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Symmetry
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Symmetry in Renewable Energy and Power Systems Ⅱ - Including...
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Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 23440

Special Issue Editors

Dr. Raúl Baños Navarro

E-Mail Website
Guest Editor
Department of Engineering, Electrical Engineering section, University of Almería, E-04120 Almería, Spain
Interests: energy economics; renewable energy; power meters; network analysis; engineering optimization
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alfredo Alcayde

E-Mail Website
Guest Editor
Department of Engineering, Universidad de Almería, La Cañada de San Urbano s/n, 04120 Almería, Spain
Interests: power engineering; optimization techniques; ICT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The study of power systems is closely related with symmetry. For example, multiphase power systems are inherently symmetric. The study of symmetrical and asymmetrical faults in power systems is a critical issue. The phase sequence arrangements of multicircuit overhead lines on the same tower directly affect the symmetry of power transmission systems, which influences the operation of the power grid and relay protection. Moreover, symmetry is a topic of intensive investigation in the analysis of grid interconnection, including symmetrical and asymmetrical network parameters in smart-grid infrastructures. In renewable energy, the symmetry is present in the layout of wind power plants or photovoltaic plants, among others, while solar systems can have a different performance if they are used with symmetric and asymmetric concentrating CPC collectors.

This Special Issue invites researchers to submit original research papers and review articles related to renewable energy and power systems in which theoretical or practical issues of symmetry are considered. Applied case studies are especially welcome. The topics of interest include, but are not limited to:

  • Symmetry in the topology of power grids;
  • Symmetry in multiphase/polyphase power systems. Power network synchronization;
  • Symmetric and asymmetric components;
  • Symmetrical and asymmetrical faults in power systems;
  • Symmetry analysis of phase sequence arrangements of multicircuit overhead lines;
  • Symmetry studies of electrical signals using signal processing methods (FFT, DFT, STFT, WT, etc.);
  • Symmetry in power electronics devices and renewable energy components;
  • Symmetry in renewable energy systems (including smart grids and microgrids);
  • Symmetrical analysis of power plant layouts and location (including wind farms and photovoltaic plants);
  • Algorithms for studying symmetry in renewable energy and power systems. 

Dr. Raúl Baños Navarro
Dr. Alfredo Alcayde
Guest Editors

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. Symmetry is an international peer-reviewed open access monthly 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 2400 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

  • symmetry
  • power systems
  • renewable energy systems
  • topology
  • smart-grids

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Published Papers (7 papers)

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Research

13 pages, 1863 KiB  
Article
Short-Term Energy Forecasting Using Machine-Learning-Based Ensemble Voting Regression
by Pyae-Pyae Phyo, Yung-Cheol Byun and Namje Park
Symmetry 2022, 14(1), 160; https://doi.org/10.3390/sym14010160 - 14 Jan 2022
Cited by 43 | Viewed by 4726
Abstract
Meeting the required amount of energy between supply and demand is indispensable for energy manufacturers. Accordingly, electric industries have paid attention to short-term energy forecasting to assist their management system. This paper firstly compares multiple machine learning (ML) regressors during the training process. [...] Read more.
Meeting the required amount of energy between supply and demand is indispensable for energy manufacturers. Accordingly, electric industries have paid attention to short-term energy forecasting to assist their management system. This paper firstly compares multiple machine learning (ML) regressors during the training process. Five best ML algorithms, such as extra trees regressor (ETR), random forest regressor (RFR), light gradient boosting machine (LGBM), gradient boosting regressor (GBR), and K neighbors regressor (KNN) are trained to build our proposed voting regressor (VR) model. Final predictions are performed using the proposed ensemble VR and compared with five selected ML benchmark models. Statistical autoregressive moving average (ARIMA) is also compared with the proposed model to reveal results. For the experiments, usage energy and weather data are gathered from four regions of Jeju Island. Error measurements, including mean absolute percentage error (MAPE), mean absolute error (MAE), and mean squared error (MSE) are computed to evaluate the forecasting performance. Our proposed model outperforms six baseline models in terms of the result comparison, giving a minimum MAPE of 0.845% on the whole test set. This improved performance shows that our approach is promising for symmetrical forecasting using time series energy data in the power system sector. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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15 pages, 1779 KiB  
Article
Hybrid Ensemble Deep Learning-Based Approach for Time Series Energy Prediction
by Pyae Pyae Phyo and Yung-Cheol Byun
Symmetry 2021, 13(10), 1942; https://doi.org/10.3390/sym13101942 - 15 Oct 2021
Cited by 21 | Viewed by 3939
Abstract
The energy manufacturers are required to produce an accurate amount of energy by meeting the energy requirements at the end-user side. Consequently, energy prediction becomes an essential role in the electric industrial zone. In this paper, we propose the hybrid ensemble deep learning [...] Read more.
The energy manufacturers are required to produce an accurate amount of energy by meeting the energy requirements at the end-user side. Consequently, energy prediction becomes an essential role in the electric industrial zone. In this paper, we propose the hybrid ensemble deep learning model, which combines multilayer perceptron (MLP), convolutional neural network (CNN), long short-term memory (LSTM), and hybrid CNN-LSTM to improve the forecasting performance. These DL architectures are more popular and better than other machine learning (ML) models for time series electrical load prediction. Therefore, hourly-based energy data are collected from Jeju Island, South Korea, and applied for forecasting. We considered external features associated with meteorological conditions affecting energy. Two-year training and one-year testing data are preprocessed and arranged to reform the times series, which are then trained in each DL model. The forecasting results of the proposed ensemble model are evaluated by using mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Error metrics are compared with DL stand-alone models such as MLP, CNN, LSTM, and CNN-LSTM. Our ensemble model provides better performance than other forecasting models, providing minimum MAPE at 0.75%, and was proven to be inherently symmetric for forecasting time-series energy and demand data, which is of utmost concern to the power system sector. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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20 pages, 3298 KiB  
Article
Optimal Scheduling of Microgrid Considering the Interruptible Load Shifting Based on Improved Biogeography-Based Optimization Algorithm
by Bo Li, Hongsheng Deng and Jue Wang
Symmetry 2021, 13(9), 1707; https://doi.org/10.3390/sym13091707 - 15 Sep 2021
Cited by 8 | Viewed by 1710
Abstract
A microgrid is an efficient method of uniting distributed generations. To ensure the applicability and symmetry of the microgrid, the environmental benefits and economic costs are considered to comprehensively model the optimal operation of the microgrid under the grid-connected operation mode, at the [...] Read more.
A microgrid is an efficient method of uniting distributed generations. To ensure the applicability and symmetry of the microgrid, the environmental benefits and economic costs are considered to comprehensively model the optimal operation of the microgrid under the grid-connected operation mode, at the same time, considering the effect of interruptible load on the operating cost of the microgrid, the power shifting for interruptible load is attempted on the basis of battery storage capacity. By adaptively adjusting the migration rate using the habitat suitability index of a normalized individual and adding a certain differential perturbation to the migration operator of the migration mechanism, an improved biogeography-based optimization algorithm is proposed and the microgrid optimization dispatching algorithm based on the improved biogeography-based optimization is applied. The advancement and effectiveness of the proposed algorithm and model is verified by the example, and the simulation results indicate that the implementation of the power dispatching scheme proposed in this paper can effectively reduce the total cost of the system. Moreover, the proper consideration of shifting interruptible load, the effective load management and guiding the electricity consumption behavior of users are of certain significance for optimizing the utilization of renewable energy and improving the system efficiency and economy. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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15 pages, 5347 KiB  
Article
Machine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messages
by Taha Selim Ustun, S. M. Suhail Hussain, Ahsen Ulutas, Ahmet Onen, Muhammad M. Roomi and Daisuke Mashima
Symmetry 2021, 13(5), 826; https://doi.org/10.3390/sym13050826 - 8 May 2021
Cited by 38 | Viewed by 4274
Abstract
Increased connectivity is required to implement novel coordination and control schemes. IEC 61850-based communication solutions have become popular due to many reasons—object-oriented modeling capability, interoperable connectivity and strong communication protocols, to name a few. However, communication infrastructure is not well-equipped with cybersecurity mechanisms [...] Read more.
Increased connectivity is required to implement novel coordination and control schemes. IEC 61850-based communication solutions have become popular due to many reasons—object-oriented modeling capability, interoperable connectivity and strong communication protocols, to name a few. However, communication infrastructure is not well-equipped with cybersecurity mechanisms for secure operation. Unlike online banking systems that have been running such security systems for decades, smart grid cybersecurity is an emerging field. To achieve security at all levels, operational technology-based security is also needed. To address this need, this paper develops an intrusion detection system for smart grids utilizing IEC 61850’s Generic Object-Oriented Substation Event (GOOSE) messages. The system is developed with machine learning and is able to monitor the communication traffic of a given power system and distinguish normal events from abnormal ones, i.e., attacks. The designed system is implemented and tested with a realistic IEC 61850 GOOSE message dataset under symmetric and asymmetric fault conditions in the power system. The results show that the proposed system can successfully distinguish normal power system events from cyberattacks with high accuracy. This ensures that smart grids have intrusion detection in addition to cybersecurity features attached to exchanged messages. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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27 pages, 9248 KiB  
Article
Soft-Switching Full-Bridge Converter with Multiple-Input Sources for DC Distribution Applications
by Sheng-Yu Tseng and Jun-Hao Fan
Symmetry 2021, 13(5), 775; https://doi.org/10.3390/sym13050775 - 29 Apr 2021
Cited by 6 | Viewed by 2793
Abstract
Due to the advantages of power supply systems using the DC distribution method, such as a conversion efficiency increase of about 5–10%, a cost reduction of about 15–20%, etc., AC power distribution systems will be replaced by DC power distribution systems in the [...] Read more.
Due to the advantages of power supply systems using the DC distribution method, such as a conversion efficiency increase of about 5–10%, a cost reduction of about 15–20%, etc., AC power distribution systems will be replaced by DC power distribution systems in the future. This paper adopts different converters to generate DC distribution system: DC/DC converter with PV arrays, power factor correction with utility line and full-bridge converter with multiple input sources. With this approach, the proposed full-bridge converter with soft-switching features for generating a desired voltage level in order to transfer energy to the proposed DC distribution system. In addition, the proposed soft-switching full-bridge converter is used to generate the DC voltage and is applied to balance power between the PV arrays and the utility line. Due to soft-switching features, the proposed full-bridge converter can be operated with zero-voltage switching (ZVS) at the turn-on transition to increase conversion efficiency. Finally, a prototype of the proposed full-bridge converter under an input voltage of DC 48 V, an output voltage of 24 V, a maximum output current of 21 A and a maximum output power of 500 W was implemented to prove its feasibility. From experimental results, it can be found that its maximum conversion efficiency is 92% under 50% of full-load conditions. It was shown to be suitable for DC distribution applications. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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14 pages, 915 KiB  
Article
Modelling of Consumption Shares for Small Wind Energy Prosumers
by Andres Annuk, Wahiba Yaïci, Andrei Blinov, Maido Märss, Sergei Trashchenkov and Peep Miidla
Symmetry 2021, 13(4), 647; https://doi.org/10.3390/sym13040647 - 11 Apr 2021
Cited by 4 | Viewed by 1990
Abstract
This article describes a simulation of energy distribution in an average household where electricity is produced with a small wind generator or purchased from the public electricity grid. Numerical experiments conducted within an average of five minutes were performed using annual production and [...] Read more.
This article describes a simulation of energy distribution in an average household where electricity is produced with a small wind generator or purchased from the public electricity grid. Numerical experiments conducted within an average of five minutes were performed using annual production and consumption graphs. Virtual storage devices, a water tank and a battery were used to buffer energy inside the household. The energy required for non-shiftable consumption and hot water consumption were taken directly from the utility grid. Surplus energy remaining from wind generator production after providing for consumption and storage needs were redirected there. A cover factor was used as a measure of the efficiency of energy distribution. One of the aims of the article was to determine by simulations the change of the cover factor in a virtually designed situation where the expected energy output of the wind generator was known in advance over one to three hours. The results found that for the configuration of the proposed nanogrid option, the positive results were readily achieved when the expected wind generator production was known an hour ahead. Then, the cover factor increased from 0.593 to 0.645. The side result of using projected/expected production is an increase in asymmetrical energy exchanges bilaterally between nanogrid and utility grid in favour of grid sales. Another finding was that the cover factor depended on the wind generator’s production intensity but less on the intensity of consumption within the household.It is hoped/expected that future research will address the prediction of output using mathematical methods. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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25 pages, 1358 KiB  
Article
Small-Signal Stability of Multi-Converter Infeed Power Grids with Symmetry
by Jiawei Yu, Ziqian Yang, Jurgen Kurths and Meng Zhan
Symmetry 2021, 13(2), 157; https://doi.org/10.3390/sym13020157 - 20 Jan 2021
Cited by 11 | Viewed by 2206
Abstract
Traditional power systems have been gradually shifting to power-electronic-based ones, with more power electronic devices (including converters) incorporated recently. Faced with much more complicated dynamics, it is a great challenge to uncover its physical mechanisms for system stability and/or instability (oscillation). In this [...] Read more.
Traditional power systems have been gradually shifting to power-electronic-based ones, with more power electronic devices (including converters) incorporated recently. Faced with much more complicated dynamics, it is a great challenge to uncover its physical mechanisms for system stability and/or instability (oscillation). In this paper, we first establish a nonlinear model of a multi-converter power system within the DC-link voltage timescale, from the first principle. Then, we obtain a linearized model with the associated characteristic matrix, whose eigenvalues determine the system stability, and finally get independent subsystems by using symmetry approximation conditions under the assumptions that all converters’ parameters and their susceptance to the infinite bus (Bg) are identical. Based on these mathematical analyses, we find that the whole system can be decomposed into several equivalent single-converter systems and its small-signal stability is solely determined by a simple converter system connected to an infinite bus under the same susceptance Bg. These results of large-scale multi-converter analysis help to understand the power-electronic-based power system dynamics, such as renewable energy integration. As well, they are expected to stimulate broad interests among researchers in the fields of network dynamics theory and applications. Full article
(This article belongs to the Special Issue Symmetry in Renewable Energy and Power Systems Ⅱ - Including Wind Energy and Fluid Energy)
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