2026· Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería· 0 citations
Abstract
Due to increased system uncertainty, nonlinear dynamics, and marketdriven power exchanges, modern deregulated multi-area power systems with high penetration of renewable energy sources (RES) like wind and solar, and electric vehicle (EV) charging stations present serious challenges to automatic generation control (AGC). Degraded frequency regulation and tie-line power control under deregulated environments result from the limited robustness, slow dynamic response, poor handling of stochastic RES/EV variations, and susceptibility to local optimal solutions of both conventional PI/PID controllers and recently reported optimizationbased AGC schemes. However, with a view to addressing these issues, this study focuses on reducing area control errors (ACE) during different operational shifts, such as frequency fluctuation (f) and tie line variations (Ptie). The main objective of this study is to determine the optimal gain settings for the Fractional Order Proportional-Integral-Derivative controller (FOPIDC) using the mother optimization algorithm (MOA). The proposed control strategy looks at how generators 3-AMS behave in a deregulated environment and emphasises the significance of FOPIDC optimization in preserving system stability with the goal of reducing integral time and absolute error (ITAE). Furthermore, the effectiveness of the proposed method is verified by comparing it with the Walrus Optimization Algorithm (WOA). As case studies, the effectiveness of the suggested strategy is also evaluated under Poolco, bilateral agreements, stability, and sensitivity analysis. In terms of generator outputs, tie-line power variations, and frequencies across different locations, comparative data unequivocally demonstrate that the suggested MOA-adjusted FOPIDC performs better than alternative approaches. In case 1, by implementing the MOA optimized controller, the settling time is 8.5 s, and the value of the objective ITAE for the transient responses is 0.0005292. However, these values are less than the values obtained by WOA. Similarly, in case 2, the settling time is 11.5 s, and ITAE is 0.000395 less
The growing penetration of renewable energy sources and electric vehicles (EVs) into modern power systems has introduced significant challenges for Automatic Generation Control (AGC), including nonlinearities, communication delays, and load uncertainties that conventional Proportional-Integral-Derivative (PID) controllers struggle to handle. This paper proposes a hybrid Fuzzy Fractional-Order Proportional-Integral (Fuzzy FOPI) and Tilt-Integral-Derivative (TID) controller for load frequency control (LFC) in a three-area interconnected power system comprising thermal, hydro, gas turbine, wind, solar photovoltaic, and EV resources. Controller parameters are optimally tuned using the Snake Optimization (SO) metaheuristic algorithm, with the Integral Squared Error (ISE) of frequency and tie-line power deviations adopted as the fitness function. A comprehensive mathematical model of the multi-source system is developed, and the proposed SO-tuned Fuzzy FOPI+TID controller is benchmarked against classical PID and Differential-Evolution (DE)-tuned Fuzzy FOPI+TID controllers under step load disturbances, random load variations, variable renewable penetration levels, and tie-line power exchange scenarios. Simulation results demonstrate that the proposed controller achieves the lowest ISE value (1.19 × 10⁻⁴), substantially outperforming the SO-tuned PID (358.5 × 10⁻³) and DE-tuned Fuzzy FOPI+TID (7.9 × 10⁻²) controllers, while also reducing settling time, overshoot, and undershoot across all three areas. The findings confirm that intelligent, optimization-driven, fractional-order control provides superior robustness and resilience for frequency regulation in EV-integrated, renewable-rich, multi-source power systems
Jagan Surwanshi and Prashant Garg· International Journal of Adv...· 0 citations
The growing induction of renewable and cleaner energy sources has made present-day interconnected power grids more complex, where frequency stability and tie-line power control are significant issues. This work presents a realistic two-area interconnected system modelled in MATLAB/Simulink comprising gas, reheat-thermal, and hydro units, with nonlinear consideration and a modified Proportional-Integral-Derivative-Filter (PIDN) controller design. The impact of the inclusion of a Fuel Cell (FC) unit with the grid on frequency stability is analysed, and a coordinated control strategy with Flexible AC Transmission System (FACTS) devices is developed. Several FACTS devices, namely Thyristor Controlled Series Capacitor (TCSC), Unified Power Flow Controller (UPFC), Interline Power Flow Controller (IPFC), and Static Synchronous Series Compensator (SSSC), are designed and integrated with the grid to improve frequency stability. Three population-based optimisation algorithms, viz, Grey Wolf Optimisation (GWO), Artificial Bee Colony (ABC), and Differential Evolution (DE), are used for minimising the cost function, Integral of Time multiplied by Absolute Error (ITAE), for optimal tuning of PIDN and FACTS controllers. A comprehensive study is performed across four scenarios, including single-area and multi-area Step Load Perturbations (SLP). The control performance of each strategy is evaluated based on the obtained ITAE, settling times, peak overshoots, peak undershoots, and rise times. Results demonstrate that GWO outperforms ABC and DE by achieving better control dynamics. Moreover, inclusion of FC achieves a substantial reduction in ITAE compared to conventional approaches, with values as low as 0.002044. FACTS devices further enhance performance, with IPFC consistently achieving the best damping, lowering ITAE to nearly half of the baseline PIDN–GWO values in multi-area disturbances. Overall, the study establishes that coordinated deployment of optimised controllers, FACTS technologies, and cleaner energy sources can significantly strengthen frequency regulation.
Vivek Kaushal Lawyee, Loveleen Kaur Taneja, Ajay Kumar et al.· Strategic Planning for Energ...· 0 citations
The increasing integration of renewable energy sources has significantly reduced greenhouse gas emissions and mitigated global warming. However, maintaining stability and efficient power management in Virtual Power Plants (VPPs) under dynamic operating conditions remains a major challenge. This study proposes a Self-Adaptive Siberian Tiger Optimization (SA-STO) based hybrid Proportional Integral–Fractional Order PID (PI-FOPID) controller for enhancing frequency regulation and power efficiency in VPP systems integrating solar photovoltaic systems, wind turbines, energy storage systems, diesel generators, and electric vehicles. The proposed hybrid controller combines the fast response of PI control with the robustness and flexibility of FOPID control, while the SA-STO algorithm optimally tunes controller parameters to improve system performance. MATLAB/Simulink simulations are conducted to evaluate the proposed approach against conventional PI, PID, and FOPID controllers using performance metrics such as frequency stability, overshoot response, power loss, and Total Harmonic Distortion (THD). The simulation results demonstrate that the proposed SA-STO-based hybrid PI-FOPID controller achieves enhanced dynamic response, improved stability, and reduced harmonic distortion, with a THD of 3.74%, compared with conventional controllers.
Srinivasa Rao.Sureddy, Nageswara Rao Pulivarthi· international journal of eng...· 0 citations
The increasing penetration of renewable energy sources (RESs), electric vehicles (EVs), and rapidly varying load demands has introduced significant challenges in maintaining frequency stability in modern interconnected power systems. Conventional load frequency control (LFC) methods with fixed or inadequately optimized controller parameters often exhibit poor dynamic performance under such uncertain operating conditions. To address these challenges, this paper proposes an Ant Lion Optimizer (ALO)-based Dual-Mode Fractional-Order Proportional Integral (DMFOPI) controller for a three-area interconnected power system incorporating RESs and EV charging stations. For a comprehensive performance evaluation, conventional Proportional-Integral (PI), Dual-Mode PI (DMPI), Fractional-Order PI (FOPI), and the proposed DMFOPI controllers are optimally tuned using the ALO algorithm based on the Integral Square Error (ISE) performance criterion. The proposed controller is validated in the MATLAB/Simulink environment under step load disturbances, EV integration, and ±20% turbine time-constant variations. Simulation results demonstrate that the ALO-DMFOPI controller achieves superior frequency regulation with reduced frequency deviations, improved damping characteristics, shorter settling times, and enhanced disturbance rejection compared with the PI, DMPI, and FOPI controllers. The proposed controller achieves the minimum ISE value of 0.21836 and the lowest performance index (J = 0.1128), indicating its improved control effectiveness. Furthermore, the proposed controller maintains robust and reliable performance under both EV-connected and EV-disconnected operating conditions, as well as under turbine parameter uncertainties. The results confirm that the ALO-DMFOPI controller is an effective and robust solution for load frequency control in modern interconnected power systems with high penetration of renewable energy sources and electric vehicles.
Maintaining frequency stability in islanded microgrids (MGs) has become increasingly challenging due to the growing penetration of renewable energy sources, particularly photovoltaic systems, wind turbine generators (WTGs), and plug-in hybrid electric vehicles (PHEVs). The intermittent nature of renewable generation and continuous load variations introduces significant power imbalances, resulting in frequency deviations and degraded system stability. Although the classical Ziegler–Nichols (ZN) tuning method is attractive because of its simplicity and ease of implementation, it is generally limited to conventional proportional–integral–derivative (PID) controllers and is often inadequate for renewable-dominated MGs. To overcome these limitations, this paper proposes a modified ZN-based tuning strategy for a novel multistage PID (MPID) controller. Unlike the conventional ZN method, the proposed approach extends its applicability to the MPID structure by introducing an additional proportional gain (KPP), enabling the tuning of five controller parameters while preserving low computational complexity and practical implementation. The proposed controller is implemented and validated using a detailed MATLAB/Simulink model of an isolated MG comprising PV systems, WTG, diesel generators, and PHEVs. Its performance is comprehensively evaluated under multi-step load disturbances, renewable power fluctuations, combined disturbances, and different PHEV charging/discharging modes and battery state-of-charge levels. Furthermore, the proposed controller is benchmarked against conventional ZN-PID, ZN-FOPID, and both PID- and MPID-based controllers tuned using Particle Swarm Optimization, Cuckoo Search Algorithm, Moth–Flame Optimization, and Grasshopper Optimization Algorithm. Simulation results demonstrate that the proposed ZN-MPID controller achieves the best overall dynamic performance, with a settling time of 4.109 s, zero overshoot, a maximum frequency undershoot of 1.801 × 10−4 Hz, and the lowest error indices (ISE = 3.073 × 10−6, ITSE = 0.697 × 10−6, and ITAE = 3.40 × 10−4). Compared with the investigated metaheuristic-based PID controllers, the proposed controller reduces the settling time by up to 86.1% and the error indices by up to 95.5%. It also consistently outperforms all investigated MPID tuning methods, confirming the effectiveness of the proposed modified ZN tuning strategy. Overall, the proposed methodology provides an efficient, low-complexity, and practical solution for frequency regulation in renewable-dominated isolated MGs.
B. Alouache, M. Helaimi, H. Benbouhenni et al.· Electronics· 0 citations
Recently, microgrid (MG) structures include a mix of renewable energy sources (RES) and conventional sources. At high levels of RES penetration, reduced inertia and frequency stability have been confirmed in several studies. Properly designed and structured load frequency control (LFC) and virtual inertia control (VIC) are feasible solutions to these problems. In this paper, a new hybridized two-degree-of-freedom (2DOF) non-integer controller is proposed for multi-generation, multi-area MGs’ frequency regulation. The proposed new LFC is based on a 2DOF tilt-integral/tilt-derivative-double-derivative controller with a filter (TI-TD2F2). Meanwhile, the proposed design process considers coordinating capacitive energy storage (CES) to help regulate frequency deviation, as well as the high penetration of RESs (wind and PV). The incorporation of CES participation in frequency regulation helps provide fast VIC for the studied multi-MG system. Furthermore, an Enhanced Escape Algorithm (EESC) optimization algorithm is proposed to simultaneously optimize the control parameter set of the two-area MG system. The proposed EESC optimization algorithm identifies appropriate parameters for controller design, yielding better overall dynamic performance. An enhanced Escape Algorithm (EESC) is based on boosting the searching mechanism of the conventional Escape Algorithm by the integration of three modifications, including the Chaos map logistic mutation mechanism, the Fitness distance balance mechanism, and the Sorted Quasi-oppositional based learning (SQOBL). The proposed 2DOF TI-TD2F2 controller demonstrates improved frequency stability and sustainable operation under load changes, variation in RESs, and other uncertainties of system parameters. The obtained results showed that the proposed EESC optimization algorithm adjusts the parameters of the TI-TD2F2 controller, which significantly improves the dynamic performance in load frequency and tie-line power control. Compared to traditional TID and FOPID controllers, TI-TD2F2 achieves up to a 70–80% reduction in tie-line power deviation and up to 60% faster settling time in many scenarios, demonstrating better robustness, faster response, and better overall system stability.
Essam. H. Abdou, Mohamed Ebeed, Aisha F. Fareed et al.· Energies· 0 citations