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This paper proposes novel multi-energy inertia support for simultaneous frequency and voltage control of an isolated hybrid power system (IHPS). Multi-energy storage (gas inertia – hydrogen storage, thermal inertia – solar thermal storage, hydro inertia – gravity hydro storage, chemical inertia – battery energy storage) supported by demand side management (DSM) for simultaneous voltage and frequency regulation and backed by biodiesel generators, are the essential elements of IHPS. A novel control strategy of concurrent virtual droop control, virtual damping control, virtual inertia control, and virtual negative inertia control is proposed to utilise multiple inertia sources and to improve LFC and AVR performance effectively. The effective coordination of inertia sources in eradicating oscillations in IHPS, is aided by a developed cascaded proportional integral-tilt-integral-sliding mode (PI-TISMC) controller. The performance of PI-TISMC is compared with PID, PI-PID, and PI-SMC controllers. A maiden attempt has been done by training five diverse classes of optimization techniques to optimize the parameters of controllers in the present work. The results are evaluated in MATLAB and it is evident from the results that the performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). The performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). Similarly, the performance of voltage control is improved by 6.7%, 4.8% and 2.3 s (over shoot, undershoot, and settling time) by employing developed PI-TISMC controller and proposed concurrent inertia control. The combination exhibits superior performance in minimizing oscillations in IHPS due to variations in loading and solar insolation. [ABSTRACT FROM AUTHOR]

In a deregulated power system, managing congestion is crucial for effective operation and control. The goal of congestion management is to alleviate transmission line congestion while adhering to system constraints at minimal cost. This research proposes a hybrid Harris Hawk Optimization–Sine Cosine Algorithm (hHHO-SCA) for an efficient generation rescheduling approach to achieve the lowest possible congestion cost. The hybridization has been performed by introducing the features of SCA in the HHO to boost the exploration and exploitation steps of HHO, providing an efficient global solution and effectively optimizing rescheduled power output. The effectiveness of this methodology is evaluated using IEEE 30 and IEEE 118-bus test systems, taking into account system parameters. The potency of the proposed method is analyzed by comparing the results of the hHHO-SCA with those from other recent optimization techniques. The findings show that the hHHO-SCA outperforms other methods by avoiding local optima and demonstrating promising convergence characteristics. [ABSTRACT FROM AUTHOR]

The increasing number of electric Vehicles (EVs) and their influence on the power grid present difficulties that this article addresses by suggesting optimal planning methods for EV charging and discharging. EV charging and discharging operations are effectively managed by creating both locally and globally optimal planning schemes. Future transportation could be changed by the widespread adoption of dynamic wireless power transfer systems in conjunction with EVs, as they would enable speedier travel and continuous EV battery recharging. Dynamic wireless power transfer is a practical answer to problems with electric vehicles. The electrification of automobiles will have a significant influence on the power infrastructure due to the increase in demand for electricity. In this study, we provide an optimal planning method worldwide and a locally optimal strategy for EV charging and discharging. To minimize the total cost of all EVs that charge and discharge during the day, we propose an optimization problem for global planning in which the charging powers are optimized. The simulation results demonstrate that the proposed planning schemes can effectively reduce the total electricity cost for EV owners while also minimizing the impact on the power grid. The globally optimal planning scheme achieves the lowest electricity cost, while the locally optimal scheme provides a good balance between cost reduction and computational complexity. [ABSTRACT FROM AUTHOR]

Hybrid renewable energy systems (HRES) integrating solar, wind, and storage technologies offer enhanced efficiency and reliability for grid-connected applications. However, existing control methods often struggle with maintaining DC voltage stability and minimizing power fluctuations, particularly under variable load conditions. This paper addresses this research gap by proposing a novel control strategy utilizing a PD (1+PI) regulator that combines proportional–integral (PI) and proportional–derivative (PD) controllers. Integrated into the HRES with maximum power point tracking (MPPT), the system includes solar panels, a storage unit, and a wind system featuring a permanent magnet synchronous generator (PMSG). The PD (1+PI) regulator plays a critical role in stabilizing DC voltages within the storage system and collaborates with predictive direct power control (P-DPC) to improve current quality by mitigating fluctuations in active and reactive power. Comparative analysis against traditional direct power control methods shows that the proposed strategy reduces voltage fluctuation by 30% and improves energy utilization efficiency by 25%, validating its efficacy in managing energy from diverse sources to meet nonlinear load demands. The results demonstrate that integrating the PD (1+PI) regulator with MPPT and P-DPC approaches enhances power stability and optimizes energy utilization in grid-connected HRES, underscoring the effectiveness of this advanced control system. [ABSTRACT FROM AUTHOR]

This paper addresses the critical challenge of optimizing the maximum power point (MPP) tracking of photovoltaic (PV) modules under varying load and environmental conditions. A novel fuzzy logic controller design has been proposed to enhance the precision and adaptability of MPP monitoring and adjustment. The research objective is to improve the efficiency and responsiveness of PV systems by leveraging voltage and power as input parameters to generate an optimized duty cycle for a buck-boost converter. This system is tested through both simulation and experimental validation, comparing its performance against the conventional perturb and observe (P&O) method. Our methodology includes rigorous testing under diverse conditions, such as temperature fluctuations, irradiance variations, and sudden load changes. The fuzzy logic technique is implemented to adjust the reference voltage every 100 µs, ensuring continuous optimization of the PV module's operation. The results revealed that the proposed fuzzy logic controller achieves a tracking efficiency of approximately 99.43%, compared to 97.83% for the conventional P&O method, demonstrating its superior performance. For experimental validation, a 150 W prototype converter controlled by a dSPACE DS1104 integrated solution was used. Real-world testing involved both a resistive static load and a dynamic load represented by a DC shunt motor. The experimental results confirmed the robustness and reliability of the fuzzy logic controller in maintaining optimal MPP operation, significantly outperforming traditional methods. In brief, this research introduces and validates an innovative fuzzy logic control strategy for MPP tracking, contributing to the advancement of PV system efficiency. The findings highlight the effectiveness of the proposed approach in consistently optimizing PV module performance across various testing scenarios. [ABSTRACT FROM AUTHOR]

For grid‐connected solar photovoltaic (PV) applications, a hybrid cascaded MLI (H‐CMLI) topology based on cascaded H‐bridge MLI is proposed in this study. The proposed configuration is a hybrid of two common MLIs: Cascaded H‐bridge and three‐phase cascaded voltage source inverter (VSI). For the same voltage level, the proposed topology enhances the number of the generated voltage levels while employing fewer components, relative to other traditional MLI topologies. Furthermore, the voltage stresses on switches in the proposed topology are decreased, compared to when each part operates independently. The proposed topology could be utilized for many applications, such as PV‐grid connection, active power filters, and STATCOM. To verify the effectiveness of the proposed topology, the model is developed in MATLAB/Simulink environment, in which a closed‐loop control scheme based on the traditional one is used to achieve the PV‐grid connection. Alongside the simulation results, the proposed topology and its control scheme are experimentally implemented in the laboratory. Two cases were experimentally applied to validate the successful performance of the proposed H‐CMLI: Open‐loop control and closed‐loop control for PV‐grid integration. The proposed control scheme effectively maintains the DC link voltage at its reference voltages. Also, the closed‐loop control scheme is capable of providing the power factor at unity and maintaining the total harmonic distortion (THD) of grid current within the acceptable limit. To demonstrate the proposed topology's functionality and viability, experimental results are provided. [ABSTRACT FROM AUTHOR]