Evaluation and Control Perceptive of VSM-Based Multilevel PV-STATCOM for Distributed Energy System

Thakre, Mohan P.; Kumar, Nitin

doi:10.1007/s12647-021-00481-x

Cited by 15 publications

(8 citation statements)

References 42 publications

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“…A mathematical concept for modeling diodes together with analytical and optimization methods was stated here. For this, a complete discussion about the single diode PV cell model mathematical equation was done as it is required [15], [16]. In this section mathematical modelling concept for single diode model has been explained.…”

Section: Photovoltaic Diode Modelling and Problem Framingmentioning

confidence: 99%

Five parameters extraction of single diode PV model by metaheuristic optimization method by identified built-up data

2023

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Precision calculation of unknown photovoltaic (PV) modules or single diode models for PV cell specifications under various environmental conditions is needed to build a sunlight-based PV framework. Installing a PV system requires knowledge of all parameters, modeling, and optimization techniques because PV system analysis and configuration help generate renewable energy. This concept requires accurate modeling and calculation of identified and unknown parameters. The single-diode model is simple and accurate for different mathematical equations. Streamlining calculations requires distinguishing this nonlinear model. The current investigation calculated five unknown parameters and compared them with particle swarm optimization (PSO) and wind-driven optimization (WDO) optimization results. The said approach utilizes MATLAB software, analytical as well as optimization methods, and manufacturing data. The suggested method is simple, fast, and accurate for calculating diode ideality factor (A), output currents (Io), series resistance (Rs), Shunt resistance (Rsh), and photocurrent (Iph).

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Section: Photovoltaic Diode Modelling and Problem Framingmentioning

confidence: 99%

Five parameters extraction of single diode PV model by metaheuristic optimization method by identified built-up data

2023

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“…It is used as a controller for PV-STATCOM, in which the solar inverter is used for maximum power point tracking as part of the PV system [68]. Thakre & Kumar [69] and Gupta et al [70] used STATCOM to do an analysis of the operation and control of drop voltage on the distribution network under normal and contingency conditions to reduce the total power losses associated with voltage fluctuations on the distribution network.…”

Section: -Artificial Intelligent Control Of Hvdc Systemmentioning

confidence: 99%

Artificial Intelligence-based Control Techniques for HVDC Systems

Abdulwahid

2023

Emerg Sci J

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The electrical energy industry depends, among other things, on the ability of networks to deal with uncertainties from several directions. Smart-grid systems in high-voltage direct current (HVDC) networks, being an application of artificial intelligence (AI), are a reliable way to achieve this goal as they solve complex problems in power system engineering using AI algorithms. Due to their distinctive characteristics, they are usually effective approaches for optimization problems. They have been successfully applied to HVDC systems. This paper presents a number of issues in HVDC transmission systems. It reviews AI applications such as HVDC transmission system controllers and power flow control within DC grids in multi-terminal HVDC systems. Advancements in HVDC systems enable better performance under varying conditions to obtain the optimal dynamic response in practical settings. However, they also pose difficulties in mathematical modeling as they are non-linear and complex. ANN-based controllers have replaced traditional PI controllers in the rectifier of the HVDC link. Moreover, the combination of ANN and fuzzy logic has proven to be a powerful strategy for controlling excessively non-linear loads. Future research can focus on developing AI algorithms for an advanced control scheme for UPFC devices. Also, there is a need for a comprehensive analysis of power fluctuations or steady-state errors that can be eliminated by the quick response of this control scheme. This survey was informed by the need to develop adaptive AI controllers to enhance the performance of HVDC systems based on their promising results in the control of power systems. Doi: 10.28991/ESJ-2023-07-02-024 Full Text: PDF

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“…For voltage balancing, [10] presented a modular multilevel converter with a simplified nearest-level control (NLC) strategy. Characterizes the implementation and monitoring conceptions of a value stream mapping (VSM-based) multilevel PV-STATCOM for harmonic elimination in a distributed energy system [11]. The uses of include flexible AC transmission systems (FACTS) controllers ISSN: 2302-9285  and custom devices as well as EV applications demonstrate a wide range of power quality improvement methodologies [12]- [14].…”

Section: Introductionmentioning

confidence: 99%

A novel pulse charger with intelligent battery management system for fast charging of electric vehicle

Kadlag¹,

Thakre²,

Mapari

et al. 2023

Bulletin EEI

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Electric vehicles contribute a major role in building an eco-friendly environment. Li-ion batteries are most widely used in electric vehicles. It is very important to maintain the operation of Li-ion batteries within their “safety operation area (SOA)”. Hence implementing a battery management system (BMS) becomes a necessity while using Li-ion batteries. This paper proposes an intelligent BMS for electric vehicles using proportional integral derivative (PID) control action along with artificial neural network (ANN). It prefers the improved pulse charging technique. The design consists of a battery pack containing four 12 V Li-ion batteries, MOSFETs, Arduino Uno, a transformer, a temperature sensor, a liquid-crystal displays (LCD), a cooling fan, and four relay circuit are used. Arduino Uno is used as a master controller for controlling the whole operation. Using this design approximately 38 minutes are required to fully charge the battery. Implementation results validate the system performance and efficiency of the design.

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Evaluation and Control Perceptive of VSM-Based Multilevel PV-STATCOM for Distributed Energy System

Cited by 15 publications

References 42 publications

Five parameters extraction of single diode PV model by metaheuristic optimization method by identified built-up data

Five parameters extraction of single diode PV model by metaheuristic optimization method by identified built-up data

Artificial Intelligence-based Control Techniques for HVDC Systems

A novel pulse charger with intelligent battery management system for fast charging of electric vehicle

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