Comparison of Fuzzy and ANFIS Controllers for Asymmetrical 31-Level Cascaded Inverter With Super Imposed Carrier PWM Technique

Muralikumar, K.; Ponnambalam, P.

doi:10.1109/access.2021.3086674

Cited by 17 publications

(4 citation statements)

References 42 publications

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“…To synchronize with the initial frequency of the grid, the node uses a phase-locked loop (PLL). The inverter receives and controls voltage from the controller via a pulse width modulation (PWM) block (Muralikumar and Ponnambalam, 2021). Figure 7 describes the inverter control scheme based on ANFIS (FLC).…”

Section: Frontiers In Energy Researchmentioning

confidence: 99%

Administration strategy of energy management in smart grid: system view and optimization path

Liu,

Wang,

Wei

2023

Front. Energy Res.

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Power generation and transmission infrastructure is vulnerable to the interaction of various Distributed Generations (DG), which leads to the imbalance of power system operation, frequent voltage drops or spikes, and even power outages. This phenomenon not only wastes energy, but also affects grid security. The main reason is a delayed feedback of circuit failure and load changes, and the optimization of energy management system and path is an effective way to solve the above problems. In this paper, a method of multi-objective optimization based on ANFIS algorithm is proposed which can help to improve the demand response, energy storage and management of smart power grid, reduce the volatility of DGs, reducing electricity costs and improving energy efficiency. Firstly, based on the ANFIS algorithm, the distributed power generation control mode, inverter control, real-time electricity price calculation method, energy transfer and storage scheme are improved, and the optimization path of the energy management system is defined. Secondly, the advantages of ANFIS algorithm in response speed and running stability are verified by comparing with other algorithms. Finally, a distributed energy microgrid is constructed for simulation verification. The results show that :(1) ANFIS optimization algorithm has good adaptability in smart grid, and has advantages in large amount of data processing and information transmission; (2) The verification model based on ANFIS has strong elasticity and efficient response speed. The research results will help solve various problems in the smart grid, including establishing a clear energy management system path, maintaining the stable operation of the power system, providing users with more reasonable power plans and the lowest cost of electricity.

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Section: Frontiers In Energy Researchmentioning

confidence: 99%

Administration strategy of energy management in smart grid: system view and optimization path

Liu,

Wang,

Wei

2023

Front. Energy Res.

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“…To address these issues, Artificial Intelligence (AI) techniques such as FLC or Neural Networks (NN) are used to control the switching operation of the converter. However, NN based control approach is computationally intensive and suffers from control complexity, especially in PV applications [19,20]. In order to address the aforesaid issues in the existing literature, this research paper proposes a Cascaded Fuzzy Logic Control (CFLC) to enhance the operation of a high-gain LUO converter and to effectively enhance the DC link voltage of the DC microgrid system.…”

Section: Introductionmentioning

confidence: 99%

DC Link Voltage Enhancement in DC Microgrid Using PV Based High Gain Converter with Cascaded Fuzzy Logic Controller

et al. 2023

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Renewable-based sources can be interconnected through power electronic converters and connected with local loads and energy storage devices to form a microgrid. Nowadays, DC microgrids are gaining more popularity due to their higher efficiency and reliability as compared to AC microgrid systems. The DC Microgrid has power electronics converters between the DC loads and renewable-based energy sources. The power converters controlled with an efficient control algorithm for maintaining stable DC bus voltage in DC microgrids under various operating modes is a challenging task for researchers. With an aim to address the above-mentioned issues, this study focuses on the DC link voltage enhancement of a DC Microgrid system consisting of PV, DFIG-based wind energy conversion system (WECS), and battery Energy Storage System (ESS). To elevate PV output voltage and minimize the oscillations in DC link voltage, a high-gain Luo converter with Cascaded Fuzzy Logic Controller (CFLC) is proposed. Droop control with virtual inertia and damping control is proposed for DFIG-based WECS to provide inertia support. Artificial Neural Network (ANN) based droop control is utilised to regulate the ESS’s State of Charge (SOC). The effectiveness of the proposed converter and its control algorithms for maintaining stable DC bus link voltage has been analysed using MATLAB/Simulink and experimentally validated using a prototype model and FPGA Spartan 6E controllers.

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“…A modified cascaded 31-level inverter is investigated with respect to reduced dc input, less switches etc. by the authors in [15], the presented topology is controlled by SIC-PWM to minimize the THD content. A novel topology of single-phase multilevel inverter is presented by the authors in [16] generates 31level of load voltage.…”

Section: Introductionmentioning

confidence: 99%

Cascaded Three-Phase Multilevel Inverter with Minimal Components for Power System Applications

Tackie,

Ozerdem,

Mohammed

et al. 2023

Preprint

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This paper proposes a new cascaded three-phase multilevel inverter based on a cascaded submultilevel and single-phase H-bridge structure. The voltage source of the traditional single-phase H-bridge is replaced with the proposed cascaded submultilevel. Cascading two basic units forms the submultilevel unit. The basic and submultilevel units generate positive voltage only hence the need for an H-bridge to generate both polarities of load voltage. Five algorithms of source voltage are proposed and the optimal algorithm selected to generate the peak load voltage and output levels. The proposed three-phase cascaded multilevel inverter generates 31-level of load voltage. The per-phase component distribution of the proffered inverter are twelve power switches, four dc sources and twelve driver circuits accordingly. Principal merits of the proposed 31-level inverter are high quality load waveforms, production of high levels of load voltage utilizing reduced component quantity, simple cascaded layout, decreased inverter area, minimal inverter cost, minimum inverter losses and utilizing lower rated switches. Also, the proposed topology is highly suited for employment in PV-DVR and other power systems. To validate these advantages of the proposed multilevel inverter, contrastive analysis of the proposed inverter and existing topologies are studied. Finally, the functionality of the proposed inverter is substantiated by simulation in PSCAD/ EMTDC software.

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Comparison of Fuzzy and ANFIS Controllers for Asymmetrical 31-Level Cascaded Inverter With Super Imposed Carrier PWM Technique

Cited by 17 publications

References 42 publications

Administration strategy of energy management in smart grid: system view and optimization path

Administration strategy of energy management in smart grid: system view and optimization path

DC Link Voltage Enhancement in DC Microgrid Using PV Based High Gain Converter with Cascaded Fuzzy Logic Controller

Cascaded Three-Phase Multilevel Inverter with Minimal Components for Power System Applications

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