Distribution Static Compensator Research Articles

Optimal planning of electric vehicle charging stations and distributed generators with network reconfiguration in smart distribution networks considering uncertainties

This paper proposes an optimal planning technique for placing the multiple renewable energy (RE) based distributed generators (DGs), Distribution Static Compensators (DSTATCOMs), and electric vehicle charging stations (EVCSs) in the radial distribution network (RDN) considering the related uncertainties. This approach gives optimal placement and sizes for DGs and DSTATCOMs as well as a number of electric vehicles (EVs) that can be charged at the EVCSs by considering the network reconfiguration (NR). The optimal allocation of EVCSs fulfills the power demand from EVs at various locations and minimizes the negative impact on the power network. The RE-based DGs considered for this work are solar photovoltaic (PV) and wind. The uncertainties related to RE-based DGs and EVCSs have been modeled by using the probabilistic-based two-point estimate method (2PEM). The best locations and sizes are identified by optimizing the individual objectives that is active power losses and voltage stability index (VSI) using the teaching learning based optimization (TLBO) algorithm. Then both objectives are optimized by using the non-dominated sorting-based TLBO algorithm. Furthermore, the optimal planning approach is implemented on IEEE 33 and 69 bus test systems to demonstrate the suitability, practicality, and efficiency of the proposed optimal planning strategy. The obtained results reveal that the proposed technique is beneficial for determining the optimal locations for DGs, DSTATCOMs, and EVCSs without affecting the grid stability. The proposed planning approach can search better network structure with reduced power losses and voltage deviation, enhanced voltage profile, and improved voltage stability.

Stochastic‐gradient‐based control algorithms for power quality enhancement in solar photovoltaic interfaced three‐phase distribution system

AbstractHere, stochastic‐gradient‐based adaptive control algorithms have been discussed and employed for power quality enhancement in a Photovoltaics (PV) integrated distribution system. Least mean square (LMS), least mean fourth (LMF), sign‐error LMS, and ‐normalised LMS (‐NLMS) have been implemented as control algorithms for the estimation of fundamental load current. The performances of these adaptive algorithms are compared under steady‐state and dynamic conditions under the non‐linear load conditions in a closed‐loop three‐phase system. The main aim of implementing these algorithms is reactive power compensation, power quality enhancement, and load balancing in a single‐stage three‐phase grid‐tied PV system. The hysteresis current control (HCC) technique is used to generate switching pulses for the three‐phase Distribution Static Power Compensator (DSTATCOM). An MPPT is also employed to ensure maximum power delivery from the solar PV array. PV integrated three‐phase single‐stage distribution system with adaptive control algorithms is implemented in MATLAB/Simulink environment as well as in experimental environment to achieve the goals per standard IEEE‐519.

Integration of Photovoltaic and DSTATCOM In the Distribution Network Using Rat Swarm Optimization Technique

Power loss minimization and improved voltage profile have been major challenges faced by the electrical distribution network (DN) mainly because of the long length of the feeders and the high resistance to reactance (R/X) ratio of the DN. A lot of techniques have been investigated to solve these problems. One of the most prominent is the optimal integration of distributed generation (DG) such as photovoltaic (PV) as well as the integration of Distribution Static Synchronous Compensator (DSTATCOM) into the network. The main challenge with this solution has been the determination of the optimal sizes and sites of the DG and/or DSTATCOM. This paper seeks to optimize the simultaneous allocation of multiple DSTATCOMs and PVs in the DN for power loss reduction and voltage profile improvement using the rat swarm optimization (RSO) technique, which is a simple, yet robust optimization technique. The optimization problem is formulated to minimize power loss, voltage deviation index, and maximize the voltage stability index. The IEEE 33 node DN is used as a test network and the simulation results show the effectiveness of the RSO technique in finding the best sizes and locations of the PVs and the DSTATCOMs. The power losses of the network are reduced from 210.996 kW, and 143.129 kVAr when there is no DSTATCOM nor PVs in the network to 26.155 kW, and 19.128 kVAr when DSTATCOM and PVs are simultaneously allocated into the network. A remarkable improvement in the voltage profile of the network is also observed with the minimum node voltage being 0.98 p.u. compared to 0.9038 p.u. when there are no DSTATCOMs or PVs. The RSO results were compared with other techniques from the literature, and it proved its superiority.

Dynamic Optimization and Placement of Renewable Generators and Compensators to Mitigate Electric Vehicle Charging Station Impacts Using the Spotted Hyena Optimization Algorithm

The growing adoption of electric vehicles (EVs) offers notable benefits, including reduced maintenance costs, improved performance, and environmental sustainability. However, integrating EVs into radial distribution systems (RDSs) poses challenges related to power losses and voltage stability. The model accounts for hourly variations in demand, making it crucial to determine the optimal placement of electric vehicle charging stations (EVCSs) throughout the day. This study proposes a new approach that combines EVCSs, distribution static compensators (DSTATCOMs), and renewable distributed generation (RDG) from solar and wind sources, with a focus on dynamic analysis over 24 h. The spotted hyena optimization algorithm (SHOA) is employed to determine near-global optimum locations and sizes for RDG, DSTATCOMs, and EVCSs, aiming to minimize real power loss while meeting system constraints. The SHOA outperforms traditional methods due to its unique search mechanism, which effectively balances exploration and exploitation, allowing it to find superior solutions in complex environments. Simulations on an IEEE 34-bus RDS under dynamic load conditions validate the approach, demonstrating a reduction in average power loss from 180.43 kW to 72.04 kW, a 72.6% decrease. Compared to traditional methods under constant load conditions, the SHOA achieves a 77.0% reduction in power loss, while the BESA and PSO achieve reductions of 61.1% and 44.7%, respectively. These results underscore the effectiveness of the SHOA in enhancing system performance and significantly reducing real power loss.

A hybrid optimization for distributed generation and D-STATCOM placement in radial distribution network: a multi-faceted evaluation

The deregulation of the power system, upward growth in electrical energy demand and network expansion have resulted in an increasing integration of distributed generation (DG) and distribution static synchronous compensator (D-STATCOM) into radial distribution systems (RDS). Nonetheless, the optimal allocation of these devices is highly important to derive immense benefits. This investigation narrows down on optimizing DG and D-STATCOM placement in IEEE 33-bus RDS with a view to increase bus voltages, decrease power losses as well as maximize economic gains. The study undertakes a comprehensive analysis comparing the technical, economic and environmental performance of DG and D-STATCOM; thereby enabling power engineers to make informed choices concerning which device will be most advantageous when it comes to delivering power in RDS. A fuzzy enhanced firefly optimization (FEFO) approach is proposed for the optimization and a multifaceted evaluation in terms of technical, financial and environmental is presented for effective decision-making on distributed energy resource deployment. D-STATCOM and wind DG integrations led to notable reductions in power loss and pollutant emissions, highlighting their effectiveness in improving power quality and reducing reliance on fossil fuels. While wind DG incurred a higher installation cost ($3,100,749.2) compared to D-STATCOM ($90,566.6), it achieved greater yearly power loss cost savings ($69,198 versus $47,619). FEFO’s efficiency in optimization stands out, aiding engineers in making informed decisions for optimizing D-STATCOM and wind-DG integration in the IEEE-33 RDS, ultimately enhancing system performance and cost-effectiveness through proactive planning. The integration of D-STATCOM and wind DG led to a significant improvement in distribution system efficiency, with D-STATCOM reducing real power loss by 28.7% and reactive power loss by 27.8%, while wind DG achieved greater reductions of 41.8% in real power loss and 37.5% in reactive power loss, alongside reductions in pollutant emissions of 1.5% and 2.2%, respectively.

Continuous–Discrete Student Psychology-Based Optimization Algorithm for Optimal Planning of Distributed Generators and Distribution Static Compensators in Power Distribution Network

Continuous–Discrete Student Psychology-Based Optimization Algorithm for Optimal Planning of Distributed Generators and Distribution Static Compensators in Power Distribution Network

Optimal planning of photovoltaic and distribution static compensators in medium-voltage networks via the GNDO approach

This research employs the generalized normal distribution optimizer (GNDO) to address the simultaneous integration of solar photovoltaic (PV) sources and distribution static compensators (D-STATCOMs) in medium-voltage distribution networks. Through a discrete-continuous codification process, the GNDO method determines the optimal locations (nodes) and capacities (sizes) of PV systems and D-STATCOMs. A power flow approach based on the successive approximations method is used to solve the power flow equations and assess the solution's technical characteristics, including voltage profiles and power injections. Using a master-slave optimization strategy, the GNDO and the power flow method are used to address the studied problem. Numerical results in the 33- and 69-bus grids demonstrate the effectiveness of the proposed approach, showing superior performance compared to the vortex search algorithm (VSA) and the sine-cosine algorithm (SCA). The results indicate reductions of approximately 35.5554% and 35.6839% when using the GNDO in both test feeders. Additionally, the GNDO reduces the computational efforts required to find solutions in both test feeders, in comparison with the VSA and the SCA. All numerical validations were performed using MATLAB 2024a.

Dynamic operation of distribution grids with the integration of photovoltaic systems and distribution static compensators considering network reconfiguration

The optimal operation of Distribution Networks (DNs) using network reconfiguration has become more critical in the modern power system due to the widespread use of Renewable Energy Sources (RESs) and the imbalance between load demand and energy provided by RESs. However, attaining the most efficient functioning while integrating RESs is a challenging endeavor due to the unpredictability of the electrical system and the complexities associated with network reconfiguration. Integrating Distribution Static Compensators (D-STATCOMs) with network reconfiguration is powerful for improving voltage deviation reducing overall costs, and minimizing active power losses, while successfully accommodating the fluctuating characteristics of renewable energy sources. To tackle these difficulties, we offer the Horned Lizard Optimization Algorithm (HLOA), a new approach for optimizing the operation of DNs. The efficacy of HLOA is showcased on the IEEE 33-bus DN, to minimize costs, voltage deviations, real power losses, and emissions in the presence of unpredictable factors like photovoltaic (PV) uncertainties, price changes, and load demand. The analysis encompasses three case studies: one focused on optimizing operation solely with PV integration, another using both PV and D-STATCOM integration, and a third incorporating PV, D-STATCOMs, and network reconfiguration. The results indicate that the combination of PV, D-STATCOMs, and network reconfiguration significantly decreases overall cost by 45.6 %, real power losses are reduced by 66.3 %, and voltage variations are improved by 71.04 %. Emissions are mitigated by 36.72 % compared to the base case.

Control of D-Statcom in Appropriation Framework Involving ANFIS for Further Developing Power Quality

This paper introduces an intelligent controller designed for the optimal operation of a D-STATCOM (Distribution Static Compensator) utilizing the ANFIS. In primary focus is improve the power quality within a 3 phase, four wire system. And distribution of fortifying and overall consistency. Then the ANFIS controller in-corporates fuzzy logic’s, devices are applied in “adaptive network framework”. To use the ANFIS method are established and using the MATLAB Simulink software. D-STATCOM, featuring a VSI and a DC side capacitance, excels in reactive power compensation and harmonic mitigation, even when subjected to dynamic load conditions and advice of the DC link capacitor V, the proposed ANFIS controller generates a compensation current reference. This reference adequately addresses the reactive power requirements imposed by nonlinear loads, ensuring the maintenance of DC voltage regulation. Through comprehensive simulation results, it is evident that the ANFIS controller surpasses in providing superior harmonic compensation and robust DC link voltage regulation under varying operating conditions. This research contributes to the advancement of intelligent control strategies for enhancing power quality and reliability in distribution systems.

Fuzzy Based Quick Acting DC Link Voltage Controller for Three Phases of D-Statcom Connected to the Microgrid

The microgrid systems are the combinations of solar photovoltaic, wind energy, fuel cell and battery systems, as well as conventional generators for backup. The micro grid system barriers that are encountered for their integration to the network. In power systems, voltage stability and power quality are major problems. Due to fluctuations in dc link voltage, changes in load may have an effect on the compensation. This work offers a fuzzy logic-based supervisory approach to enhance the performance of the dc link transient. The controllers employ proportional and integral gain changes with fuzzy logic PI controllers integrated with distribution static synchronous compensator (D-STATCOM). These changes occur in the transient response phase right after a load fluctuation. In order to verify the suggested controller, mathematical equations are given to compute the gains of the traditional controller using fuzzy-logic PI fast-acting dc-link voltage controllers for obtaining similar quick transient reaction. Fuzzy logic PI controller enhancements that employ greater sampling during the transient period and expert knowledge of system behavior enhance the controller's performance. Compared to a standard PI controller, a dc link error reduces the capacitor voltage during a load shift. Utilizing the suggested method and the outcomes of MATLAB simulations, it will be demonstrated that efficiency and the voltage's quick settling time.

Enhancing Wind Turbine and Fuel Cell Voltage Stability with Distribution Static Compensator

Integrated wind farms face significant challenges due to strict grid code requirements. Maintaining voltage stability is especially important for wind farms that are connected to the electrical grid. This research paper examines how FACTS devices, specifically Static Synchronous Compensators (STATCOMs), can be used to resolve voltage stability issues in wind farms and fuel cell power plants that employ Double Fed Induction Generators (DFIGs) and are connected to both loads and the power grid. During fault ride-throughs and power outages, wind farms face challenges such as voltage dips and fluctuations, which can negatively impact the grid. As a result, wind turbines require a stable grid to function effectively. In the absence of voltage stability measures, wind farms may experience reduced productivity, equipment failure, and downtime. As a dynamic voltage restorer, FACTS devices will be used. Thus, stable voltage levels are maintained, and power interruptions are prevented at DFIGbased wind farms. Three-phase impedance faults on load buses and 25% voltage sags on high voltage buses were examined in this study. STATCOMs were implemented as dynamic voltage restorers during fault ride-throughs and power grid disruptions in the MATLAB/SIMULINK simulations to mitigate voltage dips and fluctuations experienced by wind farms and fuel cells. Simulation results showed that STATCOMs significantly reduced downtime, increased power output, and minimized equipment failures in wind farms. Index terms: DFIG, Wind turbine, short circuit, Voltage Sag and STATCOM.

A Joint Logarithmic based nonlinear Adaptive filter for load balancing in electric power distribution system

When nonlinear loads are introduced to a distribution system, various power quality challenges emerge, such as load unbalance, harmonic distortion, and reactive power mismatch. This study presents a novel solution utilizing a joint logarithmic hyperbolic cosine adaptive filter-operated distribution static compensator to mitigate these issues. The cost function of the adaptive filter is designed to be smooth for minor errors and resilient to significant errors. The proposed control technique computes fundamental active and reactive currents, generating reference signals for the distribution static compensator. A comparative analysis with conventional adaptive control techniques is also conducted. The distribution system undergoes comprehensive testing under various dynamics to ensure compliance with IEEE-519 standards. Real-time simulation-based experiments are employed to showcase the algorithm's performance.

Power quality conditioning using two-level buck inverter based DSTATCOM

A two-level buck inverter is derived from the voltage source inverter, by replacing the additional power devices and suitable combination of inductor circuits respectively. Novel isolated buck inverter, featuring each-phase conversion and soft-switching within wide operation range, is developed. An optimized control strategy is employed to realize isolated buck conversion. By utilizing the buck inverter, the voltage stress on the power devices and passive components, the self-supported capacitor and filter inductance, is reduced to the half of the output voltage. Moreover, it is proven that the thyristor-controlled series capacitor (TCSC) equipped with a well-designed distributed static compensator (DSTATCOM) can effectively improve source current harmonics reduction, power factor correction in the source side, load compensation, regulation of load voltage and upholding constant voltage across the DC-link capacitor. In order to verify the effectiveness of the proposed DSTATCOM, its performance is compared with the two level DSTATCOM. The extensive simulations are carried out using MATLAB/Simulink to analyze the results. Experimental results using dSPACE-1104 prototype verify the appropriate DSTATCOM.

CHBMLI based DSTATCOM for power quality improvemt in a three-phase three-wire distribution system with PI controller

This paper presents a cascaded h-bridge (CHB) multilevel inverter (MLI) based MLI based distribution static synchronous compensator (DSTATCOM). The main objective of this paper is to reduce source current harmonics in the distribution system by using a cascade H-bridge multilevel inverter (CHBMLI) as DSTATCOM with a proportional-integral (PI) controller. The PI controller compensates reactive power, reduces source current harmonics, and maintains the unity power factor in the distribution system. The conventional two-level inverter-based DSTATCOM has many disadvantages such as high total harmonic distortion (THD), and high switching stress power semi-conductor devices, suitable for only low-power applications. This paper to overcome these drawbacks by using MLI-based DSTATCOM. The proposed system simulations are verified in MATLAB/Simulink software. The verified results are source current, load current, and compensating current.

A Multi-Objective Approach for Optimal Sizing and Placement of Distributed Generators and Distribution Static Compensators in a Distribution Network Using the Black Widow Optimization Algorithm

This paper presents a new optimization technique for the locations and sizes of Distributed Generators (DGs) and distribution static compensators (DSTATCOMs) in a radial system of a distribution network based on a multi-objective approach. It uses black widow optimization to improve voltage profile and power loss reduction. The black widow optimization simulates the mating behaviour of black widow spiders. The optimum size and placement of DGs and DSTATCOMs are deemed to be decision variables that are defined by using black widow optimization. The proposed technique is implemented in selected IEEE bus systems to evaluate its performance. The simulation results indicate reduced power losses and voltage profile enhancement as sizes and locations of integrated DGs and DSTATCOMs are adjusted based on optimization. The number of DGs and DSTATCOMs required to achieve the objectives is reduced. Furthermore, the results of the black widow algorithm are compared to existing techniques in the literature.

Fault detection through discrete wavelet transforms and radial basis function neural network in shunt compensated distribution systems

This paper discusses a critical study of fault detection, classification, and identification in distribution systems compensated through a distribution static synchronous compensator (D-STATCOM) using discrete wavelet transforms (DWT) and a radial basis function neural network (RBFNN). The efficacy of the proportional integral (PI) controller is discussed in the simulation during normal, voltage sag, and swell conditions. Then, the Daubechies mother wavelet (db4) is used here to extract and decompose the fault current signals because of its high accuracy of detection with less processing time. The models are subjected to different conditions of faults, such as line to ground (LG), line to line (LL), double line to ground (LLG), and three phases (LLL and LLLG) with different fault resistance. The novelty of the scheme is that DWT and RBFNN techniques were compared and proven effective in demonstrating the faulty conditions. To validate the proposed approach, a simulation study is carried out in MATLAB with various operating conditions, and it is shown that the proposed method can depend on abundantly protecting the distribution grid from faulty conditions.

Minimizing the impact of electric vehicle charging station with distributed generation and distribution static synchronous compensator using PSR index and spotted hyena optimizer algorithm on the radial distribution system

This research investigates the impact of electric vehicle charging station on power loss, voltage stability, and reliability within radial distribution systems. With the escalating use of electric vehicles, understanding these effects is crucial for ensuring the stability and efficiency of radial distribution systems infrastructure. The study formulates the electric vehicle charging station allocation problem as a multi-objective function, integrating power loss, voltage stability, and reliability metrics expressed as the PSR index. Using the IEEE 69-bus system as a test system, the research explores the ramifications of electric vehicle charging station integration and proposes strategies to mitigate their effects. An innovative combination of distributed generation and distribution static compensator are employed to alleviate the impact of electric vehicle charging station on radial distribution systems. A recent optimization methodology called spotted hyena optimizer algorithm is introduced to determine optimal electric vehicle charging station locations, with results compared to other existing algorithms. The study assesses potential power losses induced by additional electric vehicle loads, explores strategies to optimize charging rates for minimizing resistive losses, and evaluates voltage stability and reliability implications. The important results include objective function values obtained using various algorithms: Spotted hyena optimizer algorithm (0.7683), cuckoo search algorithm (0.7709), bat algorithm (0.8035), and African vultures optimization algorithm (0.7856). The findings demonstrate that the proposed algorithm outperforms other algorithms in minimizing the objective function value, indicating its efficacy in optimizing electric vehicle charging station placement within radial distribution systems. In conclusion, this research contributes valuable insights into the challenges associated with integrating electric vehicle charging station into radial distribution systems and provides innovative solutions for optimizing electric vehicle charging station placement, thereby advancing the understanding and management of distribution systems in the context of electric vehicle adoption.

HRES Integrated DSTATCOM Using High Gain Sepic-Zeta Based WOA Optimized ANFIS-MPPT Controller for PQ Issues

The power generated by renewable energy sources (RES), including photovoltaic (PV) and wind energy systems, are a great deal dependent on climate situations that result in Power Quality (PQ) issues, which require rapid adjustment of energy transmission and distribution systems. As a solution, (Distribution Static Synchronous Compensator) DSTATCOM is implemented for reactive power compensation, reducing voltage sag, swell, and THD. A novel High-gain SEPIC-ZETA converter is designed in this study to enhance the voltage obtained from the PV system with high efficiency. On the other hand, the proposed work aims to improve PQ issues using DSTATCOM with PV-Wind and battery systems. Adaptive Neuro-Fuzzy Inference System (ANFIS) based Maximum Power Point (MPPT) controller is adopted for tracking optimal power from the PV and to tune the parameters of this controller adopting Whale optimization algorithm (WOA). Moreover, the PWM rectifier is employed to convert the AC supply from the wind energy system to DC and it is controlled by the Proportional Integral (PI) controller. Hysteresis Current Controller (HCC) is incorporated to generate reference current based on Synchronous Reference Frame (SRF) theory, which is required for the reduction of harmonics. Three phase voltage source inverter is integrated to convert DC-AC supply for distributing the energy supply to load application. Finally, the anticipated work is implemented in MATLAB/Simulink and the comparative analysis is made towards the conventional topologies to authenticate the proficiency of the developed work. As a consequence, the outcomes demonstrate the improved PQ with a lower THD value of 0.72% with high tracking efficiency is accomplished by the proposed technique.

The Implementation of Space Vector PWM in 36-Pulse D-STATCOM for Power Quality Improvement

Introduction: This paper addresses the ongoing challenge of harmonics reduction in power systems, particularly focusing on Flexible AC Transmission Systems (FACTS) devices. Instead of employing a conventional multilevel converter, an alternative configuration is proposed: a 36-pulse gate turn-off thyristor-based converter (GTO-VSC). This converter comprises three 12-pulse Voltage Source Converters (VSCs) as fundamental units, operating collectively on the frequency mode of GTO switching control within a Distribution Static Synchronous Compensator (D-STATCOM). The D-STATCOM dynamically compensates reactive power in the system. The 36-pulse configuration results in AC output voltage waveforms containing harmonics such as the 35th, 37th, 71st, 73rd, etc., leading to higher total harmonic distortion (THD) levels. background: Reduced number of switches in flexible AC transmission. Method: In response, the paper presents a new model featuring a 3-level, 36-pulse, 25kV, ±3MVAr STATCOM configured with 12-pulse GTO-VSCs. This model incorporates PWM gate switching and employs a PI-control methodology to optimize harmonics in simulation, specifically targeting harmonics at the 35th, 37th, 71st, 73rd, etc., orders using Sim Power Systems toolbox in Math Works software. Result: The compensator's operational performance is controlled through switching angle optimization, which minimizes harmonics, regulates voltage, and manages reactive power in the electrical transmission system. Conclusion: The simulation results demonstrate that the proposed model is acceptable for enhancing the flexibility and performance of the FACTS device in mitigating harmonics in power systems.

Hres Integrated Dstatcom Using High Gain Sepic-Zeta Based Woa Optimized Anfis-Mppt Controller for Pq Issues

The power generated by renewable energy sources (RES), including photovoltaic (PV) and wind energy systems, are a great deal dependent on climate situations that result in Power Quality (PQ) issues, which require rapid adjustment of energy transmission and distribution systems. As a solution, (Distribution Static Synchronous Compensator) DSTATCOM is implemented for reactive power compensation, reducing voltage sag, swell, and THD. A novel High-gain SEPIC-ZETA converter is designed in this study to enhance the voltage obtained from the PV system with high efficiency. On the other hand, the proposed work aims to improve PQ issues using DSTATCOM with PV-Wind and battery systems. Adaptive Neuro-Fuzzy Inference System (ANFIS) based Maximum Power Point (MPPT) controller is adopted for tracking optimal power from the PV and to tune the parameters of this controller adopting Whale optimization algorithm (WOA). Moreover, the PWM rectifier is employed to convert the AC supply from the wind energy system to DC and it is controlled by the Proportional Integral (PI) controller. Hysteresis Current Controller (HCC) is incorporated to generate reference current based on Synchronous Reference Frame (SRF) theory, which is required for the reduction of harmonics. Three phase voltage source inverter is integrated to convert DC-AC supply for distributing the energy supply to load application. Finally, the anticipated work is implemented in MATLAB/Simulink and the comparative analysis is made towards the conventional topologies to authenticate the proficiency of the developed work. As a consequence, the outcomes demonstrate the improved PQ with a lower THD value of 0.72% with high tracking efficiency is accomplished by the proposed technique.