Application of modular multilevel converter for AGC in an interconnected power system

Madichetty, Sreedhar; Dasgupta, A.; Kumar, Lokender

doi:10.1016/j.ijepes.2015.07.033

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…In , an advanced version of controlling scheme has been called as multi variable controlling scheme. The d‐axis and q‐axis components could be written as

V_{a}^{d} = \frac{1 + S T_{n}}{S T_{i}} i_{d} - \frac{ω T_{n}}{S T_{i}} i_{q}

V_{a}^{q} = \frac{1 + S T_{n}}{S T_{i}} i_{q} - \frac{ω T_{n}}{S T_{i}} i_{d} .

…”

Section: Various Control Schemes Of Vscmentioning

confidence: 99%

Power conversion in renewable energy systems: A review advances in wind and PV system

Kumar¹,

Kumar

2016

Int. J. Energy Res.

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Summary Grid‐connected photo voltaic (PV) systems are being developed very fast and systems from a few kW to tenths of a MW are now in operation. As an important source of distributed generation (DS) the PV systems need to comply with a series of standard requirements in order to ensure the safety and the seamless transfer of the electrical energy to the grid. Multilevel voltage source converters (VSC) is a heart of the PV system and are emerging as an important power converter options for low, medium, and high‐power applications. These VSCs have bought numerous advantages, especially in renewable energy systems such as PV and wind energy systems. In this article, several topologies of VSCs, which brings together some concepts from traditional converters and multi‐level converters, are presented. Also, several control strategies for controlling current, voltage, active power and reactive power have also been reviewed. Various topologies with their technical aspects have been reviewed and the best suitable topology and control scheme for grid connected PV and wind energy systems has been suggested. Copyright © 2016 John Wiley & Sons, Ltd.

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“…In , an advanced version of controlling scheme has been called as multi variable controlling scheme. The d‐axis and q‐axis components could be written as

V_{a}^{d} = \frac{1 + S T_{n}}{S T_{i}} i_{d} - \frac{ω T_{n}}{S T_{i}} i_{q}

V_{a}^{q} = \frac{1 + S T_{n}}{S T_{i}} i_{q} - \frac{ω T_{n}}{S T_{i}} i_{d} .

…”

Section: Various Control Schemes Of Vscmentioning

confidence: 99%

Power conversion in renewable energy systems: A review advances in wind and PV system

Kumar¹,

Kumar

2016

Int. J. Energy Res.

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“…The modular multilevel converter (MMCΨ has nowadays been widely concerned owing to its significant superiority such as outstanding controllability and output performance, and flexible modularity and scalability [1][2][3]. As one of the primary applications of this kind converter, the MMC-high voltage direct current (HVDCΨ transmission technology exhibits promising prospects in high-power and high-voltage transmission application [4], centralised integration of renewable energy [5] and distribution network interconnection [6].…”

Section: Introductionmentioning

confidence: 99%

Imbalance recovery performance analysis and improvement for MMC‐HVDC systems considering DC current dynamics

Liu

Zhao

Zhu

2020

IET Generation Trans & Dist

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This study presents the imbalance recovery performance analysis of modular multilevel converter high voltage direct current (MMC‐HVDC) systems considering dc current dynamics, and proposes an enhanced control to improve the system's internal stability response. The numerical expressions of the imbalance recovery speed and overshoot amplitude response of dc current components in upper and lower arms of the MMC phase unit are firstly derived analytically, which reveal that the system can be prone to poor imbalance recovery performance after sudden disturbance impacts with no auxiliary control. According to the analysis results, an improved control based on the adaptive virtual resistance method is proposed for the MMC‐HVDC systems to reduce the recovery time regarding different system operating states. The key control parameter design of the adaptive virtual resistance is also simplified since a wider adjustment range of the parameters is allowed in the proposed method. In addition, the dc current components rebalance controller consisting of a low‐pass compensator is proposed to further reduce the overshoot amplitude of system internal response. With the implementation of the proposed control schemes, improved stability recovery performance of MMC‐HVDC systems can be achieved. Simulation results verify the effectiveness of the proposed control.

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“…Neural‐network‐based controllers provide fast dynamic response while maintaining the stability of the converter system over a wide operating range and are considered as a new tool to design control circuits for PQ devices . However, still there is a vast scope for robust controllers in UPQC with objective of PQ . The designed technique should capably make the system stable while working with high efficiency.…”

Section: Introductionmentioning

confidence: 99%

Modelling and investigation of clean power wind energy systems by using UPQC

K¹,

T²

2016

Int. J. Energy Res.

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Summary This article presents a new clean power technique for wind energy system based on Unified Power Quality Conditioner (UPQC) with usage of various Artificial Intelligent techniques (AI). Application of AI techniques such as Artificial Neural Networks, Fuzzy Logic is growing fast in the area of power electronics equipment‐based wind energy system, for instance, UPQC. A novel control scheme is developed by using different AI techniques to mitigate the balancing issues and to control the power–quality problems in UPQC and hence to provide clean power to the grid. The proposed system is composed of shunt active power filter, and the inherent proportional integral (PI) control parameters are tuned with application of PI techniques. A detailed Matlab simulation study is carried out with an application of PI techniques under sag, swell, unbalanced, and harmonic conditions. An exhaustive simulation study is carried out to investigate the application of PI technique‐based controllers and compare its performance with the conventional PI controller with its results explored. Copyright © 2016 John Wiley & Sons, Ltd.

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Application of modular multilevel converter for AGC in an interconnected power system

Cited by 11 publications

References 15 publications

Power conversion in renewable energy systems: A review advances in wind and PV system

Power conversion in renewable energy systems: A review advances in wind and PV system

Imbalance recovery performance analysis and improvement for MMC‐HVDC systems considering DC current dynamics

Modelling and investigation of clean power wind energy systems by using UPQC

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