TY - JOUR
T1 - Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems
AU - Yameen, Muhammad Zubair
AU - Junejo, Abdul Khalique
AU - Lu, Zhigang
AU - Siddiqui, Rizwan Aziz
AU - El-Sousy, Fayez F.M.
AU - Naveed, Ibtisam
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - The integration of unconventional power sources, such as solar, wind, and electric vehicles (EVs), into electrical power grids poses significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can compromise the reliability and quality of power delivered to end-users. To address these challenges, this paper proposes a novel Proportional-Integral-Derivative (PID) controller optimized using a hybrid Grasshopper Optimization Algorithm-Particle Swarm Optimization (GOA-PSO) approach. Unlike conventional tuning methods, the proposed GOA-PSO hybridization leverages the exploratory strengths of GOA and the exploitative capabilities of PSO, resulting in an optimized control strategy that significantly enhances load frequency control (LFC) performance. This study is among the first to integrate a fuzzy-based MPPT PV system, a P&O MPPT-controlled PMSG-based wind energy system, and EVs within a single-area multi-source energy network while simultaneously addressing a dual-area interconnected power system (IPS). The GOA-PSO-PID controller is fine-tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control efficiency. The controller’s effectiveness is evaluated across two distinct cases: (1) a single-area system integrating thermal, solar, wind, and EV resources, and (2) a two-area thermal tie-line interconnected power system. Comparative studies across various operational scenarios, including extensive parameter variations (± 40%) and load fluctuations, demonstrate the superior performance of the GOA-PSO-PID controller over the conventional PSO-PID approach. The GOA-PSO-PID achieves a 79.95% reduction in overshoot, a 92.78% reduction in undershoot, and a 98.91% improvement in settling time in the single-area system. Similarly, in the dual-area IPS, it provides a 76.73% reduction in overshoot, an 87.62% reduction in undershoot, and a 75.68% improvement in rise time. These findings highlight the robustness and adaptability of the GOA-PSO-PID controller in handling highly fluctuating renewable-dominated power networks, making it a reliable solution for future smart grids.
AB - The integration of unconventional power sources, such as solar, wind, and electric vehicles (EVs), into electrical power grids poses significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can compromise the reliability and quality of power delivered to end-users. To address these challenges, this paper proposes a novel Proportional-Integral-Derivative (PID) controller optimized using a hybrid Grasshopper Optimization Algorithm-Particle Swarm Optimization (GOA-PSO) approach. Unlike conventional tuning methods, the proposed GOA-PSO hybridization leverages the exploratory strengths of GOA and the exploitative capabilities of PSO, resulting in an optimized control strategy that significantly enhances load frequency control (LFC) performance. This study is among the first to integrate a fuzzy-based MPPT PV system, a P&O MPPT-controlled PMSG-based wind energy system, and EVs within a single-area multi-source energy network while simultaneously addressing a dual-area interconnected power system (IPS). The GOA-PSO-PID controller is fine-tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control efficiency. The controller’s effectiveness is evaluated across two distinct cases: (1) a single-area system integrating thermal, solar, wind, and EV resources, and (2) a two-area thermal tie-line interconnected power system. Comparative studies across various operational scenarios, including extensive parameter variations (± 40%) and load fluctuations, demonstrate the superior performance of the GOA-PSO-PID controller over the conventional PSO-PID approach. The GOA-PSO-PID achieves a 79.95% reduction in overshoot, a 92.78% reduction in undershoot, and a 98.91% improvement in settling time in the single-area system. Similarly, in the dual-area IPS, it provides a 76.73% reduction in overshoot, an 87.62% reduction in undershoot, and a 75.68% improvement in rise time. These findings highlight the robustness and adaptability of the GOA-PSO-PID controller in handling highly fluctuating renewable-dominated power networks, making it a reliable solution for future smart grids.
KW - Dual-area power network
KW - Electric vehicle
KW - GOA
KW - ITAE
KW - LFC
KW - PID controller
KW - PSO
UR - http://www.scopus.com/inward/record.url?scp=105005544371&partnerID=8YFLogxK
U2 - 10.1038/s41598-025-01481-6
DO - 10.1038/s41598-025-01481-6
M3 - Article
C2 - 40394105
AN - SCOPUS:105005544371
SN - 2045-2322
VL - 15
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 17549
ER -