Shunt Capacitor Research Articles

Enhancing Smart Microgrid Resilience Under Natural Disaster Conditions: Virtual Power Plant Allocation Using the Jellyfish Search Algorithm

Electric power networks face critical challenges from extreme weather events and natural disasters, disrupting socioeconomic activities and jeopardizing energy security. This study presents an innovative approach incorporating virtual power plants (VPPs) within networked microgrids (MGs) to address these challenges. VPPs integrate diverse distributed energy resources such as solar- and wind-based generation, diesel generators, shunt capacitors, battery energy storage systems, and electric vehicles (EVs). These resources enhance MG autonomy during grid disruptions, ensuring uninterrupted power supply to critical services. EVs function as mobile energy storage units during emergencies, while shunt capacitors stabilize the system. Excess energy from distributed generation is stored in battery systems for future use. The seamless integration of VPPs and networked technologies enables MGs to operate independently under extreme weather conditions. Prosumers, acting as both energy producers and consumers, actively strengthen system resilience and efficiency. Energy management and VPP allocation are optimized using the jellyfish search optimization algorithm, enhancing resource scheduling during outages. This study evaluates the proposed approach’s resilience, reliability, stability, and emission reduction capabilities using real-world scenarios, including the IEEE 34-bus and Indian 52-bus radial distribution systems. Various weather conditions are analyzed, and a multi-objective function is employed to optimize system performance during disasters. The results demonstrate that networked microgrids with VPPs significantly enhance distribution grid resilience, offering a promising solution to mitigate the impacts of extreme weather events on energy infrastructure.

Putting piezoelectric sensors into Fano resonances

AbstractPiezoelectric resonance sensors are essential to many diverse applications associated with chemical and biological sensing. In general, they rely on continuously detecting the resonant frequency shift of piezoelectric resonators due to analytes accreting on their surfaces in vacuum, gas or fluid. Resolving the small analyte changes requires the resonators with a high quality factor. Here, we propose theoretically and demonstrate experimentally a scheme using a physics concept, i.e., a Fano resonance, to enhance the quality factor rather than optimizing the structure and material of the resonator itself though these are important. The Fano resonance arises due to the interference between a discrete mode and a continuum of modes, leading to the asymmetric and steep dispersion. In our scheme, the as-fabricated piezoelectric sensors are put into the Fano resonance by connecting an external shunt capacitor to them. As a verification case, one-port surface acoustic wave (SAW) resonators on LiNbO3 substrate, incorporating a composite of polymethyl methacrylate (PMMA) and graphene oxide (GO) for humidity sensing, have been fabricated and characterized. We enhance the quality factor by up to a factor of about 8, from 929 for the as-fabricated sensor to 7682 for that with the external shunt capacitor. Our results pave the way for the practical development of piezoelectric resonance sensors with high quality factor.

A Low-Profile Reconfigurable Wide Band BPF with RF-MEMS Switches for 5G/ Satellite Applications

A low-profile wide-band tunable semi-circular cavity BPF is designed and analyzed in this work. RF-MEMS switches were utilized on either side of the 50 Ω microstrip transmission lines to provide reconfigurability. BPF tunability is achieved when the two switches travel from upstate to downstate in an electrostatically activated shunt capacitive shunt type RF-MEMS switch. The switch has a capacitance ratio of 10 and operates at a transition time of 30 μS with an actuation voltage of 6.5 V to move it downward. This is suitable for 5G wireless communication applications (n77, n78, and n79) as well as C-band applications. Return loss of -22 dB is obtained at 3.7 GHz when the switch is in the ON state, while reflection co-efficient of -32 dB is obtained at 6.7 GHz when the switch is in the OFF state. When both switches are ON or OFF, a bandpass filter provides a 3GHz frequency shift. The frequency range where BPF is intended to operate, which is adjustable for various purposes, is 1–10 GHz. The characteristics of the switch were investigated by simulating its design in COMSOL Multiphysics and the outcomes were contrasted with theoretical computations. The adjustable properties of the BPF have been observed and shown using the HFSS v 13 tool.

Reliability Variation Assessment Due to Alteration in Subsystems of a Series-Parallel System under Weibull Failure Laws

Here, we consider a (m, ni) order system having 'm' number of subsystems connected in series and each subsystem has 'n' number of components in parallel. The reliability of the system has been obtained by deleting 'y' number of subsystems (or adding 'x' number of subsystems) from (or to) it. The variation in reliability due to alteration in subsystems has been assessed for a particular system of (4,3) order. A regression approach is used to quantify the strength of variation in reliability due to alteration in subsystems. The coefficient of determination (R2) and adjusted R2 are also obtained to examine the goodness of fit. The variation in reliability has been shown numerically and graphically for particular value of the parameters. The application of the present study can be visualized in an Internally Fused Shunt Capacitor Bank System (electrical system).. KEYWORDS :Reliability variations, Series-Parallel system, Internally fused shunt capacitor bank, Regression Analysis.

Multi-port network based modeling and selection of capacitor for desired voltage regulation of a standalone six-phase short-shunt induction generator for application in remote areas

This paper gives a straightforward method to determine the values of excitation capacitors of a standalone short-shunt six-phase induction generator (SPIG) to maintain the voltage profile within predetermined percentage of voltage deviation (VD). In this envisioned study, the value of the capacitor is meticulously chosen to optimize the number of capacitor switching, ensuring minimal system cost and complexity. The theory of multi-port network analysis has been applied for modelling of the SPIG, thus, the complex mathematical derivation to obtain the model equations is avoided. The system is expressed as a multivariable nonlinear optimization problem. The resultant admittance of the SPIG is calculated from its per phase equivalent circuit and is used as an objective function, which is solved using Binary Search Algorithm (BSA). The main novelty of this work is the determination of the model equations of the SPIG system in an efficient and simple way using the multi-port network analysis approach. Along with this, the BSA is employed for optimal selection of excitation capacitors because of its simplicity and less computational time. The results, on a 3.7 kW induction machine, reveal that to maintain a 4 % VD, a fixed series capacitor of 140 µF and two switched shunt capacitors (34.4 µF, 91.8 µF) are required. For 2 % VD, four shunt capacitors (24.2µF, 36.2µF, 64.7µF, 91.2µF) are necessary. The performance of the machine is evaluated with the help of magnetic characteristics and other equations obtained from its per phase equivalent circuit. The experimentation has been carried out in a hardware prototype system developed in the laboratory. The experimental and the simulated results are compared and found that both are nearly same for different operating conditions, which indicates the efficacy of the proposed approach.

Multi-Objective Optimization for Distributed Generator and Shunt Capacitor Placement Considering Voltage-Dependent Nonlinear Load Models

This paper aims to optimize the placement and sizing of distributed generator (DG) and shunt capacitor (SC) to minimize various single and multi-objective problems. Initially, three single objectives are addressed: minimizing active power loss, minimizing total operating cost, and minimizing total voltage deviation. A new mathematical expression for total operating cost, based on installation, maintenance, and operation costs of DG and SC, is developed. The Competitive Swarm Optimizer (CSO) algorithm is utilized to solve the optimization problem. The results obtained using CSO are compared with several other algorithms, including Cuckoo Search, Jaya, Teaching Learning Based Optimization, Particle Swarm Optimization, and Genetic Algorithm. The comparative results demonstrate that the CSO algorithm outperforms these methodologies. Subsequently, three multi-objective problems are formulated: simultaneous minimization of active power loss and total voltage deviation, simultaneous minimization of active power loss and total operating cost, simultaneous minimization of active power loss, total voltage deviation, and total operating cost. Multi-objective CSO is used to obtain a set of non-dominated optimal solutions, providing more realistic results. The R-method is then applied to select the best compromise solution from these non-dominated solutions. The developed model demonstrates its ability to find optimal placements of DG and SC, offering superior results compared to existing approaches. The proposed methodology is validated on six different non-linear loads such as constant power, constant current, constant impedance, industrial, commercial, and residential loads, highlighting its effectiveness and tested on the IEEE-34 bus radial distribution system.

Optimal distributed generation and shunt capacitor bank placement in microgrid distribution planning for enhanced performance

Optimal distributed generation and shunt capacitor bank placement in microgrid distribution planning for enhanced performance

Multi-Objective Optimization Algorithm Based Bidirectional Long Short Term Memory Network Model for Optimum Sizing of Distributed Generators and Shunt Capacitors for Distribution Systems

In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution systems at any desired load factor. The stochastic traits of evolutionary computing methods necessitate running the algorithm repeatedly to confirm the global optimum. In order to save utility engineers time and effort, this study introduces a BiLSTM network-based machine learning model to directly estimate the optimal values of DGs and SHCs, rather than relying on load flow estimates. At first, a multi-objective grey wolf optimizer determines the most suitable locations and capacities of DGs and SHCs at the unity load factor and the same locations are used to obtain optimum sizing of DGs and SHCs at other load factors also. The base case data sets consisting of substation apparent power, real power load, reactive power load, real power loss, reactive power loss and minimum node voltage at various load factors in per unit values are taken as input training data for the machine learning model. The optimal sizes of the DGs and SHCs for the corresponding load factors obtained using GWO algorithm are taken as target data sets in per unit values for the machine learning model. An adaptive moment estimation (adam) optimization approach is employed to train the BiLSTM ML model for identifying the ideal values of distributed generations and shunt capacitors at different load factors. The efficacy of the proposed ML-based sizing algorithm is demonstrated via simulation studies.

Optimizing grid-dependent and islanded network operations through synergic active-reactive power integration

DG integration improves distribution network performance and also enables microgrid (MG) formation for islanded operation. However, existing studies assume an isolated operation approach for islanded mode, which is unrealistic and increases overall system costs while adding complexity to the grid. This paper presents a dual-stage methodology for the efficient operation of distributed generation (DG) and shunt capacitor banks (SCBs) in radial distribution networks (RDNs) for both grid-integrated and islanded modes. The first stage proposes an improved Jaya algorithm (IJaya) to optimize DG and SCB allocation during grid-connected operation, aiming to reduce power loss and improve voltage profiles. IJaya employs a dynamic weight-based grid search to address premature convergence. The second stage formulates a multiobjective function for the islanded operation to minimize power loss and underutilization of DG-SCB capacity. Case studies on IEEE 33- and 69-bus RDNs show IJaya reduces power loss by 38.84 % and improves voltage by 3.26 % in grid-connected networks compared to existing methods. The proposed analytical approach for islanded operation tunes the source power factor, reducing DG-SCB underutilization by up to 15.83 % for power factors between 0.8 and 0.93. The results demonstrate that operating distributed resources near optimal capacities meets a larger portion of the island network's energy needs.

Design of 2.45 GHz rectenna based on high-gain 2-element array antenna and 7-stage voltage-doubler rectifier for energy harvesting applications

Abstract This paper proposes a new design of a 2.45 GHz compact rectenna for ambient RF energy harvesting, presenting a complete energy harvesting system. The proposed rectenna design features a two-element antenna array with high gain and a novel voltage-doubler configuration. The two-element antenna array is fabricated on Rogers RT/Duroid-5880 substrate, utilizing a rectangular microstrip patch antenna fed by a symmetric 50 Ω coplanar line. The antenna’s performance is tested numerically and experimentally in terms of return loss (S11) and radiation patterns. The results show excellent matching bandwidth at 2.45 GHz with a high gain of 7.03 dBi, providing a reasonable agreement between measurement and simulation results. The rectenna design employs a 7-stage voltage doubler rectifier that generates a dynamic DC voltage and improves the circuit’s reliability and performance. The receiving antenna and the rectifier are connected via a single L-section, comprising a shunt capacitor and a series inductor, for impedance matching, resulting in size reduction. The rectifier exhibits a peak simulated power conversion efficiency (PCE) of 75% and a measured efficiency of 60% at an input power of 20 dBm. The rectenna yields a high output DC voltage of 4.9 V at an input power of 13 dBm with a resistive load of 1 kΩ. These results reveal that the proposed 2.45 GHz rectenna is a suitable candidate for RF energy harvesting applications in low-power sensors and electronic devices.

Dynamic control of elastic wave transmission by a digital metalayer

Piezoelectric materials with shunt circuits have aroused much research interest due to flexible parameter adjustment. However, shunted piezoelectric elements are difficult to respond to the dynamic changes in the whole system due to the absence of autonomous control ability, which constrains their practical applications. Here, we propose a digital metalayer to control the wave energy transmission across different materials in real time. This digital metalayer comprises a stack of multiple piezoelectric lead zirconate titanate (PZT) disks connected with shunt capacitance circuits (SCCs). The external digital control system adjusts the effective acoustic impedance of the PZT disks through digital potentiometers and microprogrammed control unit, thereby enabling digital manipulation of wave transmission. Utilization of optimized SCCs further enhances adjustment accuracy, supporting both negative and positive capacitance values. The experiments demonstrate that this digital metalayer exhibits remarkable performance in controlling wave transmission. Moreover, the distinct variations in transmitted amplitudes, precisely controlled by the digital metalayer, are harnessed as binary signals for information transmission. An image of letters is encoded into a series of amplitude-modulated waves by the digital metalayer and clearly transmitted. The proposed digital metalayer shows great promise for applications in intelligent impedance matching and the real-time modulation systems.

Factorized form of the dispersion relations of a traveling wave tube

The traveling tube (TWT) design in a nutshell comprises of a pencil-like electron beam (e-beam) in vacuum interacting with guiding it slow-wave structure (SWS). In our prior studies the e-beam was represented by one-dimensional electron flow and SWS was represented by a transmission line (TL). We extend in this paper our previously constructed field theory for TWTs as well the celebrated Pierce theory by replacing there the standard TL with its generalization allowing for the low frequency cutoff. Both the standard TL and generalized transmission line (GTL) feature uniformly distributed shunt capacitance and serial inductance, but the GTL in addition to that has uniformly distributed serial capacitance. We remind the reader that the standard TL represents a waveguide operating at the so-called TEM mode with no low frequency cutoff. In contrast, the GTL represents a waveguide operating at the so-called TM mode featuring the low frequency cutoff. We develop all the details of the extended TWT field theory and using a particular choice of the TWT parameters we derive a physically appealing factorized form of the TWT dispersion relations. This form has two factors that represent exactly the dispersion functions of non-interacting GTL and the e-beam. We also find that the factorized dispersion relations comes with a number of interesting features including: (i) focus points that belong to each dispersion curve as TWT principle parameter varies; (ii) formation of “hybrid” branches of the TWT dispersion curves parts of which can be traced to non-interacting GTL and the e-beam.

Estimation of abnormal states in shunt capacitor banks using transient disturbance feature extraction

Shunt capacitor banks are essential for reactive power compensation, ensuring voltage stability, and reducing system losses. These banks consist of multiple units with components in series and parallel. A few component failures do not immediately affect the safe operation of the capacitor bank, but component breakdown can lead to voltage redistribution. Under combined factors such as system overvoltage and equipment aging, and others can trigger an avalanche effect causing capacitor breakdown, resulting in significant safety accident risks. Practical operation experience shows that partial component breakdown generates many transient disturbance signals. Quantitative analysis of these signals can detect capacitor bank anomalies early. This paper proposes the quantitative extraction of transient disturbance characteristics using the Prony algorithm and estimates the phase and number of capacitors that break down to judge capacitor anomalies. The simulation part verifies the theoretical analysis and detection algorithm’s correctness through numerical simulations and PSCAD (Power Systems Computer Aided Design) electromagnetic transient simulations. The numerical simulations consider different signal lengths, noise levels, attenuation coefficients, and oscillation frequencies. In the PSCAD simulation environment, verification models are built under varying sampling frequencies, numbers of breakdown components, signal lengths, and signal-to-noise ratios. These simulation results verify the accuracy of the detection algorithm under different conditions.

High Quality Factor Miniaturized CMOS Transmission Lines Using Cascaded T-Networks for 60 GHz Millimeter Wave Applications

This work presents an on-chip 60 GHz lumped element transmission line (TL) using cascaded T-networks with a high Quality factor. Each T-network consists of a series inductance with a shunt capacitance at its center. We have derived the design equations for this TL configuration and proved that a TL whose electrical length ≥ 60° achieves additional miniaturization when implemented with three or more cascaded T-networks. The inductance is implemented using a straight wire model with no ground below it, while the capacitance is implemented using a parallel plate model with a grounding pedestal. Both configurations guarantee maximum inductance per unit length and capacitance per unit area to further improve the miniaturization level. A quarter wavelength TL with three cascaded T-networks is fabricated as proof of concept. The measured and simulated results of the fabricated TL have good agreement, and the measured quality factor is 17 at 60 GHz.

Analysis of seismic damage mechanism of capacitor

Abstract A high voltage shunt capacitor bank is very important for the normal operation of the power system, especially for the UHVDC transmission in long distance large capacity transmission, and power system networking has an important role. Therefore, its performance response under earthquakes is one of the key concerns. Through the fine finite element simulation modeling of the actual capacitor, the sine beat wave, and the actual earthquake input, the dynamic characteristics and the response index under the earthquake are studied. The results show that the stiffness in the x direction of the capacitor assembly is greater than that in the y direction. The weak position of the model is the root and top of the end insulator and the middle insulator. Under the action of different working conditions, such as X - and Y-El Centro waves, the maximum stress response of the root of the end insulator of the capacitor device is 4.98 MPa, and the safety factor is 3.51, which meets the requirement greater than 1.67.

The League Championship Algorithm (LCA) for optimal placement and sizing of shunt capacitors

The League Championship Algorithm (LCA) for optimal placement and sizing of shunt capacitors

Selection of sectionalising switch to address any switching failure in a droop controlled islanded microgrid

This paper presents a heuristic approach to address the restoration of droop-controlled islanded microgrids (DCIMGs) in the event of a sectionalising switch (SS) failure. The proposed approach consists of two-step procedures to ensure the smooth operation of the network. First, a faulty SS is isolated by replacing it with a tie switch (TS) that acts as an SS. Then, the switching configuration is adjusted to improve the performance of DCIMGs. To assess the efficacy of the proposed approach, the 33-bus and 118-bus DCIMG test networks are considered. For fulfilling the load demand in each DCIMG, droop-controlled DGs (DDGs) and renewable DGs (RDGs) are employed. Along with satisfying load demand, DGs decrease the power loss and voltage drop. Additionally, shunt capacitor banks (SCBs) are also incorporated into the DCIMG to improve the voltage profile. In conjunction with the load flow analysis, the power injection of the DDGs are determined using the modified Newton–Raphson method. For determining the power injection of RDGs and the size of SCBs, particle swarm optimisation method is implemented. The paper investigates the effectiveness of the proposed method for resolving SS faults in DCIMGs over a 24 hour period amidst hourly demand and renewable power generation variation. By employing Hong’s 2m+1 point estimate method, the uncertainties associated with load demands and renewable power generation are also considered. The effectiveness of the issue formulation is verified using MatLabR2023b. With the proposed method, the voltage and frequency can be effectively maintained after the network is restored following a fault.

Analyzing the consequences of power factor degradation in grid-connected solar photovoltaic systems

This study examines the impact of integrating solar photovoltaic (PV) systems on power factor (PF) within low-voltage radial distribution networks, using empirical data from the Energy Self-Sufficiency for Health Facilities in Ghana (EnerSHelF) project sites in Ghana. The research included simulations focusing on optimal PV integration, with and without PF considerations, and the strategic placement of PV and shunt capacitors (SC). Three scenarios evaluated PV injection at high-load demand nodes, achieving penetration levels of 85.00 percent, 82.88 percent with high voltage drop, and 100.00 percent with high loss nodes. Additionally, three scenarios assessed SC allocation methods: proportional to the node's reactive power demand (Scenario I), even distribution (Scenario II), and proportional to installed PV capacity at PV nodes (Scenario III).The analysis used a twin-objective index (TOI), combining voltage deviations and power factor degradation. Results showed significant PV curtailment was necessary to achieve standard PF. Optimal penetration levels, considering TOI, reduced PV penetration from 85.00 percent to 63.75 percent, 82.88 percent to 57.38 percent, and 100.00 percent to 72.50 percent for high load, high voltage drops, and high loss nodes, respectively. Notably, all scenarios showed a concerning PF of 0.00 at dead-end nodes (P20, P21, P22).Scenario I achieved PF ranges of -0.26 to 1.00 with PV at high load, -0.69 to 1.00 with PV at high voltage drop, and 0.95 to 1.00 with PV at high loss nodes. Scenario II produced similar ranges, -0.48 to 1.00, -1.00 to 0.99, and 0.30 to 0.96, with PV placement at high load, voltage drops, and loss nodes, respectively. Scenario III yielded ranges of -0.19 to 0.97 (high load), -0.23 to 1.00 (high voltage drop), and 0.86 to 0.96 (high losses).The study concluded that the most effective strategy involves installing PVs at high-loss nodes and distributing SCs proportionally to the node's reactive power demand (Scenario I). This approach achieved a more uniform PF pattern throughout the network, highlighting the practical implications of strategic PV placement and targeted reactive power compensation for maintaining a healthy and efficient distribution system with solar PV integration.

Using Shunt Capacitors to Mitigate the Effects of Increasing Renewable Energy Penetration

Over the past two decades, Renewable Energy Sources (RESs) have gained global popularity. Control issues are becoming more difficult as the system inertia decreases due to the absence of typical synchronous generators. Innovative methods like fault current limiters, energy storage devices, and alternative control systems are utilized to deal with these difficulties. This study provides a summary of the challenges associated with incorporating high-level RESs into the existing grid. The increased penetration of the RESs has a negative impact on the system oscillations and harmonics, generating the need for power quality improvement techniques, such as adaptive control, adding energy systems, power stream assessment, or weight stream examination. This paper presents a framework of the power stream issue, its arrangement as well as different game plan methods. The power stream model of a power structure can be built using the significant association, weight, and age data.

Power efficiency improvement in reactive power dispatch under load uncertainty

Nowadays, there is a significant rise in electricity demand, posing challenges for power grid operators due to inaccurate forecasting, leading to excessive power losses and voltage instability. This paper addresses these issues by focusing on solving optimal reactive power dispatch (ORPD) while considering load demand uncertainty. The main objective of solving ORPD is to reduce power losses by adjusting generator voltage ratings, transformer tap ratio, and shunt capacitors' reactive power. Monte Carlo simulation (MCS) is employed to generate load scenarios using the normal probability density function, while a reduction-based technique is implemented to decrease the number of those scenarios. The improved gray wolf optimization (I-GWO) algorithm is introduced for the first time to address the stochastic ORPD problem. Experimentation is conducted on an IEEE-30 bus system when results are contrasted with conventional gray wolf optimization (GWO) and five other algorithms as stated in the literature. The I-GWO algorithm's performance is assessed with and without considering load demand uncertainty. Through Friedman's statistical tests, a significant decrease of 20.96% in active power losses and 63.06% in the summation of expected power losses is observed. The I-GWO algorithm's results on the ORPD problem demonstrate its effectiveness and robustness.