A Novel Fractional-Order Active Disturbance Rejection Load Frequency Control Based on An Improved Marine Predator Algorithm

Weichao He, Yuemin Zheng, Jin Tao, Yujuan Zhou, Jiayan Wen () and Qinglin Sun
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Weichao He: School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China
Yuemin Zheng: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Jin Tao: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Yujuan Zhou: School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China
Jiayan Wen: School of Automation, Guangxi University of Science and Technology, Liuzhou 545616, China
Qinglin Sun: College of Artificial Intelligence, Nankai University, Tianjin 300350, China

Sustainability, 2023, vol. 15, issue 13, 1-23

Abstract: Load frequency control (LFC) serves as a crucial component of automatic generation control in renewable energy power systems. Its primary objective is to maintain a balance between the output power of generators and the load demand, thereby ensuring system frequency stability. However, integrating renewable energy sources into power systems brings forth several challenges, such as low power quality and poor system stability due to their uncontrollable nature. To enhance the response speed, stability, and disturbance rejection capabilities of LFC, a novel fractional-order active disturbance rejection controller (NFOADRC) based on an improved marine predator algorithm (IMPA) has been designed in this paper. By leveraging the wide frequency-response range and non-local memory of NFOADRC, a more precise prediction and compensation of rapid oscillations in the system can be achieved. Additionally, the IMPA can be utilized for efficient parameter tuning, enabling a more accurate adjustment of the controller. Subsequently, the combined application of these approaches can be applied to two-area interconnected power systems with a solar thermal power plant (STPP) and a five-area interconnected power system including a wind turbine generator (WTG), photovoltaic (PV) cells, hydro turbine, and gas turbine. The simulation results confirm that the proposed control strategy effectively minimizes the undershoot and overshoot of frequency deviation in the power system. It achieves a faster stabilization of the load frequency, leading to enhanced power quality.

Keywords: automatic generation control; fractional-order disturbance rejection controller; marine predator algorithm; load frequency control; five-area interconnected power system (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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