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This study presents the design and functional performance of Cross Least Mean Square (X-LMS) neural network based distributed static compensator for shunt compensation. First, considering the adaptive least mean square (ALMS) technique, harmonics correction, power factor (p.f) upgrading, load balancing, and voltage regulation at the supply bus are attained. Second, based on the X-LMS principle, active and reactive components of load current by updating their respective weights are mathematically analyzed. The main objective is to extract the tuned weighted values of fundamental active and reactive power components of distorted load currents using the suggested adaptive principle. The X-LMS exhibits better convergence speed provides a significant computational saving and avoids the additional filtering needed with the ALMS structure. Finally, the X-LMS model is built using MATLAB/Simulink for simulation study and validated experimentally by d-SPACE laboratory setup results. The parameter design of X-LMS can be used to improve the harmonic reduction with other compensation performances to showcase better power quality of the distribution utility. [ABSTRACT FROM AUTHOR]

This article demonstrates the performance of back-to-back connected voltage source inverter (BTB-VSI)-based distribution static compensator (DSTATCOM). In the proposed system, a three-phase three wire electrical utility system (EUS) is integrated with distributed energy resources (DER) through BTB-VSI. It has drawn more attention due to enhanced active power filtering, simple design procedure and performs reliable operation. The objectives of the research work is to provide clean power for weak EUS with improved power quality (PQ) such as, better voltage regulation, improved power factor (P.F), reduced total harmonic distortion (THD), balanced voltage at point of common coupling (PCC) and better optimal active power flow control (OAPFC), and so on. An artificial neurocontrol technique Kernel Hebbian Least Mean Square (KHLMS) is chosen to determine the accurate reference source current for operation of voltage source inverter (VSI). The BTB-VSI performance is investigated on both shunt compensation and OAPFC. The proposed system is converted to a simulation model and hardware unit using MATLAB/Simulink software and SPARTAN−6 field programmable gate arrays (FPGA) controller. Finally, the Simulation and experimental results illustrate that the shunt compensating ability with OAPFC of BTB-VSI performs better over VSI as per IEEE Std 1159–2019 grid code. [ABSTRACT FROM AUTHOR]

In this research work, two Back to Back connected 2-level voltage source inverters (BBC-VSI) under three phase three wire weak utility grid is examined. Generally, the challenges addressed in the modern utility grid are end users' nonlinear loads and dependency on conventional energy sources. The end users' nonlinear loads generate power quality (PQ) issues and dependency on conventional energy sources raises environment pollution and economic crises. The BBC-VSI based distribution static compensator (DSTATCOM) topology consists of two voltage source inverters (VSIs) supplied by a distributed energy resources (DERs) supported common DC-link capacitor. A sparse least mean squares (SLMS) technique is selected for generating the pulses IGBTs. The SLMS technique offers high estimation speed, less than one cycle weight convergence, fast transient response and small error in steady state over conventional technique. A holistic comparison is performed between the BBC-VSI and VSI using the field programmable gate arrays (FPGA) SPARTAN-6 control board regarding optimal power flow control, which shows the BBC-VSI is competitive. Also, it is authenticated under different conditions like source current shaping before and after compensation, source power failure, DER power fluctuation, nonlinear load variation, etc., which are naturally encountered in a modern utility grid. [ABSTRACT FROM AUTHOR]

This article proposes an adaptive Kernel-Hebbian least mean square (KHLMS) controller for a dual voltage source inverter (VSI). The recommended topology consists of a distributed energy resource (DER) supported VSI called main VSI (MVSI) and split capacitor supported VSI termed as auxiliary VSI (AVSI). Both the MVSI and AVSI are used to serve the shunt compensation when DER is not integrated with MVSI. The DER scenario is considered to suppress the active power flow shortage in the utility grid. Here, optimal active power flow control (OAPFC) is managed by MVSI and shunt compensation is achieved by AVSI during DER operated mode. Hence, a dual VSI based distribution static compensator (DSTATCOM) facilitates the configuration merits such as reduction in system downtime cost, filter rating switching stress etc. Supremacy of both the neural network (NN) based controller and topology is presented by comparing VSI (called AVSI) in the context of harmonic reduction in source side, voltage balancing, power factor (PF) enhancement, better voltage regulation and OAPFC. The experimental results are obtained through field programmable gate array (FPGA) based hardware units which exhibit radical improvement in the power quality (PQ) conferring as per the international standard grid code (IEEE-519-2017). [ABSTRACT FROM AUTHOR]

Microgrids have emerged as a feasible solution for consumers, comprising Distributed Energy Resources (DERs) and local loads within a smaller geographical area. They are capable of operating either autonomously or in coordination with the main power grid. As compared to Alternating Current (AC) microgrid, Direct Current (DC) microgrid helps with grid modernisation, which enhances the integration of Distributed and Renewable energy sources, which promotes energy efficiency and reduces losses. The integration of energy storage systems (ESS) into microgrids has garnered significant attention due to the capability of ESS to store energy during periods of low demand and then provide it during periods of high demand. This research includes planning, operation, control, and protection of the DC microgrid. At the beginning of the chapter, a quick explanation of DC microgrids and their advantages over AC microgrids is provided, along with a thorough evaluation of the various concerns, control techniques, challenges, solutions, applications, and overall management prospects associated with this integration. Additionally, this study provides an analysis of future trends and real-time applications, which significantly contributes to the development of a cost-effective and durable energy storage system architecture with an extended lifespan for renewable microgrids. Therefore, providing a summary of the anticipated findings of this scholarly paper contributes to the advancement of a techno-economic and efficient integration of ESS with a prolonged lifespan for the use of green microgrids. [ABSTRACT FROM AUTHOR]

This paper presents a dual voltage source inverter (DVSI)-based Distributed Static Compensator (DSTATCOM) to enhance the power quality in the power utility system (PUS). The proposed DSTATCOM consists of two numbers of two-level voltage source inverters (VSI) which controls the reactive power. One of them is regarded as the main voltage source inverter (MVSI) and the other is considered as auxiliary voltage source inverter (AVSI). The i cos ⁡ ϕ control algorithm is employed to generate the reference source currents as well as switching pulses. The detailed control algorithm is formulated by mathematical analysis using MATLAB/Simulink, and compared with different case studies. Among all the theoretical findings, the DVSI offers better voltage regulation, voltage balancing, source current harmonic reduction and power factor correction under various loading scenarios. Apart from these, reliability, stress balancing of the both MVSI and AVSI, cost reduction due to a decrease in the filter size and better operation of PUS is obtained. To check the effectiveness, the performance of the DVSI-based DSTATCOM is carried out as per the benchmark value of the IEEE-519-2014 and IEC-61000-1 grid code. [ABSTRACT FROM AUTHOR]

The power quality (PQ) improvement employing appropriate intelligent controllers is identified as a suitable solution for the dependable, safe, and stable operation in the electric utility systems (EUS). Hence, this paper proposes new types of neural network (NN) based Greedy Least Mean Square (GLMS) controllers for distributed static compensators (DSTATCOM). First, the EUS is developed by considering current source-based non linear load using the MATLAB/Simulink environment. Next, both controllers are implemented by their own learning principle using embedded systems toolboxes. The proposed scheme combines different weighting factors like step size, learning rate and convergence factor to achieve the approximate tuned weight. Then, the final weighting components are achieved by adding DC and AC PI controller weights corresponding to the mean value of active/reactive weight of load currents for the triggering pattern. The proposed control algorithm provides a precise control for the system by maintaining reduced voltage across the self-braced capacitor as compared to the Adaptive Least Mean Square (ALMS) controller. The other PQ merits like better voltage regulation, load balancing, total harmonic distortion (THD) suppression, and power factor (P.F) improvement are attained. Finally, experimental results obtained from the proposed controller fulfill all the shunt-related PQ requirements as per IEEE benchmark for the different case studies. [ABSTRACT FROM AUTHOR]

In this research paper, an inductively coupled distributed static compensator (IC-DSTATCOM) for three phase three wire (3P3W) electric power distribution system (EPDS) is proposed. The contraction of power quality (PQ) was marked as a perilous droop mode bump into direct coupled distributed static compensator (DC-DSTATCOM). To regain the PQ, inductive coupling transformer is assisted in conjunction with DC-DSTATCOM. The system equivalent circuit of IC-DSTATCOM is accomplished by take into account of impedance of both transformer and DC-DSTATCOM to reveal the filtering technique. The filtering icosØ mechanism is performed by following the generalized mathematical approach using MATLAB/Simulink. A case education is reviewed in detail to illustrate the performance of both DC-DSTATCOM and IC-DSTATCOM. The IC-DSTATCOM is amplified healthier as compared to other in terms of harmonics shortening, good power factor, load balancing, and potential regulation. To examine the effectiveness, simulation outputs of the IC-DSTATCOM with different PQ parameter indices are presented by following the benchmark measure of IEEE-2030-7-2017 and IEC-61000-1 system code. [ABSTRACT FROM AUTHOR]

This research study explains the feasibility of implementing machine learning (ML) oriented inductively coupled distributed static compensator (IC-DSTATCOM) for power quality (PQ) enhancement. The issue involved in declining the power quality (PQ) using direct coupled static compensator (DC-DSTATCOM) was identified as a hazardous disappointment. Hence, to improve the quality, coupling transformer is served in unification with DCDSTATCOM. Also, the recent growth of machine learning (ML) systems and progression of computational resources, with unpredicted data obtainability, has inspired the researchers. In this study, density based spatial clustering of application with noise (DBSCAN) is employed by using its own learning mechanism (LM) using MATLAB/Simulink. This controller contains six subnets. Among them, six subnets are employed for active tuned weight extraction whereas other three subnets are used for reactive part. Moreover, the abovesaid devices are triggered with the help of generated reference supply current. A case education is reviewed in detail to demonstrate the operation of both DC-DSTATCOM & IC-DSTATCOM. Finally, the IC-DSTATCOM is amplified healthier as compared to other in terms of harmonics shortening, upgrading in power factor, load balancing, and potential regulation etc. To examine the effectiveness, simulation outputs of the IC-DSTATCOM is presented by following the benchmark measure of IEEE-2030-7-2017 and IEC-61000-1 grid code. [ABSTRACT FROM AUTHOR]

This research study explains the design and performance of a Static VAR Compensator (SVC) coupled Hybrid Distribution Static Compensator (DSTATCOM) for low voltage power distribution system (PDS). A comparative analysisis done between Voltage Source Inverter (VSI)-based DSTATCOM and SVC Hybrid DSTATCOM using Jordan Least Mean Square (JLMS) algorithm to alleviate the shunt-related power quality (PQ) glitches. The specific design is obtained as compared to the existing neural network toolbox algorithm to improve the estimation speed and accuracy. The main objective is to extract the tuned weighted values of fundamental active and reactive power components of distorted load currents for the switching signal generation using an adaptive JLMS algorithm.Several functions of DSTATCOM and hybrid DSTATCOM using this JLMS controller are showcased for harmonics curtailment, power factor (p.f.) improvement, load balancing, voltage regulation, etc. Simulation results on an SVC Hybrid DSTATCOM have shown an acceptable level of performance under unbalanced loading situations. Finally, some comparative results are provided to validate the feasibility and effectiveness of the suggested topology. [ABSTRACT FROM AUTHOR]

This paper presents the shunt compensation performance of quasi-Z-source inverter (QZSI) and back to back connected QZSIs (BB-QZSI) to address the power quality (PQ) issues in the three-phase three-wire power utility network (PUN). Generally, these PQ issues are poor voltage regulation, low power factor (PF), source current distortion, unbalanced voltage, etc. The proposed BBQZSI-based distribution static compensator (DSTATCOM) consists of two QZSIs with a common dc-link capacitor. Because the QZSI could achieve buck/boost conversion as well as DC to AC inversion in a single-stage and the back to back configuration decreases the system down time cost (if a fault occurs in one QZSI the other can continue the shunt compensation). Particularly, icos ϕ control algorithmcontrol algorithm is implemented to generate proper switching pulses for the switches of DSTATCOM. The effectiveness of the BB-QZSI is verified through simulation studies over QZSI using MATLAB/Simulink software satisfying the recommended grid code. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to introduce a new Hebbian least mean square control algorithm for two level self‐supported voltage source converter based distributed static compensator. The Hebbian least mean square controller is employed on the various aspects such as, weight updating, direct and quadrature unit voltage template, active and reactive part of reference supply currents and switching signal generation. Firstly, a set up equations using Hebbian least mean square are premeditated to compute both active and reactive weight updating. Secondly, DC and AC proportional integral controller outputs are involved with the updating weight to generate the reference supply current. The error signal obtained from both reference and actual source current is processed through the hysteresis current controller for the gate signal firing. The MATLAB/Simulink results as well as experimental results prove that the proposed algorithm is competent to afford the better voltage regulation, voltage balancing, source current harmonic reduction and power factor correction. Finally, performance obtained from the proposed controller reveals the applicability for various loading condition in the distribution grid. [ABSTRACT FROM AUTHOR]

Sparse least mean square algorithm is proposed for the DSTATCOM as an optimal current harmonic extractor to cope with the intermittent nature of loadings. Sparse least mean square is the improved version of adaptive least mean square learning mechanism with regards to sparsity. This innovative approach is utilized for better parameter estimation due to its algorithmic simplicity and parallel computing nature. Hence, sparse least mean square is expected to reduce the computation and storage requirements significantly. This suggested controller consists of six subnets. Three subnets for active and another three for reactive weight component are used to extract the fundamental component of the load current. Several factors like previous weight, normalizing weight and learning rate are involved in the sparse least mean square based weight‐updating rule to have better dynamic performance, reduced computational burden and better estimation speed etc. The detailed control algorithm is formulated using MATLAB/Simulink, and validated using experimental analysis. Among these two algorithms, the sparse least mean square offers better voltage regulation, voltage balancing, source current harmonic reduction and power factor correction under various loading scenarios. [ABSTRACT FROM AUTHOR]

The requirement of a robust and adaptive control algorithm in active filters is inevitable nowadays. In this paper, an ADAptive LINEar neuron (ADALINE) based Least Mean Square (LMS) control algorithm is proposed for a three-phase-four-wire (3P4W) distribution power system under unbalanced loading conditions. The proposed controller has a unique inbuilt characteristic to extract the fundamental active positive sequence component from an unbalanced load current. Particularly, the control algorithm is intended to calculate an adaptive and suitable amplitude for the three-phase reference source currents which are used for the switching pulse generation in the subsequent steps. Moreover, the Distribution STATic COMpensator (DSTATCOM) is performed to eliminate harmonic contents of supply current and harmful excessive neutral current in the system. Further, the DC-link voltage is regulated in order to reduce the power loss across the DSTATCOM, and to attain a balanced, high-quality power availability at the Point of Common Coupling (PCC). The proposed system is accomplished in the MATLAB2014a/Simulink, and a low power rated 3P4W DSTATCOM prototype incorporating with the dSPACE1104 real-time environment to verify the proposed control algorithm. [ABSTRACT FROM AUTHOR]

In this study, the design and implementation of a new hybrid soft computing control technique called Levenberg–Marquardt backpropagation (LMBP)‐based icosϕ is proposed. Two different compensation techniques are evaluated for the performance analysis of three‐phase three‐wire (3P3W) voltage source converter (VSC)‐based DSTATCOM. The first one is the conventional icosϕ control technique whereas the other one is called the LMBP‐based icosϕ control technique. The better power quality of the system is obtained using the proposed control algorithm by maintaining a less voltage across the capacitor as compared to the conventional one. So, the reduction in the size of the DSTATCOM is realised by the LMBP‐based control algorithm. Furthermore, the performance parameters such as load balancing, harmonics elimination, power factor improvement, and voltage regulation are evaluated under both balanced and unbalanced loading conditions as per the IEEE guidelines. The effectiveness of the proposed controller is studied in the MATLAB/Simulink environment and also validated with a low power rated prototype experimental results. [ABSTRACT FROM AUTHOR]

The assessment of the shunt compensation allied power quality glitches bounds the design and modelling of a controller for the d-FACTS (Distribution Flexible Alternating current Transmission System) device. So, Kernel Hebbian least mean square (KHLMS) is proposed for controlling the distributed static compensator (DSTATCOM) in this study. The KHLMS is the improved version of an adaptive LMS (ALMS), which is designed by using a suitable pattern of learning mechanism. Both the controller algorithms are formulated on the basis of mathematical equations using MATLAB/Simulink. In accordance with the system variation adaptability and experimental application, each phase controller is configured as an independent neural network structure. The objective of control algorithms is used for the extraction of fundamental active and reactive components from load currents for the generation of the reference source currents. In comparison with the ALMS algorithm, the KHLMS demonstrates more effective in improving the voltage regulation at DC link capacitor, voltage balancing, source current harmonic reduction, and power factor correction under the disturbance influences caused by even and uneven loading. [ABSTRACT FROM AUTHOR]

A propounded control strategy called naive back propagation (NBP)-based icosϕ is implemented in designing of distribution static compensator (DSTATCOM) in this study. The performance of the DSTATCOM using both the proposed and icosϕ control technique are compared under varying load condition in the three-phase three-wire (3P3W) distribution system. The extraction of both tuned active as well as reactive weighting components are obtained from the accuracy of the control algorithm with respect to proportional.integral controllers. The comparative study reveals with source current harmonics reduction, voltage regulation, load balancing, power factor correction and sizing of VSC. The results demonstrate the robustness of the DSTATCOM in order to show the superiority, reliability, robustness and effectiveness of the proposed approach compared with the conventional one. The effectiveness of both the algorithms are validated through the simulation using MATLAB and real-time implementation conducted in real time digital simulator (RTDS) environment, showing the power quality indices. [ABSTRACT FROM AUTHOR]

This research work introduces a new hybrid technique called quasi‐Newton back‐propagation based i cosϕ control algorithm. Its structure is constructed on the concept of biological features like input neuron, target neuron, weight correction and more attractive due to its parallel computing, learning capability behaviour. Systematic step‐by‐step procedures are represented by mathematical equations in the MATLAB/Simulink platform. The fundamental weighted values of active and reactive power components of load currents are extracted using the proposed control technique to generate the reference source currents. Further, the reference source currents are used to generate switching pulses for voltage source converter (VSC) of the distributed static compensator (DSTATCOM). It is capable enough to perform several functions such as harmonic mitigation, power factor correction, load balancing and voltage regulation which further reduce the DC link voltage across the self‐supported capacitor of the VSC. Simulation and experimental validation demonstrates better performance of the suggested algorithm for operation of the DSTATCOM at different loading conditions. [ABSTRACT FROM AUTHOR]

A new hybrid control technique called gradient descent back propagation (GDBP)-based i cos ø for a three phase twolevel distribution static compensator (DSTATCOM) to perform the functions such as harmonic mitigation, power factor correction under reactive loads, which further reduces the DC link voltage across the self-supported capacitor of voltage source converter (VSC). The weighted value of fundamental active and reactive components of load currents are extracted using the proposed control technique to generate the reference source currents. Furthermore, these currents are used to trigger the VSC of the DSTATCOM. The effectiveness of this control technique is demonstrated through simulation using MATLAB/SIMULINK and sim power system tool boxes. The real-time implementation of DSTATCOM is also realised by real-time digital simulator. These results reveal the robustness of the proposed DSTATCOM as it is showing outstanding harmonic compensation capabilities under the various loading conditions and keeping the total harmonics distortion of the source current well <5%, the limit imposed by IEEE-519 standard. [ABSTRACT FROM AUTHOR]