Enhanced momentum LMS‐based control technique for grid‐tied solar system

Singh, Sunaina; Kewat, Seema; Singh, Bhim; Panigrahi, Bijaya Ketan

doi:10.1049/iet-pel.2019.1126

Cited by 11 publications

(3 citation statements)

References 18 publications

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“…The updated weights are averaged to eliminate the effect of unbalancing in the current components. The basic building block of adaptive least mean square (ALMS) control algorithm is illustrated in Fig 11. This algorithm computes fundamental active (p) and reactive (q) weight components of load currents considering the grid voltages and RE source generation [114], [125], [126]. In this control algorithm, the new reactive weight component is updated by adding the product of reactive current error component (e qabc (n)) and reactive voltage unit vector component along with adaptive constant (τ q ).…”

Section: ) Adaptive Linear Element (Adaline) Control Theorymentioning

confidence: 99%

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

Chawda

Shaik

Mahela³

et al. 2020

IEEE Access

112

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Rapid industrialization and its automation on the globe demands increased generation of electrical energy with more reliability and quality. Renewable energy (RE) sources are considered as a green form of energy and extensively used as an alternative source of energy for conventional energy sources to meet the increased demand for electrical power. However, these sources, when integrated to the utility grid, pose challenges in maintaining the power quality (PQ) and stability of the power system network. This is due to the unpredictable and variable nature of generation by these sources. The distributed flexible AC transmission system (DFACTS) devices such as distributed static compensator (DSTATCOM) and dynamic voltage restorer (DVR) play an active role in mitigating PQ issues associated with RE penetration. The performance of DFACTS devices is mostly dependent on the type of control algorithms employed for switching of these devices. This paper presents a comprehensive review of various conventional and adaptive algorithms used to control DFACTS devices for improvement of power quality in utility grids with RE penetration. This review intends to provide a summary of the design, experimental hardware, performance and feasibility aspects of these algorithms reported in the literature. More than 170 research publications are critically reviewed, classified, and listed for quick reference for the advantage of engineers and academician working in this area. INDEX TERMS Adaptive control algorithm, conventional control algorithm, DFACTS device, modern utility grid, power quality, renewable energy source. ABBREVIATIONS 3P4W Three phase four wire 3P3W Three phase three wire ABT Admittance based theory ACA Adaptive control algorithm ADALINE Adaptive linear element theory ALMS Adaptive least mean square ANF Adaptive notch filter ANFIS Adaptive neuro-fuzzy inference system ARLS Adaptive recursive least square CCA Conventional control algorithm DFACTS Distributed flexible AC transmission system DSP Digital signal processing DSSSC Distributed static synchronous series compensator DSSC Distributed static series compensator DSTATCOM Distributed static compensator DSVC Distributed static var compensator DTCSC Distributed thyristor controlled series

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Section: ) Adaptive Linear Element (Adaline) Control Theorymentioning

confidence: 99%

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

Chawda

Shaik

Mahela³

et al. 2020

IEEE Access

112

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show abstract

“…Further in ANF two different techniques i.e, least mean square (LMS) and recursive least square (RLS) are employed for further investigations based on direct current control (DCC) to accomplish the extraction of harmonics in the distribution system. The LMS technique [23] is designed based on linear adaptive filtering with the objectives that the output is computed by the adaptive filter based on the estimation of the errors between the outputs and the desired response and the weights are updated automatically for minimizing the error. RLS algorithm is a self-adaptive algorithm [24] and is extensively implemented in many applications due to its simple structure and robust performance.…”

Section: Introductionmentioning

confidence: 99%

Industrial power quality enhancement using fuzzy logic based photovoltaic integrated with three phase shunt hybrid active filter and adaptive controller

Das

Hota²,

Pandey

et al. 2022

Applied Soft Computing

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“…It generates orthogonal sequence component which ensures high disturbance rejection capability, but phase-locked loops (PLLs) and a higher number of abc-dq0 transformations reduces the speed of response. Extraction of fundamental component is possible through some advanced control techniques such as the least mean square (LMS) technique [14], techniques based on adaptive notch filter (ANF) [15], adaptive linear element (ADALINE) [16], wavelet transformations [17], [18] etc. These advanced techniques have higher accuracy but an increased computational burden is undesirable in grid-connected systems.…”

Section: Introductionmentioning

confidence: 99%

Grid integrated solar energy transfer system with a two‐layer complex coefficient filter‐based control

Mukundan

Pychadathil

et al. 2021

IET Power Electronics

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In this paper, a novel control strategy for grid-integrated solar energy transfer system (SETS) is proposed which enhances the grid power quality along with active power injection. Some of the conventional grid synchronization controls face problems due to imperfect estimation of fundamental active load current during both grid-side and load-side disturbances. The proposed two-layer multiple-complex coefficient filter control improves the performance of SETS by accurately estimating the fundamental active load current at adverse operating conditions. One layer extracts the fundamental positive sequence of the sensed three-phase grid voltages and derives the unit in-phase voltage templates for grid currents reference generation to achieve unity power factor operation. The second layer evaluates the average active fundamental component of the load currents, and finally derives the reference amplitude of three-phase grid currents. The two-stage SETS consists of a quadratic boost DC-DC converter to extract the maximum solar array power forming an interface between PV array and inverter. It also provides high voltage gain and decreases the length of the PV array string while maintaining a low DC-link voltage ripple, extending the service life of the SETS. The effect of a nonlinear unbalanced load is nullified and therefore the grid current's waveform quality is maintained in compliance with the IEEE-519 standard during the dynamic operating conditions. The SETS provides sinusoidal, balanced, and steady grid currents at unity power factor withstanding adverse operating conditions such as distorted grid voltages, varying irradiance and varying unbalanced nonlinear load currents. Due to its flexibility to operate in such adverse conditions, the proposed control based SETS is suitable for grid-connected applications. Simulations are carried out in MATLAB/Simulink and results validate the performance of the SETS. The hardware prototype of the proposed SETS is developed and rigorously tested under various operating conditions to validate the proposed claims.

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Enhanced momentum LMS‐based control technique for grid‐tied solar system

Cited by 11 publications

References 18 publications

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

Industrial power quality enhancement using fuzzy logic based photovoltaic integrated with three phase shunt hybrid active filter and adaptive controller

Grid integrated solar energy transfer system with a two‐layer complex coefficient filter‐based control

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