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Advanced Control, Optimization, Stability and Reliability of Microgrids and Power...
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Advanced Control, Optimization, Stability and Reliability of Microgrids and Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 1955

Special Issue Editor

Dr. Muhammad Akmal

E-Mail Website
Guest Editor
Electrical, Electronic and Future Technologies Subject Group, Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield S1 1WB, UK
Interests: renewable energy integration into power systems; microgrids; smart grids; power system operation and stability analysis

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the stability and reliability of advanced control of microgrids and power systems. Microgrids are local electricity distribution systems that can operate independently or in conjunction with the main power grid. The integration of renewable energy sources, such as solar and wind, into microgrids poses challenges in terms of control, optimization, stability, and reliability. This Special Issue emphasises recent advances in these areas and provides a platform for researchers and practitioners to share knowledge and discuss the latest developments. It aims to delve into various aspects of microgrids and power systems to address the evolving challenges and opportunities in the energy sector.

This Special Issue invites submissions that investigate advanced control strategies, emphasizing the need for efficient and adaptable control systems in microgrids.

The topics of interest include, but are not limited to, the following:

  • Advanced control of AC and DC microgrids;
  • Grid interaction studies for all types of microgrids;
  • Optimization techniques to enhance the performance of microgrids and power systems;
  • Energy efficiency, cost-effectiveness, and environmental impact of microgrids and power systems;
  • Stability of microgrids and power systems under significant penetration;
  • Reliability studies in relation to microgrids and power systems;
  • Methods to enhance the stability of microgrids;
  • Strategies to ensure the reliable operation of microgrids and power systems, even under adverse conditions or cyber threats.

This Special Issue aims to serves as a comprehensive resource for academics, engineers, and policymakers interested in the sustainable development and improved performance of microgrids and power systems.

Dr. Muhammad Akmal
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microgrids
  • power systems
  • control of microgrids
  • optimization in microgrids
  • stability of microgrids
  • reliability of microgrids and power systems
  • integrating renewable energy sources

Published Papers (3 papers)

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Research

29 pages, 29232 KiB  
Article
Current Compensation Method in a Distribution System Based on a Four-Leg Inverter under Unbalanced Load Conditions Using an Artificial Neural Network
by Tae-Gyu Kim, Chang-Gyun An, Junsin Yi and Chung-Yuen Won
Energies 2024, 17(6), 1325; https://doi.org/10.3390/en17061325 - 10 Mar 2024
Viewed by 461
Abstract
This study proposes an unbalanced current compensation method based on a four-leg inverter using an artificial neural network (ANN) under unbalanced load conditions. Distribution systems exhibit rapid load variations, and conventional filter-based control methods suffer from the drawback of requiring an extended time [...] Read more.
This study proposes an unbalanced current compensation method based on a four-leg inverter using an artificial neural network (ANN) under unbalanced load conditions. Distribution systems exhibit rapid load variations, and conventional filter-based control methods suffer from the drawback of requiring an extended time period to reach a steady state. To address this problem, an ANN is applied to calculate the unbalanced current reference and enhance dynamic performance. Additionally, because of the periodic incorrect output inherent in the ANN, applying it to a proportional–integral controller would result in an error being directly reflected in the current reference. In the aforementioned problem, an ANN is applied to the dq0 coordinate system current controller to compensate for the periodic incorrect output in the current reference calculation. The proposed ANN-based unbalanced current compensation method is validated through PSIM simulations and experiments. Full article
(This article belongs to the Special Issue Advanced Control, Optimization, Stability and Reliability of Microgrids and Power Systems)
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26 pages, 1577 KiB  
Article
Multivariable Algorithm Using Signal-Processing Techniques to Identify Islanding Events in Utility Grid with Renewable Energy Penetration
by Ming Li, Anqing Chen, Peixiong Liu, Wenbo Ren and Chenghao Zheng
Energies 2024, 17(4), 877; https://doi.org/10.3390/en17040877 - 14 Feb 2024
Viewed by 528
Abstract
This paper designs a multi-variable hybrid islanding-detection method (HIDM) using signal-processing techniques. The signals of current captured on a test system where the renewable energy (RE) penetration level is between 50% and 100% are processed by the application of the Stockwell transform (ST) [...] Read more.
This paper designs a multi-variable hybrid islanding-detection method (HIDM) using signal-processing techniques. The signals of current captured on a test system where the renewable energy (RE) penetration level is between 50% and 100% are processed by the application of the Stockwell transform (ST) to compute the Stockwell islanding-detection factor (SIDF) and the co-variance islanding-detection factor (CIDF). The signals of current are processed by the application of the Hilbert transform (HT), and the Hilbert islanding-detection factor (HIDF) is computed. The signals of current are also processed by the application of the Alienation Coefficient (ALC), and the Alienation Islanding Detection Factor (AIDF) is computed. A hybrid islanding-detection indicator (HIDI) is derived by multiplying the SIDF, CIDF, AIDF, and an islanding weight factor (IWF) element by element. Two thresholds, designated as the hybrid islanding-detection indicator threshold (HIDIT) and the hybrid islanding-detection indicator fault threshold (HIDIFT), are selected to detect events of islanding and also to discriminate such events from fault events and operational events. The HIDM is effectively tested using an IEEE-13 bus power network, where solar generation plants (SGPs) and wind generation plants (WGPs) are integrated. The HIDM effectively identified and discriminated against events such as islanding, faults, and operational. The HIDM is also effective at identifying islanding events on a real-time distribution feeder. The HIDM is also effective at detecting islanding events in the scenario of a 20 dB signal-to-noise ratio (SNR). It is established that the HIDM has a small non-detection zone (NDZ). The effectiveness of the HIDM is better relative to the islanding-detection method (IDM) supported by the discrete wavelet transform (DWT), an IDM using a hybridization of the slantlet transform, and the Ridgelet probabilistic neural network (RPNN). An IDM using wavelet transform multi-resolution (WT-MRA)-based image data and an IDM based on the use of a deep neural network (DNN) were used. The study was performed using the MATLAB software (2017a) and validated in real-time using the data collected from a practical distribution power system network. Full article
(This article belongs to the Special Issue Advanced Control, Optimization, Stability and Reliability of Microgrids and Power Systems)
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16 pages, 5940 KiB  
Article
A Novel Refined Regulation Method with Modified Genetic Commutation Algorithm to Reduce Three-Phase Imbalanced Ratio in Low-Voltage Distribution Networks
by Dazhao Liu, Zhe Liu, Ti Wang, Zhiguang Xie, Tingting He, Aixin Dai and Zhiqiang Chen
Energies 2023, 16(23), 7838; https://doi.org/10.3390/en16237838 - 29 Nov 2023
Viewed by 595
Abstract
The three-phase imbalance in low-voltage distribution networks (LVDNs) seriously threatens the security and stability of the power system. At present, a standard solution is automatic phase commutation, but this method has limitations because it does not address the branch imbalance and premature convergence [...] Read more.
The three-phase imbalance in low-voltage distribution networks (LVDNs) seriously threatens the security and stability of the power system. At present, a standard solution is automatic phase commutation, but this method has limitations because it does not address the branch imbalance and premature convergence or instability of the commutation algorithm. Therefore, this paper proposes a novel refined regulation commutation system, combined with a modified optimized commutation algorithm, and designs a model and simulation for feasibility verification. The refined regulatory model incorporates branch control units into the traditional commutation system. This effectively disperses the main controller’s functions to each branch and collaborates with intelligent fusion terminals for precise adjustment. The commutation algorithm designed in this paper, combined with the above model, adopts strategies such as symbol encoding, cubic chaotic mapping, and adaptive adjustment based on traditional genetic algorithms. In addition, in order to verify the effectiveness of the proposed method, this paper establishes a mathematical model with the minimum three-phase imbalance and commutation frequency as objectives and establishes a simulation model. The results of the simulation demonstrate that this method can successfully lower the three-phase imbalance of the low-voltage distribution network. It leads to a decrease of the main circuit’s three-phase load imbalance rate from 27% to 6% and reduces each branch line’s three-phase imbalance ratio to below 10%. After applying the method proposed in this paper, the main and branches circuit three-phase imbalance are both lower than the limit ratio of the LVDNs, which can improve the quality and safety of electricity consumption. Additionally, the results also prove that the commutation algorithm under this method has faster convergence speed, better application effect, and better stability, which has promotion and application value. Full article
(This article belongs to the Special Issue Advanced Control, Optimization, Stability and Reliability of Microgrids and Power Systems)
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