An Adaptive Power Oscillation Damping Controller for a Hybrid AC/DC Microgrid

Ahmed, Moudud; Vahidnia, Arash; Datta, Manoj; Meegahapola, Lasantha

doi:10.1109/access.2020.2985978

Cited by 20 publications

(8 citation statements)

References 30 publications

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“…The MVDC in DC microgrid application is illustrated in [18], covering AC interfaces, architectures, possible grounding schemes, power quality issues, and communication systems. Furthermore, the MVDC is introduced to improve the power oscillation damping of the DG grid connection, as presented in [12] and [19]. Therefore, to improve the power oscillation of the DG connection, the MVDC grid connection is proposed and investigated in this paper.…”

Section: Figure 1 Schematic Diagram Grid Connection With Mvdc Systemmentioning

confidence: 99%

Power oscillation damping control using PI-neuron network controller for distributed generator grid connection with MVDC

Somsai

Sripanya

Sumpavakup

2022

IJPEDS

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Distributed generator (DG) connection to the system with the DC grid called medium voltage direct current (MVDC) grid connection has received attention and gradually integrated into the distribution grid. The linear controller, such as the PI controller, usually uses the MVDC grid control for power oscillation damping. The PI controller is limited and does not show satisfactory results when the load and parameters of the system itself are changed. This paper proposes the PI with neuron network (NN) as a feed-forward controller (PINNF) to improve the control of the DG grid connection with the MVDC. The proposed PINNF controller is applied to control the power oscillation damping. Since the NN can estimate the proper feed-forward control signals in each situation to the control system, the proposed PINNF controller performs better than the conventional PI controller. The effectiveness of the proposed PINNF controller is validated using nonlinear dynamic simulations on the MATLAB/Simulink program. Four case tests are presented and discussed in this paper. Results indicate the improvement of power oscillation damping stability and performance in the MVDC grid connection with the proposed PINNF controller.

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Section: Figure 1 Schematic Diagram Grid Connection With Mvdc Systemmentioning

confidence: 99%

Power oscillation damping control using PI-neuron network controller for distributed generator grid connection with MVDC

Somsai

Sripanya

Sumpavakup

2022

IJPEDS

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“…Small-signal stability analysis is an important technique to identify the dynamics of the AC microgrid. AC microgrids are usually comprised of VSC based DERs with active/reactive power controllers for parallel operation, dynamic loads (motor loads), passive loads, and resistive or inductive lines [130]- [132]. Extensive research studies have been carried out on small-signal analysis, voltage, and transient stability of AC microgrid to identify the dynamics of each parameter, such as controller dynamics, load dynamics, and system dynamics.…”

Section: Stability Studies Of Ac Microgridmentioning

confidence: 99%

“…In power system dynamic stability studies, the aggregated model of IMs has been considered, which does not reflect the true dynamics of IMs. Authors previous work investigated the LFO characteristics of the multiple parallel operating small IMs and a large IM of equivalent power rating [132], [274]. It was found that the multiple parallel operating IMs have multiple dominant oscillation frequencies which introduces more non-linearity into system dynamics.…”

Section: E Dynamic Performance With P − F and Q − V Droop Schemes And Dynamic Loadsmentioning

confidence: 99%

Stability and Control Aspects of Microgrid Architectures–A Comprehensive Review

et al. 2020

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Self-governing small regions of power systems, known as "microgrids", are enabling the integration of small-scale renewable energy sources (RESs) while improving the reliability and energy efficiency of the electricity network. Microgrids can be primarily classified into three types based on their voltage characteristics and system architecture; 1) AC microgrids, 2) DC microgrids, and 3) Hybrid AC/DC microgrids. This paper presents a comprehensive review of stability, control, power management and fault ride-through (FRT) strategies for the AC, DC, and hybrid AC/DC microgrids. This paper also classifies microgrids in terms of their intended application and summarises the operation requirements stipulated in standards (e.g., IEEE Std. 1547. The control strategies for each microgrid architecture are reviewed in terms of their operating principle and performance. In terms of the hybrid AC/DC microgrids, specific control aspects, such as mode transition and coordinated control between multiple interlinking converters (ILCs) and energy storage system (ESS) are analysed. A case study is also presented on the dynamic performance of a hybrid AC/DC microgrid under different control strategies and dynamic loads. Hybrid AC/DC microgrids shown to have more advantages in terms of economy and efficiency compared with the other microgrid architectures. This review shows that hierarchical control schemes, such as primary, secondary, and tertiary control are very popular among all three microgrid types. It is shown that the hybrid AC/DC microgrids require more complex control strategies for power management and control compared to AC or DC microgrids due to their dependency on the ILC controls and the operation mode of the hybrid AC/DC microgrid. Case study illustrated the significant effects of microgrid feeder characteristics on the dynamic performance of the hybrid AC/DC microgrid. It is also revealed that any transient conditions either in the AC or DC microgrids could propagate through the ILC affecting the entire microgrid dynamic performance. Additionally, the critical control issues and the future research challenges of microgrids are also discussed in this paper.INDEX TERMS Energy storage system (ESS), hybrid AC/DC microgrid, IEEE Std. 1547-2018, interlinking converter (ILC), microgrid stability, power management, renewable energy sources (RESs).

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“…In this regard, in [46], using a neuro-fuzzy controller is proposed a Home Energy Management System (HEMS) to carry out day ahead management and real-time regulation; according to the inputs and outputs, this approach is considered a MIMO application. Another work can be seen in [47], where it is developed an adaptive neuro-fuzzy system based on Power Oscillation Damping (POD) controller to damp Low-Frequency Oscillations (LFOs) in hybrid AC/DC microgrids. Finally, in [48] an adaptive neuro-fuzzy control power is proposed to regulate the voltage in a distribution network when there is a variation in the load.…”

Section: ) Energy Microgridsmentioning

confidence: 99%

Control of a MIMO Coupled Plant Using a Neuro-Fuzzy Adaptive System Based on Boolean Relations

2021

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This document describes the implementation of a neuro-fuzzy adaptive system MIMO (Multiple Input Multiple Output), using two neuro-fuzzy MIMO systems: one for control and the other for identifying the plant. Under this approach, the controller is optimized, employing the model obtained during the identification of the plant that utilizes data generated from the controller's operation. In this way, the plant identification and the controller optimization is performed iteratively. The application case consists of controlling a MIMO non-linear hydraulic system fed by a pump and a three-way valve. In order to observe the controller performance various experimental configurations are considered.

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An Adaptive Power Oscillation Damping Controller for a Hybrid AC/DC Microgrid

Cited by 20 publications

References 30 publications

Power oscillation damping control using PI-neuron network controller for distributed generator grid connection with MVDC

Power oscillation damping control using PI-neuron network controller for distributed generator grid connection with MVDC

Stability and Control Aspects of Microgrid Architectures–A Comprehensive Review

Control of a MIMO Coupled Plant Using a Neuro-Fuzzy Adaptive System Based on Boolean Relations

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