Abstract
In the modern world, the surge of renewable energy has become a focal point, drawing global attention due to its ability to merge cost-effectiveness with sustainability. This shift has made renewable energy an inescapable component of our power grids. A fresh approach is being proposed for load frequency control (LFC) in multi-area power systems, integrating diverse energy sources like photovoltaic (PV), electric vehicles, wind turbines, and thermal plants. This study dives deep into the complex domain of control systems by examining the intercommunication between multi-stage controllers, specifically comparing the 2DOF proportional integral and derivative with filter-PI (2 Degrees of Freedom PIDn-PI) models against the classic PI and 2DOF-PIDn controllers. The key differentiator here lies in introducing an enhanced coyote optimization algorithm (ECOA), aimed at determining the optimal parameters for these advanced controllers. A unique facet of this research is its inclusion of uncertainty, addressing variability by allowing the system parameters to fluctuate within a range of ± 40 %. The robustness of the suggested controllers is tested under dynamic load changes, with these variations applied independently across multiple regions. Two distinct test scenarios are employed, each subject to varying disturbances, to gauge the controllers' adaptability. The operational restrictions of the governor dead band (GDB) impact on the reheat thermal governor unit and generation rate constraint (GRC) in the reheat thermal generating units are simulated using the proper dynamic models. This research includes GDB after the governor unit and GRC after re-heat unit and studies the effect of nonlinearity in power system. CTD is added before the controller and because, in a realistic scenario, there is a time delay in communication with the system. So, the proposed controller helps to give the results as close as the real-time scenario. The findings reveal that by incorporating the GRC, GDB and CTD, the oscillations are damp successfully and even rise under uncertainty situations. The stability analysis also performs the proposed technique upon comparison with previously established methods. The simulated results imply that the proposed multi-staged 2DOF PIDn-PI control system, optimized by ECOA, exhibits remarkable efficiency and resilience. For instance, in case of perturbation in the system, the cumulative settling time of the proposed controller is 1.137 sec while compared with GA-PI, PSO-PID, ABC-PIDn, COA-PI, COA-PIDn, MPA-PIDn has settling time of 28.972 sec, 26.42 sec, 24.52 sec, 17.68 sec, 15.125 sec and 14.01 sec respectively. Its ability to manage load frequency control across multi-area power systems sets it apart, offering a sophisticated solution to the complexities of modern energy management.
Original language | English |
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Article number | 101120 |
Journal | Sustainable Computing: Informatics and Systems |
Volume | 46 |
DOIs | |
State | Published - Jun 2025 |
Bibliographical note
Publisher Copyright:© 2025 Elsevier Inc.
Keywords
- Coyote optimization algorithm
- Load frequency control
- Multi-area power system
- Renewable energy sources
ASJC Scopus subject areas
- General Computer Science
- Electrical and Electronic Engineering