A Maximum Correntropy Criteria Based Adaptive Algorithm for an Improved Power Quality SPV System

Modi, Gaurav; Kumar, Shailendra; Singh, Bhim

doi:10.1109/poweri.2018.8704371

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…On the other hand, adaptive controls have a moderate computational burden and deliver reduced steady-state error with a faster convergence speed. Adaptive algorithms such as least mean square (LMS) [30], least mean fourth (LMF) [31], maximum correntropy criteria (MCC) [32] deliver faster convergence and robustness. The LMS control due to the fixed step size, produce a relatively higher steady-state error as compared to the LMF, which acts as a higher-order filter for the error signal.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

et al. 2021

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This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using a multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) control of the presented system is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and maximum power point tracking (MPPT) control is accomplished using the variable step-size incremental conductance (VSS-InC) technique. The proposed VSC control offers lower mean square error and better accuracy, convergence rate and speed as compared to peer adaptive algorithms, i.e., least mean square (LMS), least mean fourth (LMF), maximum correntropy criteria (MCC), etc. The adaptive Gaussian kernel width is a function of the error signal, which changes to accommodate and filter Gaussian and non-Gaussian noise signals in each iteration. The VSS-InC based MPPT is provided with a MOGHO based modulation factor for better and faster tracking of the maximum power point during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates the DC bus to improve the power quality, and DC link stability during dynamic conditions. The optimized DC-link generates an accurate loss component of current, which further improves the VSC capability of fundamental load current component extraction. The VSC is designed to perform multi-functional operations, i.e., harmonics elimination, reactive power compensation, load balancing and power balancing at point of common coupling during diverse dynamic conditions. The MOSHO based VSS-InC, and DC bus performance is compared to particle swarm optimization (PSO) and genetic algorithm (GA). The proposed system operates satisfactorily as per IEEE519 standards in the MATLAB simulation environment.

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Section: Introductionmentioning

confidence: 99%

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

et al. 2021

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“…The KAF methods utilize the MSE as a cost function, which provides adequate accuracy, stability, and convergence rates with Gaussian noises. More robust adaptive algorithms, such as maximum correntropy criteria (MCC) [11], which is a biased estimator, utilizes the Gaussian kernel for better mean square stability. The reweighted zero-attracting MCC (RZA-MCC) [12] enhances the performance of MCC with a zero-attracting algorithm resulting in a better convergence rate and reduced harmonics level.…”

Section: Introductionmentioning

confidence: 99%

Nyström Minimum Kernel Risk-Sensitive Loss Based Seamless Control of Grid-Tied PV-Hybrid Energy Storage System

et al. 2021

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This paper presents Nyström minimum kernel risk-sensitive loss (NysMKRSL) based control of a three-phase four-wire grid-tied dual-stage PV-hybrid energy storage system, under varying conditions such as irradiation variation, unbalanced load, and abnormal grid voltage. The Voltage Source Converter (VSC) control enables the system to perform multifunctional operations such as reactive power compensation, load balancing, power balancing, and harmonics elimination while maintaining Unity Power Factor (UPF). The proposed VSC control delivers more accurate weights with fewer oscillations, hence reducing overall losses and providing better stability to the system. The seamless control with the Hybrid Energy Storage System (HESS) facilitates the system’s grid-tied and isolated operation. The HESS includes the battery, fuel cell, and ultra-capacitor to accomplish the peak shaving, managing the disturbances of sudden and prolonged nature occurring due to load unbalancing and abnormal grid voltage. The DC link voltage is regulated by tuning the PI controller gains utilizing the Salp Swarm Optimization (SSO) algorithm to stabilize the system with minimum deviation from the reference voltage, during various simulated dynamic conditions. The optimized DC bus control generates the accurate loss component of current, which further enhances the performance of the proposed VSC control. The presented system was simulated in the MATLAB 2016a environment and performed satisfactorily as per IEEE 519 standards.

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“…519 [12] have set the guidelines to limit the harmonics currents in the LV-AC network. Various improved power converter topologies [13][14][15] and improved control methods [16][17][18][19][20][21][22] are discussed in the literature to limit the harmonics currents in the AC network due to the generation of the SPVP and the load characteristic, respectively. In [13], the transformer integrated filtering method, in [14], a 7-level T type multilevel inverter (MLI) based power converter topology and in [15], interleaved MLI based topology are presented to reduce the harmonics currents injected by the SPVP at the PCC.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, active shunt compensation [16] and active series compensation [17] are discussed to diminish the effect of the load harmonics currents on the LV‐AC network. The effect of the load harmonics currents can also be diminished by controlling the SPVP [18] as its configuration is the same as the active shunt compensator. The SPVP can be used to provide the multifunctional operational capability such as power quality improvement (PQI) at the PCC, to minimize the line losses in the LV‐AC network, and mitigation of the negative sequence and zero sequence currents problem at the PCC, etc.…”

Section: Introductionmentioning

confidence: 99%

Multi‐functional commercial solar photovoltaic plant integrated to three‐phase low voltage AC network

Modi

Singh

2021

IET Power Electronics

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This study presents the commercial solar PV plant (SPVP) operation, integrated into the low voltage (LV) AC network. The SPVP has the multi-functional operational capability. It feeds the PV array generated power to loads and the AC network, while ensuring the power quality improvement at the point of common coupling (PCC) as per the IEEE std. 519, irrespective of the load characteristic (linear/nonlinear and balanced/unbalanced). The SPVP minimises the line losses in the AC network by recouping the load reactive power requirement locally. Moreover, the SPVP operates in either maximum power extraction (MPE) mode or constant power generation (CPG) mode, depending upon the rise in PCC voltage amplitude during the peak PV array power generation and low load demand condition. The SPVP switches between the MPE and the CPG modes during the high rise in PCC voltage amplitude and regulates the PV array generated power to protect itself and the load connected at PCC. In this study, an adaptive filter technique based on maximum correntropy criterion is used for the PQI, and the perturb and observe based algorithm is used for MPE. A simulation model and reduced rating hardware prototype are developed to validate the system's performance.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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A Maximum Correntropy Criteria Based Adaptive Algorithm for an Improved Power Quality SPV System

Cited by 11 publications

References 12 publications

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

Nyström Minimum Kernel Risk-Sensitive Loss Based Seamless Control of Grid-Tied PV-Hybrid Energy Storage System

Multi‐functional commercial solar photovoltaic plant integrated to three‐phase low voltage AC network

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