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Inventions
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Recent Advances and Challenges in Emerging Power Systems: 2nd Edition
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Recent Advances and Challenges in Emerging Power Systems: 2nd Edition

A special issue of Inventions (ISSN 2411-5134). This special issue belongs to the section "Inventions and Innovation in Electrical Engineering/Energy/Communications".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 5183

Special Issue Editor

Prof. Dr. Om P. Malik

E-Mail Website
Guest Editor
Department of Electrical & Computer Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
Interests: digital protection; adaptive control; control of renewable power generation and microgrids; AI applications in power system control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue follows the publication of the first edition of "Recent Advances and Challenges in Emerging Power Systems", consisting of 15 interesting papers.

The continually increasing demand for energy and the pollution caused by the increased generation of electricity using fossil fuels have caused environmental concerns. This has led to the development of renewable energy sources for the generation of electricity and their integration within existing conventional power networks. Differences in the characteristics of the generation of electricity from conventional and renewable energy sources offer challenges, and major restruction in the operation, control, and protection practices of the entire power network is currently taking place to integrate the two in a seamless and efficient manner. It also offers a tremendous opportunity to rejuvenate the practices that have developed over the past 140 years and enhance the entire grid operation, making it more efficient and reliable in light of the newly developed technologies. A large number of investigators in all parts of the world are now working on developing new ideas and schemes from this perspective, and many advances in emerging power systems are being made. The objective of this Special Issue of Inventions is to provide a platform where all researchers can contribute their ideas on the integration of conventional power systems and renewable energy sources for the generation of electricity.

Prof. Dr. Om P. Malik
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. Inventions 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 1800 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

  • renewable energy sources
  • conventional power networks
  • the integration of conventional and renewable generation
  • the operation, control, and protection of power systems

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Related Special Issue

Published Papers (5 papers)

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Research

24 pages, 3192 KiB  
Article
Multi-Objective Optimization Algorithm Based Bidirectional Long Short Term Memory Network Model for Optimum Sizing of Distributed Generators and Shunt Capacitors for Distribution Systems
by Amarendra Alluri, Srinivasa Rao Gampa, Balaji Gutta, Mahesh Babu Basam, Kiran Jasthi, Nibir Baran Roy and Debapriya Das
Inventions 2024, 9(6), 114; https://doi.org/10.3390/inventions9060114 - 12 Nov 2024
Viewed by 484
Abstract
In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution [...] Read more.
In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution systems at any desired load factor. The stochastic traits of evolutionary computing methods necessitate running the algorithm repeatedly to confirm the global optimum. In order to save utility engineers time and effort, this study introduces a BiLSTM network-based machine learning model to directly estimate the optimal values of DGs and SHCs, rather than relying on load flow estimates. At first, a multi-objective grey wolf optimizer determines the most suitable locations and capacities of DGs and SHCs at the unity load factor and the same locations are used to obtain optimum sizing of DGs and SHCs at other load factors also. The base case data sets consisting of substation apparent power, real power load, reactive power load, real power loss, reactive power loss and minimum node voltage at various load factors in per unit values are taken as input training data for the machine learning model. The optimal sizes of the DGs and SHCs for the corresponding load factors obtained using GWO algorithm are taken as target data sets in per unit values for the machine learning model. An adaptive moment estimation (adam) optimization approach is employed to train the BiLSTM ML model for identifying the ideal values of distributed generations and shunt capacitors at different load factors. The efficacy of the proposed ML-based sizing algorithm is demonstrated via simulation studies. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)
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29 pages, 6072 KiB  
Article
Optimized Wavelet Transform for the Development of an Algorithm Designed for the Analysis of Digital Substation Electrical Equipment Parameters
by Alexander S. Efimov, Stanislav A. Eroshenko, Pavel V. Matrenin and Vladislav V. Popovtsev
Inventions 2024, 9(5), 108; https://doi.org/10.3390/inventions9050108 - 29 Sep 2024
Viewed by 692
Abstract
This study emphasizes the urgent need for systems that monitor the operational states of primary electrical equipment, particularly power transformers. The rapid digitalization of and increasing data volumes from substations, coupled with the inability to retrofit outdated equipment with modern sensors, underscore the [...] Read more.
This study emphasizes the urgent need for systems that monitor the operational states of primary electrical equipment, particularly power transformers. The rapid digitalization of and increasing data volumes from substations, coupled with the inability to retrofit outdated equipment with modern sensors, underscore the necessity for algorithms that analyze the operational parameters of digital substations based on key power system metrics such as current and voltage. This research focuses on digital substations with Architecture III and aims to develop an algorithm for processing digital substation data through an appropriate mathematical tool for time-series analysis. For this purpose, the fast discrete wavelet transform was chosen as the most suitable method. Within the framework of the research, possible transformer faults were divided into two categories by the nature of their manifestation. A mathematical model for two internal transformer fault categories was built. The most effective parameters from the point of view of the possibility of identifying an internal fault were selected. The proposed algorithm shows its effectiveness in the compact representation of the signal and compression of the time series of the parameter to be monitored. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)
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22 pages, 8415 KiB  
Article
Technical Requirements of Photovoltaic Inverters for Low Voltage Distribution Networks
by Krzysztof Chmielowiec, Łukasz Topolski, Mateusz Dutka, Aleks Piszczek, Zbigniew Hanzelka and Tomasz Rodziewicz
Inventions 2024, 9(4), 91; https://doi.org/10.3390/inventions9040091 - 16 Aug 2024
Viewed by 896
Abstract
The paper presents the results of an experimental study, which was conducted in 2021 and briefly presented at the conference CIGRE Paris Session 2022, as a part of a joint initiative for comparative studies of PV inverters, of AGH University of Science and [...] Read more.
The paper presents the results of an experimental study, which was conducted in 2021 and briefly presented at the conference CIGRE Paris Session 2022, as a part of a joint initiative for comparative studies of PV inverters, of AGH University of Science and Technology and Tauron Dystrybucja (Polish DSO). The study was performed on a representative sample of 29 brand new PV inverters, widely available for sale in the EU, from over 20 various manufacturers from and outside the EU. For the purposes of this research, all tested PV have been made available by their manufacturers or regional distributors, which confirms the origin of the devices from official distribution channels and their designation for the EU market. The conducted research covers the technical aspects of PV inverters’ operation and performance included in the NC RfG network code, technical standard EN-505049-1:2019, and internal regulations of distribution system operators governing PV inverter technical quality and its cooperation with the low-voltage distribution network. The national regulations may differ between individual EU member states. The paper describes the testing procedure, obtained results, conclusions, and recommendations for regulatory bodies and DSOs. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)
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21 pages, 4216 KiB  
Article
Comparative Economic Analysis of Transmission Lines Adopted for Energy-Saving Conductors Considering Life Cycle Cost
by Lanxin Fan, Heng Chen, Shuyuan Zhao and Yinan Wang
Inventions 2024, 9(4), 75; https://doi.org/10.3390/inventions9040075 - 12 Jul 2024
Viewed by 1313
Abstract
Transmission lines serve as pivotal equipment within the power system. Conductors, the primary medium for power transmission and distribution, directly influence the construction cost, operational performance, and long-term benefits of transmission line projects. This study first provides a detailed introduction to the life [...] Read more.
Transmission lines serve as pivotal equipment within the power system. Conductors, the primary medium for power transmission and distribution, directly influence the construction cost, operational performance, and long-term benefits of transmission line projects. This study first provides a detailed introduction to the life cycle cost of transmission lines. It utilizes linear regression analysis, the grey model, and the autoregressive integrated moving average model to forecast the electricity sales benefit and quantify the carbon reduction benefits of energy-saving conductors through a methodology. Through the life cycle cost model, we found that operating costs, particularly energy loss costs, dominate the total expenses, accounting for 65% to 66.2%. The JLHA3-425 scheme offers the lowest life cycle cost of 22,891.66 k$. Comparing economic indicators like ENPV, EIRR, and DPP confirmed that the JLHA3-425 medium-strength aluminum alloy stranded wire emerged as the most economically viable option among the evaluated schemes, holding substantial promise for fostering economic and environmental sustainability in electrical power transmission. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)
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17 pages, 5750 KiB  
Article
Development of an MPPT-Based Genetic Algorithm for Photovoltaic Systems versus Classical MPPT Techniques in Scenarios with Partial Shading
by Fernando Marcos de Oliveira, Marcelo Henrique Manzke Brandt, Fabiano Salvadori, José Enrique Eirez Izquierdo, Marco Roberto Cavallari and Oswaldo Hideo Ando Junior
Inventions 2024, 9(3), 64; https://doi.org/10.3390/inventions9030064 - 30 May 2024
Cited by 2 | Viewed by 1285
Abstract
Photovoltaic (PV) systems face challenges in achieving maximum energy extraction due to the non-linear nature of their current versus voltage (IxV) characteristics, which are influenced by temperature and solar irradiation. These factors lead to variations in power generation. The situation becomes [...] Read more.
Photovoltaic (PV) systems face challenges in achieving maximum energy extraction due to the non-linear nature of their current versus voltage (IxV) characteristics, which are influenced by temperature and solar irradiation. These factors lead to variations in power generation. The situation becomes even more complex under partial shading conditions, causing distortion in the characteristic curve and creating discrepancies between local and global maximum power points. Achieving the highest output is crucial to enhancing energy efficiency in such systems. However, conventional maximum power point tracking (MPPT) techniques often struggle to locate the global maximum point required to extract the maximum power from the PV system. This study employs genetic algorithms (GAs) to address this issue. The system can efficiently search for the global maximum point using genetic algorithms, maximizing power extraction from the PV arrangements. The proposed approach is compared with the traditional Perturb and Observe (P&O) method through simulations, demonstrating its superior effectiveness in achieving optimal power generation. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 2nd Edition)
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