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This paper proposes a novel hybrid control strategy integrating a Finite Control Set Model Predictive Controller (FCS-MPC) with a universal droop controller (UDC) for effective load power sharing in inverter-fed microgrids. Traditional droop-based methods, though widely adopted for their simplicity and decentralized nature, suffer from limitations such as steady-state inaccuracies and poor transient response, particularly under mismatched impedance conditions. To overcome these drawbacks, the proposed scheme incorporates detailed modeling of inverter and source dynamics within the predictive controller to enhance accuracy, stability, and response speed. The UDC complements the predictive framework by ensuring coordination among inverters with different impedance characteristics. Simulation results under various load disturbances demonstrate that the proposed approach significantly outperforms conventional PI-based droop control in terms of voltage and frequency regulation, transient stability, and balanced power sharing. The performance is further validated through real-time simulations, affirming the scheme’s potential for practical deployment in dynamic microgrid environments.

Partial shading conditions lead to power mismatches among photovoltaic (PV) panels, resulting in the generation of multiple peak power points on the P-V curve. At this point, conventional MPPT algorithms fail to operate effectively. This research work mainly focuses on the exploration of performance optimization and harnessing more power during the partial shading environment of solar PV systems with a single-objective non-linear optimization problem subjected to different operations formulated and solved using recent metaheuristic algorithms such as Cat Swarm Optimization (CSO), Grey Wolf Optimization (GWO) and the proposed Chimp Optimization algorithm (ChOA). This research work is implemented on a test system with the help of MATLAB/SIMULINK, and the obtained results are discussed. From the overall results, the metaheuristic methods used by the trackers based on their analysis showed convergence towards the global Maximum Power Point (MPP). Additionally, the proposed ChOA technique shows improved performance over other existing algorithms.

In this paper, an automatic voltage regulator (AVR) embedded with fractional order PID (FOPID) is employed for the alternator terminal voltage control. A novel meta-heuristic technique, a modified version of grey wolf optimizer (mGWO) is proposed to design and optimize the FOPID AVR system. The parameters of FOPID, namely, proportional gain ( Κ Ρ), the integral gain ( Κ I), the derivative gain ( Κ D), λ and μ have been optimally tuned with the proposed mGWO technique using a novel fitness function. The initial values of the Κ Ρ, Κ I , and Κ D of the FOPID controller are obtained using Ziegler-Nichols (ZN) method, whereas the initial values of λ and μ have been chosen as arbitrary values. The proposed algorithm offers more benefits such as easy implementation, fast convergence characteristics, and excellent computational ability for the optimization of functions with more than three variables. Additionally, the hasty tuning of FOPID controller parameters gives a high-quality result, and the proposed controller also improves the robustness of the system during uncertainties in the parameters. The quality of the simulated result of the proposed controller has been validatedby other state-of-the-art techniques in the literature.

Metaheuristic optimization algorithms (MOAs) are widely used to optimize the design process of engineering problems [...]

Molecular crystals are not known to be as stiff as metals, composites and ceramics. Here we report an exceptional mechanical stiffness and high hardness in a known elastically bendable organic cocrystal [caffeine (CAF), 4-chloro-3-nitrobenzoic acid (CNB) and methanol (1:1:1)] which is comparable to certain low-density metals. Spatially resolved atomic level studies reveal that the mechanically interlocked weak hydrogen bond networks which are separated by dispersive interactions give rise to these mechanical properties. Upon bending, the crystals significantly conserve the overall energy by efficient redistribution of stress while perturbations in hydrogen bonds are compensated by strengthened π-stacking. Furthermore we report a remarkable stiffening and hardening in the elastically bent crystal. Hence, mechanically interlocked architectures provide an unexplored route to reach new mechanical limits and adaptability in organic crystals. This proof of concept inspires the design of light-weight, stiff crystalline organics with potential to rival certain inorganics, which currently seem inconceivable.

Numerous reviews are available in the literature on PV inverter topologies. These reviews have intensively investigated the available PV inverter topologies from their modulation techniques, control strategies, cost, and performance aspects. However, their compliance with industrial standards has not been investigated in detail so far in the literature. There are various standards such as North American standards (UL1741, IEEE1547, and CSA 22.2) and Australian and European safety standards and grid codes, which include IEC 62109 and VDE. These standards provide detailed guidelines and expectations to be fulfilled by a PV inverter topology. Adherence to these standards is essential and crucial for the successful operation of PV inverters, be it a standalone or grid-tied mode of operation. This paper investigates different PV inverter topologies from the aspect of their adherence to different standards. Both standalone and grid-tied mode of operation-linked conditions have been checked for different topologies. This investigation will help power engineers in selecting suitable PV inverter topology for their specific applications.

The hybridization of a recently suggested Harris hawk’s optimizer (HHO) with the traditional particle swarm optimization (PSO) has been proposed in this paper. The velocity function update in each iteration of the PSO technique has been adopted to avoid being trapped into local search space with HHO. The performance of the proposed Integrated HHO-PSO (IHHOPSO) is evaluated using 23 benchmark functions and compared with the novel algorithms and hybrid versions of the neighbouring standard algorithms. Statistical analysis with the proposed algorithm is presented, and the effectiveness is shown in the comparison of grey wolf optimization (GWO), Harris hawks optimizer (HHO), barnacles matting optimization (BMO) and hybrid GWO-PSO algorithms. The comparison in convergence characters with the considered set of optimization methods also presented along with the boxplot. The proposed algorithm is further validated via an emerging engineering case study of controller parameter tuning of power system stability enhancement problem. The considered case study tunes the parameters of STATCOM and power system stabilizers (PSS) connected in a sample power network with the proposed IHHOPSO algorithm. A multi-objective function has been considered and different operating conditions has been investigated in this papers which recommends proposed algorithm in an effective damping of power network oscillations.

Heating, ventilation and air-conditioning (HVAC) systems constitute the majority of the demands in modern power systems for aggregated buildings. However, HVAC integrated with renewable energy sources (RES) face notable issues, such as uneven demand–supply balance, frequency oscillation and significant drop in system inertia owing to sudden disturbances in nearby generation for a longer period. To overcome these challenges, load frequency control (LFC) is implemented to regulate the frequency, maintain zero steady-state error between the generation and demand, reduce frequency deviations and balance the active power flow with neighboring control areas at a specified value. In view of this, the present paper investigates LFC with a proposed centralized single control strategy for a micro-grid (µG) system consisting of RESs and critical load of a HVAC system. The proposed control strategy includes a newly developed cascaded two-degree-of-freedom (2-DOF) proportional integral (PI) and proportional derivative filter (PDF) controller optimized with a very recent meta-heuristic algorithm—a modified crow search algorithm (mCSA)—after experimenting with the number of performance indices (PICs). The superiority of both the proposed optimization algorithm and the proposed controller is arrived at after comparison with similar other algorithms and similar controllers, respectively. Compared to conventional control schemes, the proposed scheme significantly reduces the frequency deviations, improving by 27.22% from the initial value and reducing the performance index criteria (ƞISE) control error to 0.000057. Furthermore, the demand response (DR) is implemented by an energy storage device (ESD), which validates the suitability of the proposed control strategy for the µG system and helps overcome the challenges associated with variable RESs inputs and load demand. Additionally, the improved robustness of the proposed controller for this application is demonstrated through sensitivity analysis with ±20% μG coefficient variation.

An electrical power system is a vast interlocked network that needs a vigilant design to sustain the system with an uninterrupted power flow operation without any restrictions, called optimal power flow (OPF). OPF problem requires robust and fast optimization techniques to volve it due to its complexity. Cuckoo Search (CS) is one method that is being applied in OPF problems, and it has many advantages, e.g., ease use and littler tuning parameters. But it is not good enough, falling into local optimal resolutions and slow converges. Therefore, recently developed Grey Wolf Optimization (GWO) algorithm is used to solve OPF, but it has low accuracy and inadequate local searching ability. To overcome these problems, this paper proposed to combine CS with GWO to create a novel the Hybrid algorithm, called here HCSGWO. The main objective is to deduce the emission, true power generation cost, true power losses, and voltage stability, being a multi-objective problem. THCSGWO are validated by solving the OPF problem considering the calssic IEEE57 bus system. The results are compared with GWO and other algorithms employed in the literature.