number of new concerns. The control architecture of linked power networks now faces an increasingly pressing challenge: tie-line power fluctuations and reducing frequency deviations. Because of their nature and dependence on external circumstances, RESs are analogous to continually fluctuating power generators. Using a fractional order-based frequency regulator, this work presents a new method for improving the frequency regulation in a two-area interconnected power system. In order to deal with the frequency regulation difficulties of the hybrid system integrated with RES, the suggested controller utilizes the modified form of fractional order proportional integral derivative (FOPID) controller known as FOI-PDN controller. The new proposed controllers are designed using the white shark optimizer (WSO), a current powerful bioinspired meta heuristic algorithm which has been motivated by the learning abilities of white sharks when actively hunting in the environment. The suggested FOI-PDN controller's performance was compared to that of various control methodologies such as FOPID, and PID. Furthermore, the WSO findings are compared to those of other techniques such as the salp swarm algorithm, sine cosine algorithm and fitness dependent optimizer. The recommended controller and design approach have been tested and validated at different loading conditions and different circumstances, as well as their robustness against system parameter suspicions. The simulation outcomes demonstrate that the WSO-based tuned FOI-PDN controller successfully reduces peak overshoot by 73.33%, 91.03%, and 77.21% for region-2, region-1, and link power variation respectively, and delivers minimum undershoot of 89.12%, 83.11%, and 78.10% for both regions and tie-line. The obtained findings demonstrate the new proposed controller's stable function and frequency controlling performance with optimal controller parameters and without the requirement for a sophisticated design process.
引用
收藏
页数:21
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