Optimal design of passive power filters using the MRFO algorithm and a practical harmonic analysis approach including uncertainties in distribution networks

The design of Passive Power Filters (PPFs) has been widely acknowledged as an optimization problem. This paper addresses the PPF parameters design problem using the novel Manta Ray Foraging Optimization (MRFO) algorithm. Moreover, an analytical method based on Monte Carlo Simulation (MCS) is proposed to investigate the harmonic performance of such an optimally designed PPF with variations in power networks. The MRFO algorithm has shown a superior solution-finding ability, but a relatively higher computational effort in comparison with other recently proposed algorithms. The harmonic performance of the optimal PPF solution with uncertainties was analyzed using the proposed method. The results imply that the optimally designed PPF can effectively attenuate the high-order harmonics and improved the system performance parameters over different operating conditions to continually comply with the standard limits. The proposed MCS method showed that the optimally designed PPF reduced the voltage and current distortions by roughly 54% and 30%, respectively, and improved the network hosting capacity by 10% for the worst-case scenario

Modelling and control development of a cascaded NPC-based MVDC converter for harmonic analysis studies in power distribution networks

Today’s power distribution networks are predicted to incorporate more Power Electronics (PE)-based power conversion systems, widely acknowledged as harmonic sources. Concerns about power harmonic severity in the distribution networks can arise, especially with the growing numbers of Medium Voltage Direct Current (MVDC) systems, which are also facilitated by such power converters. Yet, an accurate harmonic model of the MVDC converter is required to investigate its harmonic emissions, propagations, effects, and solutions in today’s distribution networks. This article is devoted to the development of a detailed model of a cascaded Neutral Point-Clamped (NPC)-based MVDC converter for accurate harmonic analysis studies. An appropriate control system with a simple Proportional Integral (PI) controller tuned using the loop-shaping technique is developed. An interleaved Sinusoidal Pulse-Width Modulation (SPWM) scheme aiming to improve the harmonic performance of such an application is introduced. The detailed model of the MVDC system was developed using the Simulink/MATLAB simulation environment, for which the concept of operation was validated, control system performance was investigated, and the effectiveness of the harmonic reduction method was analysed. The key finding is that the interleaved SPWM technique has significantly reduced the Total Harmonic Distortion (THD) to 2% with no significant even-order harmonic components in comparison to the reported models

A pattern reconfigurable antenna using eight-dipole configuration for energy harvesting applications

A pattern reconfigurable antenna, composed of eight elements, is proposed for energy harvesting applications. Pattern reconfigurable antennas are a promising technique for harvesting from different wireless sources. The radiation pattern of the proposed antenna can be steered electronically using an RF switch matrix, covering an angle range from 0 to 360 degrees with a step size of 45 degrees. The proposed antenna primarily consists of an eight-dipole configuration that shares the same excitation. Each dipole is excited using a balun comprising a quarter-wavelength grounded stub and a quarter-wavelength open-circuit stub. The proposed antenna operates in the frequency range of 4.17 to 4.5 GHz, with an impedance bandwidth of 7.6%. By switching between the different switches, the antenna can be steered with a narrower rotational angle. In addition, the antenna can work in an omnidirectional mode when all switches are in the ON state simultaneously. The results demonstrate a good agreement between the numerical and experimental findings for the reflection coefficient and radiation characteristics of the proposed reconfigurable antenna

Tracking analysis of maximum Versoria criterion based adaptive filter

Recently, maximum Versoria criterion-based adaptive algorithms have been introduced as a new solution for robust adaptive filtering. This paper studies the steady-state tracking analysis of an adaptive filter with maximum Versoria criterion (MVC) in a non-stationary (Markov time-varying) system. Our analysis relies on the energy conservation method. Both Gaussian and general non-Gaussian noise are considered, and for both cases, the closed-form expression for steady-state excess mean square error (EMSE) is derived. Regardless of noise type, unlike the stationary environment, the EMSE curves are not increasing functions of step-size parameter. The validity of the theoretical results is justified via simulation

Enhancing grid-forming converters control in hybrid AC/DC microgrids using bidirectional virtual inertia support

This paper presents a new grid-forming strategy for hybrid AC/DC microgrids using bidirectional virtual inertia support designed to address weak grid conditions. The stability of hybrid AC/DC microgrids heavily relies on the AC mains frequency and the DC-link voltage, and deviations in these factors can lead to undesirable outcomes such as load curtailments and power system congestions and blackouts. This paper introduces a unique approach that leverages bidirectional virtual inertia support to enhance the stability and reliability of hybrid AC/DC microgrids under weak grid conditions. The proposed strategy employs virtual inertia as a buffer to mitigate rapid changes in DC-link voltage and AC frequency, thereby enhancing system stability margins. This strategy significantly contributes to a more stable and reliable grid operation by reducing voltage and frequency fluctuations. A standard hybrid AC/DC microgrid configuration is used to implement the bidirectional virtual inertia support, where a bidirectional interlinking converter control is adjusted to deliver inertia support to both the AC and DC subgrids. This converter utilizes the DC grid voltage and AC grid frequency as inputs, effectively managing active power balance and implementing auxiliary functions. Extensive simulations are conducted under weak grid conditions and standalone mode to validate the effectiveness of the proposed strategy. The simulation results demonstrate a remarkable improvement in frequency nadir, rate-of-change-of-frequency (RoCoF), and DC bus voltage deviation in the hybrid AC/DC microgrids. The bidirectional virtual inertia support substantially reduces voltage and frequency fluctuations, enhancing the microgrid stability and resilience. There is an improvement of over 45% and 25% in the frequency deviation and voltage deviation, respectively, achieved through implementing the proposed control strategy

Decentralized smart energy management in hybrid microgrids: Evaluating operational modes, resources optimization, and environmental impacts

Escalating energy demands and climate change challenges necessitate the adaptation of renewable-based microgrid systems in the energy sector. The proposed work employs a robust Multi Agent System (MAS) technique to achieve efficient and automated control of the hybrid microgrid operation. The hybrid microgrid system incorporates Renewable Energy Sources (RES), a diesel generator, and a battery storage system. The operation of the hybrid microgrid consists of three distinct modes: islanded, transition to grid, and grid-oriented mode. The system’s performance is optimized by considering factors like climatic patterns, energy costs, connected source characteristics, and load demand. Different climatic scenarios are assessed for each mode of operation, where the best, extreme sunny, extreme cloudy, and worst climate conditions are considered for islanded mode; sunny and cloudy scenarios are considered for transition to grid mode as well as grid-feed and grid-tied modes are considered for grid-oriented operation of the microgrid. The simulation studies are performed using the MATLAB/Simulink R2021a environment. Furthermore, Particle Swarm Optimization (PSO) is implemented to optimize power allocation within the microgrid and enhance its cost-effectiveness. The optimization results demonstrate efficient utilization of available energy sources along with effective energy management facilitated by the MAS control system. The results emphasize the importance of adopting a MAS approach for achieving smart energy management through comprehensive analysis and integrating decentralized energy management techniques for optimal accommodation of distributed energy resources in hybrid microgrids

A review of constraints and adjustable parameters in microgrids for cost and carbon dioxide emission reduction

In a world grappling with escalating energy demand and pressing environmental concerns, microgrids have risen as a promising solution to bolster energy efficiency, alleviate costs, and mitigate carbon emissions. This article delves into the dynamic realm of microgrids, emphasizing their indispensable role in addressing today's energy needs while navigating the hazards of pollution. Microgrid operations are intricately shaped by a web of constraints, categorized into two essential domains: those inherent to the microgrid itself and those dictated by the external environment. These constraints, stemming from component limitations, environmental factors, and grid connections, exert substantial influence over the microgrid's operational capabilities. Of particular significance is the three-tiered control framework, encompassing primary, secondary, and energy management controls. This framework guarantees the microgrid's optimal function, regulating power quality, frequency, and voltage within predefined parameters. Central to these operations is the energy management control, the third tier, which warrants in-depth exploration. This facet unveils the art of fine-tuning parameters within the microgrid's components, seamlessly connecting them with their surroundings to streamline energy flow and safeguard uninterrupted operation. In essence, this article scrutinizes the intricate interplay between microgrid constraints and energy management parameters, illuminating how the nuanced adjustment of these parameters is instrumental in achieving the dual objectives of cost reduction and Carbon Dioxide emission minimization, thereby shaping a more sustainable and eco-conscious energy landscape. This study investigates microgrid dynamics, focusing on the nuanced interplay between constraints and energy management for cost reduction and Carbon Dioxide minimization. We employ a three-tiered control framework—primary, secondary, and energy management controls—to regulate microgrid function, exploring fine-tuned parameter adjustments for optimal performance

Enhancing the control of doubly fed induction generators using artificial neural networks in the presence of real wind profiles

This study tackles the complex task of integrating wind energy systems into the electric grid, facing challenges such as power oscillations and unreliable energy generation due to fluctuating wind speeds. Focused on wind energy conversion systems, particularly those utilizing double-fed induction generators (DFIGs), the research introduces a novel approach to enhance Direct Power Control (DPC) effectiveness. Traditional DPC, while simple, encounters issues like torque ripples and reduced power quality due to a hysteresis controller. In response, the study proposes an innovative DPC method for DFIGs using artificial neural networks (ANNs). Experimental verification shows ANNs effectively addressing issues with the hysteresis controller and switching table. Additionally, the study addresses wind speed variability by employing an artificial neural network to directly control reactive and active power of DFIG, aiming to minimize challenges with varying wind speeds. Results highlight the effectiveness and reliability of the developed intelligent strategy, outperforming traditional methods by reducing current harmonics and improving dynamic response. This research contributes valuable insights into enhancing the performance and reliability of renewable energy systems, advancing solutions for wind energy integration complexities

A distributed architecture of parallel buck-boost converters and cascaded control of DC microgrids-real time implementation

To enhance the stability and reliability of the system, the converters’ parallel operation can be cascaded to address the constraints posed by the substantial integration of renewable resources. Buck-boost DC-DC converters are often controlled via a cascaded control approach to allow parallel operation. The converter’s output current and its voltage will be controlled by nested loop control. This study proposes adaptive droop control parameters that are updated and verified online using the principal current sharing loops to minimize the fluctuation in load current sharing. When the converters in the microgrid are paralleled, load sharing will be accomplished using the droop control approach in addition to nested proportional-integral-based voltage and current control loops. To restore the correct voltage across the DC microgrid, an outer addition voltage secondary loop will be used, rectifying any voltage disparities caused by the droop management strategy. Several common load resistances and input voltage variations are used to test the suggested method. Using a linearized model, this work assesses the stability and performance of the proposed method. It then confirms the findings with an adequate model created in MATLAB/SIMULINK, Real-Time Simulation Fundamentals, and hardware-based experiments

Quad element MIMO antenna for C, X, Ku, and Ka-band applications

This article presents a quad-element MIMO antenna designed for multiband operation. The prototype of the design is fabricated and utilizes a vector network analyzer (VNA-AV3672D) to measure the S-parameters. The proposed antenna is capable of operating across three broad frequency bands: 3–15.5 GHz, encompassing the C band (4–8 GHz), X band (8–12.4 GHz), and a significant portion of the Ku band (12.4–15.5 GHz). Additionally, it covers two mm-wave bands, specifically 26.4–34.3 GHz and 36.1–48.9 GHz, which corresponds to 86% of the Ka-band (27–40 GHz). To enhance its performance, the design incorporates a partial ground plane and a top patch featuring a dual-sided reverse 3-stage stair and a straight stick symmetrically placed at the bottom. The introduction of a defected ground structure (DGS) on the ground plane serves to provide a wideband response. The DGS on the ground plane plays a crucial role in improving the electromagnetic interaction between the grounding surface and the top patch, contributing to the wideband characteristics of the antenna. The dimensions of the proposed MIMO antenna are 31.7 mm × 31.7 mm × 1.6 mm. Furthermore, the article delves into the assessment of various performance metrics related to antenna diversity, such as ECC, DG, TARC, MEG, CCL, and channel capacity, with corresponding values of 0.11, 8.87 dB, −6.6 dB, ±3 dB, 0.32 bits/sec/Hz, and 18.44 bits/sec/Hz, respectively. Additionally, the equivalent circuit analysis of the MIMO system is explored in the article. It’s worth noting that the measured results exhibit a strong level of agreement with the simulated results, indicating the reliability of the proposed design. The MIMO antenna’s ability to exhibit multiband response, good diversity performance, and consistent channel capacity across various frequency bands renders it highly suitable for integration into multi-band wireless devices. The developed MIMO system should be applicable on n77/n78/n79 5G NR (3.3–5 GHz); WLAN (4.9–5.725 GHz); Wi-Fi (5.15–5.85 GHz); LTE5537.5 (5.15–5.925 GHz); WiMAX (5.25–5.85 GHz); WLAN (5.725–5.875 GHz); long-distance radio telecommunication (4–8 GHz; C-band); satellite, radar, space communications and terrestrial broadband (8–12 GHz; X-band); and various satellite communications (27–40 GHz; Ka-band)