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Power System Dynamics, Operation, and Control including Renewable Energy Systems...
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Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 11975

Special Issue Editors

Dr. Hany M. Hasanien

E-Mail Website
Guest Editor
Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Interests: power system dynamics and control; energy storage systems; renewable energy; smart grids
Dr. Shady H. E. Abdel Aleem

E-Mail Website
Guest Editor
Department of Electrical Engineering, Valley Higher Institute of Engineering and Technology, Science Valley Academy, Qalyubia 44971, Egypt
Interests: power quality; optimization; renewable energy; smart grids
Special Issues, Collections and Topics in MDPI journals
Dr. Calasan Martin

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro
Interests: renewable energies; power generation; electric storage devices; electric machines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The increasing trend of renewable energy use and energy storage technologies has led to the emergence of new practices in modern power systems. These new practices necessitate the strengthening of conventional energy systems to be dynamic smart networks that can communicate, store data, and make decisions to allow today’s energy industry to switch to modern smart networks while expanding the use of clean renewables along with conventional resources. Accordingly, efficient procedures are needed to address these issues effectively at the academic and industrial levels. Further, new solutions must be sought to enable networks to deal with these developments to achieve flexible energy networks that can host high renewable energy penetration while maintaining acceptable levels of reliability and energy quality in a cost-effective manner.

Hence, in this Special Issue, we are calling for original contributions that cover emerging challenges in power system dynamics, operation, and control, including renewable energy systems and smart grid technology and applications in modern power systems. It will be our pleasure to provide a platform to bring together university scientists, researchers, and leading researchers to share their thoughts, ideas, experiences, and research results on all aspects of smart networks.

Prof. Dr. Hany M. Hasanien
Dr. Shady H. E. Abdel Aleem
Dr. Calasan Martin
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. Electronics 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 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

  • decision making
  • energy storage
  • power quality
  • power system dynamics
  • power system operation and control
  • renewable energy systems
  • reliability
  • smart grid
  • sustainability
  • optimization
  • uncertainty
  • future trends
  • case studies

Published Papers (5 papers)

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Research

17 pages, 3049 KiB  
Article
An Event Matching Energy Disaggregation Algorithm Using Smart Meter Data
by Rehan Liaqat and Intisar Ali Sajjad
Electronics 2022, 11(21), 3596; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11213596 - 03 Nov 2022
Cited by 6 | Viewed by 1498
Abstract
Energy disaggregation algorithms disintegrate aggregate demand into appliance-level demands. Among various energy disaggregation approaches, non-intrusive load monitoring (NILM) algorithms requiring a single sensor have gained much attention in recent years. Various machine learning and optimization-based NILM approaches are available in the literature, but [...] Read more.
Energy disaggregation algorithms disintegrate aggregate demand into appliance-level demands. Among various energy disaggregation approaches, non-intrusive load monitoring (NILM) algorithms requiring a single sensor have gained much attention in recent years. Various machine learning and optimization-based NILM approaches are available in the literature, but bulk training data and high computational time are their respective drawbacks. Considering these drawbacks, we devised an event matching energy disaggregation algorithm (EMEDA) for NILM of multistate household appliances using smart meter data. Having limited training data, K-means clustering was employed to estimate appliance power states. These power states were accumulated to generate an event database (EVD) containing all combinations of appliance operations in their various states. Prior to matching, the test samples of aggregate demand events were decreased by event-driven data compression for computational effectiveness. The compressed test events were matched in the sorted EVD to assess the contribution of each appliance in the aggregate demand. To counter the effects of transient spikes and/or dips that occurred during the state transition of appliances, a post-processing algorithm was also developed. The proposed approach was validated using the low-rate data of the Reference Energy Disaggregation Dataset (REDD). With better energy disaggregation performance, the proposed EMEDA exhibited reductions of 97.5 and 61.7% in computational time compared with the recent smart event-based optimization and optimization-based load disaggregation approaches, respectively. Full article
(This article belongs to the Special Issue Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications)
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25 pages, 7762 KiB  
Article
A Novel Approach for the Implementation of Fast Frequency Control in Low-Inertia Power Systems Based on Local Measurements and Provision Costs
by Jelena Stojković and Predrag Stefanov
Electronics 2022, 11(11), 1776; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11111776 - 02 Jun 2022
Cited by 2 | Viewed by 1517
Abstract
Transitioning towards carbon-free energy has brought severe difficulties related to reduced inertia in electric power systems. Regarding frequency stability, low-inertia systems are more sensitive to disturbance, and traditional frequency control is becoming insufficient to maintain frequency within acceptable limits. Consequently, there is a [...] Read more.
Transitioning towards carbon-free energy has brought severe difficulties related to reduced inertia in electric power systems. Regarding frequency stability, low-inertia systems are more sensitive to disturbance, and traditional frequency control is becoming insufficient to maintain frequency within acceptable limits. Consequently, there is a necessity for faster frequency support that can be activated before the primary frequency control and that can decelerate further frequency decay. This paper proposes a local control strategy for a multi-stage fast frequency response (FFR) provided as an ancillary service that considers the location of the disturbance and the distribution of system inertia. The novelty of the presented control strategy is the ranking of FFR resources by price, which takes the economic component into consideration. The proposed control is simple, based only on RoCoF measurements that trigger the activation of FFR resources. Its advantage over other methods is the ability to adapt the FFR resource response to the disturbance without complex calculations and the ability to ensure a bigger response closer to the disturbance, as well as in low-inertia parts of the system. In that way, there is a bigger activation of resources in the parts of the system that are more endangered by disturbances, which, as a result, minimizes the propagation of the disturbance’s impact on system stability. The applicability of the presented method is demonstrated in a simple 3-area power system and IEEE 68-bus system implemented in MATLAB/Simulink. The results show that the proposed control enables the largest response closer to the disturbance, thus mitigating the propagation of the disturbance. Furthermore, the results confirm that the proposed control enables lower provision costs and more support in low-inertia areas that are more vulnerable to disturbances. Full article
(This article belongs to the Special Issue Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications)
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16 pages, 4874 KiB  
Article
Hardware-In-the-Loop Validation of Direct MPPT Based Cuckoo Search Optimization for Partially Shaded Photovoltaic System
by Abdullrahman A. Al-Shammaa, Akram M. Abdurraqeeb, Abdullah M. Noman, Abdulaziz Alkuhayli and Hassan M. H. Farh
Electronics 2022, 11(10), 1655; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11101655 - 23 May 2022
Cited by 10 | Viewed by 2074
Abstract
During partial shading conditions (PSCs), the power-voltage curve becomes more complex, having one global maximum power (GMP) and many local peaks. Traditional maximum power point tracking (MPPT) algorithms are unable to track the GMP under PSCs. Therefore, several optimization tactics based on metaheuristics [...] Read more.
During partial shading conditions (PSCs), the power-voltage curve becomes more complex, having one global maximum power (GMP) and many local peaks. Traditional maximum power point tracking (MPPT) algorithms are unable to track the GMP under PSCs. Therefore, several optimization tactics based on metaheuristics or artificial intelligence have been applied to deal with GMP tracking effectively. This paper details how a direct control cuckoo search optimizer (CSO) is used to track the GMP for a photovoltaic (PV) system. The proposed CSO addresses the limitations of traditional MPPT algorithms to deal with the PSCs and the shortcomings of the particle swarm optimization (PSO) algorithm, such as low tracking efficiency, steady-state fluctuations, and tracking time. The CSO was implemented using MATLAB/Simulink for a PV array operating under PSCs and its tracking performance was compared to that of the PSO-MPPT. Experimental validation of the CSO-MPPT was performed on a boost DC/DC converter using a real-time Hardware-In-the-Loop (HIL) simulator (OPAL-RT OP4510) and dSPACE 1104. The results show that CSO is capable of tracking GMP within 0.99–1.32 s under various shading patterns. Both the simulation and experimental findings revealed that the CSO outperformed the PSO in terms of steady-state fluctuations and tracking time. Full article
(This article belongs to the Special Issue Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications)
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15 pages, 11070 KiB  
Article
New High-Gain Transformerless DC/DC Boost Converter System
by Hassan Yousif Ahmed, Omar Abdel-Rahim and Ziad M. Ali
Electronics 2022, 11(5), 734; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11050734 - 26 Feb 2022
Cited by 23 | Viewed by 3322
Abstract
This article proposes a new high-gain transformerless dc/dc boost converter. Although they possess the ability to boost voltage at higher voltage levels, converter switching devices are under low voltage stress. The voltage stress on active switching devices is lower than the output voltage. [...] Read more.
This article proposes a new high-gain transformerless dc/dc boost converter. Although they possess the ability to boost voltage at higher voltage levels, converter switching devices are under low voltage stress. The voltage stress on active switching devices is lower than the output voltage. Therefore, low-rated components are used to implement the converter. The proposed converter can be considered as a promising candidate for PV microconverter applications, where high voltage-gain is required. The principle of operation and the steady-state analysis of the converter in the continuous conduction mode are presented. A hardware prototype for the converter is implemented in the laboratory to prove the concept of operation. Full article
(This article belongs to the Special Issue Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications)
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27 pages, 15792 KiB  
Article
Accurate Photovoltaic Models Based on an Adaptive Opposition Artificial Hummingbird Algorithm
by Abdelhady Ramadan, Salah Kamel, Mohamed H. Hassan, Emad M. Ahmed and Hany M. Hasanien
Electronics 2022, 11(3), 318; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics11030318 - 20 Jan 2022
Cited by 33 | Viewed by 2168
Abstract
The greater the demand for energy, the more important it is to improve and develop permanent energy sources, because of their advantages over non-renewable energy sources. With the development of artificial intelligence algorithms and the presence of so many data, the evolution of [...] Read more.
The greater the demand for energy, the more important it is to improve and develop permanent energy sources, because of their advantages over non-renewable energy sources. With the development of artificial intelligence algorithms and the presence of so many data, the evolution of simulation models has increased. In this research, an improvement to one recent optimization algorithm called the artificial hummingbird algorithm (AHA) is proposed. An adaptive opposition approach is suggested to select whether or not to use an opposition-based learning (OBL) method. This improvement is developed based on adding an adaptive updating mechanism to enable the original algorithm to obtain more accurate results with more complex problems, and is called the adaptive opposition artificial hummingbird algorithm (AOAHA). The proposed AOAHA was tested on 23 benchmark functions and compared with the original algorithm and other recent optimization algorithms such as supply–demand-based optimization (SDO), wild horse optimizer (WHO), and tunicate swarm algorithm (TSA). The proposed algorithm was applied to obtain accurate models for solar cell systems, which are the basis of solar power plants, in order to increase their efficiency, thus increasing the efficiency of the whole system. The experiments were carried out on two important models—the static and dynamic models—so that the proposed model would be more representative of real systems. Two applications for static models have been proposed: In the first application, the AOAHA satisfies the best root-mean-square values (0.0009825181). In the second application, the performance of the AOAHA is satisfied in all variable irradiance for the system. The results were evaluated in more than one way, taking into account the comparison with other modern and powerful optimization techniques. Improvement showed its potential through its satisfactory results in the tests that were applied to it. Full article
(This article belongs to the Special Issue Power System Dynamics, Operation, and Control including Renewable Energy Systems and Smart Grid: Technology and Applications)
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