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Electricity, Volume 5, Issue 2 (June 2024) – 12 articles

Cover Story (view full-size image): A growing demand for electricity has led to congestion within distribution networks. The challenge is to expand and modernise the grid to meet this demand, while implementing smart grid technologies to improve efficiency and reliability. Battery energy storage systems can be used to alleviate these problems. These systems absorb excess energy during off-peak periods and release it during peak periods, thereby balancing the load and reducing grid stress. This paper discusses two optimal power flow formulations: the branch flow model and the relaxed bus injection model. These formulations optimise battery energy storage to minimise power losses and avoid congestion. In addition, the paper compares these formulations by analysing objective function results and flexibility operation. A real Spanish network has been used for this analysis. View this paper
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29 pages, 2237 KiB  
Article
Average Modeling of High Frequency AC Link Three-Port DC/DC/DC Converters
by Eduardo Vasquez Mayen and Emmanuel De Jaeger
Electricity 2024, 5(2), 397-425; https://doi.org/10.3390/electricity5020021 - 17 Jun 2024
Viewed by 724
Abstract
The current transition towards renewable energies has led to an increased utilization of Photovoltaic (PV) sources and battery energy storage systems to complement the PV panels. To facilitate energy transfer among PVs, batteries, and loads, multiple converters are required. Thus, this transformation in [...] Read more.
The current transition towards renewable energies has led to an increased utilization of Photovoltaic (PV) sources and battery energy storage systems to complement the PV panels. To facilitate energy transfer among PVs, batteries, and loads, multiple converters are required. Thus, this transformation in the energy system has resulted in an increase in converter-interfaced elements. Within this context, three-port converters allow for replacing multiple converters with a single one. These three-port converters use a high-frequency AC resonant link for the bidirectional transfer of energy across the different ports. This architecture uses multiple switches and has a variable operating frequency. These characteristics make the simulation of these converters computationally heavy. Thus, averaged models are required, especially for simulating multiple converters connected in parallel or composing a microgrid. In this paper, an averaged model for this type of converter is developed. The methodology is first demonstrated and applied to a two-port DC/DC converter, and subsequently extended to the three-port DC/DC/DC version. Afterwards, control strategies for three-port DC/DC/DC converters are proposed based on the elements connected to their ports. The developed model for three-port DC/DC/DC converters is then implemented in an islanded DC microgrid to demonstrate their parallel operation. The proposed developed averaged models and the test DC microgrid are implemented in MATLAB/Simulink. Full article
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Figure 1
<p>Schematic of a two-port DC-DC HFAC link converter.</p>
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<p>Two-port DC/DC converter circuit diagram during Mode 1 ©2023 IEEE. Reproduced with copyright permission from [<a href="#B15-electricity-05-00021" class="html-bibr">15</a>].</p>
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<p>Two-port DC/DC converter circuit diagram during Modes 2 and 4 ©2023 IEEE. Reproduced with copyright permission from [<a href="#B15-electricity-05-00021" class="html-bibr">15</a>].</p>
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<p>Two-port DC/DC converter circuit diagram during Mode 3 ©2023 IEEE. Reproduced with copyright permission from [<a href="#B15-electricity-05-00021" class="html-bibr">15</a>].</p>
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<p>Two-port DC/DC converter HFAC link voltage and current waveform.</p>
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<p>Two-port DC/DC converter simplified circuit diagram.</p>
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<p>Two-port DC/DC converter state-space output voltage, <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mi>f</mi> </msub> </msub> </semantics></math>, step response to input <math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>i</mi> <mi>n</mi> </mrow> </msub> </semantics></math>.</p>
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<p>Influence of components parameters on two-port DC/DC converter state-space output voltage, <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mi>f</mi> </msub> </msub> </semantics></math>, response.</p>
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<p>Two-port DC/DC average converter implementation.</p>
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<p>Two-port DC/DC converter average model output: (<b>a</b>) Output voltage, <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mi>f</mi> </msub> </msub> </semantics></math>, (<b>b</b>) Link current, <math display="inline"><semantics> <msub> <mi>I</mi> <mi>L</mi> </msub> </semantics></math>, (<b>c</b>) Output inductance current, <math display="inline"><semantics> <msub> <mi>I</mi> <msub> <mi>L</mi> <mi>f</mi> </msub> </msub> </semantics></math>.</p>
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<p>Two-port DC/DC converter output voltage response to a 5% input voltage drop.</p>
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<p>Two-port DC/DC converter switch model Simulink implementation.</p>
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<p>Two-port DC/DC converter switches model HFAC link and switch currents.</p>
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<p>Switch and average two-port DC/DC converter step response comparison: (<b>a</b>) Output voltage, (<b>b</b>) HFAC link current.</p>
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<p>Switch and average two-port DC/DC converter ramp response comparison: (<b>a</b>) Output voltage, (<b>b</b>) HFAC link current.</p>
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<p>Three-port DC/DC/DC converter circuit diagram: two sources, one load.</p>
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<p>Three-port DC/DC/DC converter two sources, one load HFAC link voltage and current waveform ©2023 IEEE. Reproduced with copyright permission from [<a href="#B15-electricity-05-00021" class="html-bibr">15</a>].</p>
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<p>Three-port DC/DC/DC covnerter output voltage step response to inputs <math display="inline"><semantics> <msub> <mi>V</mi> <mn>1</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>V</mi> <mn>2</mn> </msub> </semantics></math>.</p>
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<p>Average three-port DC/DC/DC converter implementation with two sources, one load.</p>
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<p>Three-port DC/DC/DC converter two sources, one load Simulink implementation: (<b>a</b>) Output voltage, <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mi>f</mi> </msub> </msub> </semantics></math>, (<b>b</b>) Link current, <math display="inline"><semantics> <msub> <mi>I</mi> <mi>L</mi> </msub> </semantics></math>, (<b>c</b>) Output inductance current, <math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>L</mi> <mi>f</mi> </mrow> </msub> </semantics></math>.</p>
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<p>Three-port DC/DC/DC converter two sources, one load output voltage response to a 5% input voltage drop on both sources.</p>
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<p>Simplified three-port DC/DC/DC converter circuit diagram: one source, two loads.</p>
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<p>Three-port DC/DC/DC one source, two loads voltage and current waveform.</p>
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<p>Average three-port DC/DC/DC converter implementation with one, source two loads.</p>
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<p>Impact of load resistors size on <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mrow> <mi>f</mi> <mn>1</mn> </mrow> </msub> </msub> </semantics></math> response. Arrow indicates the direction of movement of the poles as the value of the resistances increase.</p>
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<p>Impact of filter capacitors size on <math display="inline"><semantics> <msub> <mi>V</mi> <msub> <mi>C</mi> <mrow> <mi>f</mi> <mn>1</mn> </mrow> </msub> </msub> </semantics></math> response. Arrow indicates the direction of movement of the poles as the value of the capacitors increase.</p>
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<p>Control scheme for battery-fed three-port DC/DC/DC converters connected to the DC microgrid and a load.</p>
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<p>Control scheme for battery and PV-fed three-port DC/DC/DC converters connected to the DC microgrid.</p>
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<p>Control scheme for PV-fed three-port DC/DC/DC converters connected to the DC microgrid and a load.</p>
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<p>Implemented DC microgrid in Matlab/Simulink.</p>
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<p>Three-port DC/DC/DC converters load-port output regulation: (<b>a</b>) Voltage, (<b>b</b>) Power supplied.</p>
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<p>Three-port DC/DC/DC converters DC microgrid port output regulation: (<b>a</b>) Voltage, (<b>b</b>) Power supplied.</p>
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<p>Power transfer in each port of Converter 3.</p>
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12 pages, 1797 KiB  
Article
The Implementation and Evaluation of Virtualized Protection Intelligent Electronic Devices into a Virtual Substation
by Dennis Rösch, Kevin Schäfer and Steffen Nicolai
Electricity 2024, 5(2), 385-396; https://doi.org/10.3390/electricity5020020 - 13 Jun 2024
Viewed by 474
Abstract
This paper presents an investigation into the virtualization of substation protection IED functions using a sophisticated co-simulation environment that integrates virtual intelligent electronic devices (vIEDs) with a real-time power grid simulation. Anchored by the IEC 61850 protocol, this study constructs a virtualized IED [...] Read more.
This paper presents an investigation into the virtualization of substation protection IED functions using a sophisticated co-simulation environment that integrates virtual intelligent electronic devices (vIEDs) with a real-time power grid simulation. Anchored by the IEC 61850 protocol, this study constructs a virtualized IED framework, emphasizing the encapsulation of protection schemes using the example of different types of overcurrent protection within a containerized vIED. Using open-source software, this study aims to replicate the communication and functional aspects of physical IEDs. This study uses a co-simulation environment that couples virtualized network components with a real-time power grid simulation to validate the vIEDs against real substation hardware. Simulation results from induced short-circuit events confirm the operational congruence of the vIEDs with their physical counterparts, demonstrating their potential to serve as cost-effective and adaptable testbeds for substation automation. This paper concludes that virtualized IEDs represent a cost-effective, flexible alternative for substation automation testing, with future research directed towards increasing the functional complexity and real-world applicability of these virtual systems. Full article
(This article belongs to the Special Issue Electricity in 2024)
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<p>Co-simulation structure including proposed vIED layout with two separated layers.</p>
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<p>A detailed overview of the two layers of the vIED with the structured workflow of PTOC relay.</p>
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<p>Extract of modeled substation with two feeder branches for protection function validation.</p>
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<p>Resulting short-circuit currents when using implemented vIED PIOC (<b>a</b>) and vIED PTOC protection algorithm (<b>b</b>).</p>
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<p>Resulting tripping times for described vIED approach and commercial ABB IED for PIOC (<b>a</b>) and PTOC protection algorithm (<b>b</b>).</p>
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<p>A breakdown of the total fault clearance time in digital IEDs.</p>
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15 pages, 850 KiB  
Article
Virtual Power Plants: Challenges, Opportunities, and Profitability Assessment in Current Energy Markets
by Zahid Ullah, Arshad Arshad and Azam Nekahi
Electricity 2024, 5(2), 370-384; https://doi.org/10.3390/electricity5020019 - 12 Jun 2024
Viewed by 635
Abstract
The arrival of virtual power plants (VPPs) marks important progress in the energy sector, providing optimistic solutions to the increasing need for energy flexibility, resilience, and improved energy systems’ integration. VPPs harness several characteristics to bring together distributed energy resources (DERs), resulting in [...] Read more.
The arrival of virtual power plants (VPPs) marks important progress in the energy sector, providing optimistic solutions to the increasing need for energy flexibility, resilience, and improved energy systems’ integration. VPPs harness several characteristics to bring together distributed energy resources (DERs), resulting in economic gains and improved power grid reliability. Nevertheless, VPPs encounter major challenges when it comes to engaging in energy markets, mainly because there is no all-encompassing policy and regulatory framework specifically designed to accommodate their unique characteristics. This underscores the necessity for research endeavours to develop more advanced methods and structures for the long-term viability of VPPs. To address this concern, the study advocates for the implementation of a multi-aspect framework (MAF) as a systematic approach to thoroughly examine each aspect of virtual power plants (VPPs). A STEEP (social, technological, environmental, economic, and political) analytical tool is utilized to evaluate the challenges, opportunities, and benefits of a VPP in the existing energy markets. The proposed approach highlights important factors and actions that need to be taken to tackle the challenges related to VPP’ entry into energy markets. This study suggests that further support is required to promote the fast and widespread adoption of long-term VPP implementations. For this reason, a more favourable policy and regulatory framework based on social, technological, economic, environmental, and policy considerations is necessary to realize the genuine contributions of VPPs. Full article
(This article belongs to the Topic Smart Energy Systems, 2nd Edition)
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<p>Virtual power plant structure.</p>
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<p>Followed methodology.</p>
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<p>STEEP model application.</p>
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19 pages, 1894 KiB  
Article
Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling
by Víctor Taltavull-Villalonga, Eduard Bullich-Massagué, Antonio E. Saldaña-González and Andreas Sumper
Electricity 2024, 5(2), 351-369; https://doi.org/10.3390/electricity5020018 - 9 Jun 2024
Viewed by 595
Abstract
The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the [...] Read more.
The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used. Full article
(This article belongs to the Special Issue Electricity in 2024)
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<p>Flowchart of the article methodology.</p>
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<p>Study distribution network structure and topology.</p>
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<p>Apparent power demanded hourly by each network node over one year.</p>
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<p>Apparent power aggregated to the slack node throughout the year and zoom of the week with the highest consumption of the year.</p>
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<p>Power flow result. Apparent power is flowing through each line of the network.</p>
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<p>Apparent power flowing through line 9 of the network when carrying out a power flow.</p>
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<p>Percentage load of network line 9 for each study model (Power Flow, BIM, and BFM) and maximum power and safety limits of the DSO.</p>
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<p>State-of-charge behavior of the network storage system over 7 time periods.</p>
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<p>Comparison between voltage results for power flow and optimal power flow.</p>
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<p>BoxPlot of objective function results with BIM and BFM models.</p>
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<p>Comparison of Computational Time Using BIM and BFM Models.</p>
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17 pages, 1189 KiB  
Review
Electricity Theft Detection and Prevention Using Technology-Based Models: A Systematic Literature Review
by Potego Maboe Kgaphola, Senyeki Milton Marebane and Robert Toyo Hans
Electricity 2024, 5(2), 334-350; https://doi.org/10.3390/electricity5020017 - 7 Jun 2024
Cited by 1 | Viewed by 1257
Abstract
Electricity theft comes with various disadvantages for power utilities, governments, businesses, and the general public. This continues despite the various solutions employed to detect and prevent it. Some of the disadvantages of electricity theft include revenue loss and load shedding, leading to a [...] Read more.
Electricity theft comes with various disadvantages for power utilities, governments, businesses, and the general public. This continues despite the various solutions employed to detect and prevent it. Some of the disadvantages of electricity theft include revenue loss and load shedding, leading to a disruption in business operations. This study aimed to conduct a systematic literature review to identify what technology solutions have been offered to solve electricity theft and the effectiveness of those solutions by considering peer-reviewed empirical studies. The systematic literature review was undertaken following the guidelines for conducting a literature review in computer science to assess potential bias. A total of 11 journal articles published from 2012 to 2022 in SCOPUS, Science Direct, and Web of Science were analysed to reveal solutions, the type of theft addressed, and the success and limitations of the solutions. The findings show that the focus in research is channelled towards solving electricity theft in Smart Grids (SGs) and Advanced Metering Infrastructure (AMI); moreover, there is a neglect in the recent literature on finding solutions that can prevent electricity theft in countries that do not have SG and AMI installed. Although the results reported in this study are confined to the analysed research papers, the leading limitation in the selected studies, lack of real-life data for dishonest users. This study’s contribution is to show what technology solutions are prevalent in solving electricity theft in recent years and the effectiveness of such solutions. Full article
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<p>Summary of electricity theft solutions.</p>
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<p>SLR protocol.</p>
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<p>Full selection criteria.</p>
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<p>Article search and selection process.</p>
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21 pages, 5826 KiB  
Article
Combined Light and Data Driving Stages without Capacitors for Energy Transformation
by Michael Windisch, Felix A. Himmelstoss, Monica Leba, Olimpiu Stoicuta and Helmut L. Votzi
Electricity 2024, 5(2), 313-333; https://doi.org/10.3390/electricity5020016 - 5 Jun 2024
Viewed by 681
Abstract
Three LED drivers which can be used for illumination, but whose main task is the transmission of information (data) via the light of the LEDs, are explored in this paper. The converter circuits need no capacitors for the energy transformation and avoid an [...] Read more.
Three LED drivers which can be used for illumination, but whose main task is the transmission of information (data) via the light of the LEDs, are explored in this paper. The converter circuits need no capacitors for the energy transformation and avoid an inrush current. The lack of necessity of electrolytic capacitors reduces cost and space. Dimming the illumination is also easy to achieve. The control concept of the converters and the generation of pulsing of the LEDs for transmitting the information (data) are explained. The converters can also be expanded to more stages to drive more LEDs with different types of information. All three converters are explained in detail; all presented circuits are built up and simulated with LTSpice. Several data transmission concepts are applied and demonstrated through simulations. Full article
(This article belongs to the Special Issue Electricity in 2024)
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Figure 1
<p>The basic structure of the LED driver of type I with the possibility to pulse the output.</p>
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<p>The simulation circuit. From top to bottom: the control signal of the pulsing switch (turquoise), the control signal of the main switch (blue), the load current (violet), the current through the coil (red), and the change in the current through the coil (red).</p>
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<p>The simulation circuit. From top to bottom: the control signal of the pulsing switch (turquoise), the control signal of the main switch (blue), the load current (violet), the current through the coil (red), and the change in the current through the coil (red).</p>
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<p>From top to bottom: the input voltage (green); the control signal of the pulsing switch (turquoise); the control signal of the main switch (blue); the load current (violet); the current through the coil (red); the change in the current through the coil (red).</p>
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<p>Simulation circuit.</p>
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<p>From top to bottom: current through LED3 (brown), current through LED2 (violet), current through LED1 (dark violet), control signal of main switch (dark blue), control signal of LED3 (turquoise), control signal of LED2 (blue), control signal of LED1 (green), and change in current through coil (red).</p>
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<p>(<b>a</b>) First variation. (<b>b</b>) Second variation.</p>
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<p>Combination of three converters of type I.</p>
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<p>Influence of parasitic load inductance. From top to bottom: ripple current through L1 (red), current through load (dark violet), voltage across S2 (blue), control signal of S2 (turquoise), voltage across S1 (green), and parasitic load inductance 1 µH without and with RC snubber of 10 Ω and 10 nF across S2.</p>
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<p>From top to bottom: ripple current through L1 (red), current through load (dark violet), voltage across S2 (blue), control signal of S2 (turquoise), voltage across S1 (green), and parasitic load inductance of 1 µH twice with RC snubber with 10 Ω and 10 nF across S2 and across load.</p>
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<p>Driving stage II.</p>
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<p>Start-up and pulsing information. From top to bottom: the current through the LEDs (dark violet), the information (blue), and the current through the coil (red).</p>
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<p>Start-up and pulsing information. From top to bottom: the current through the LEDs (dark violet), the information (blue), and the current through the coil (red).</p>
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<p>(<b>a</b>) A clock frequency of 500 kHz. From top to bottom: the current through the load (dark violet); the control signal of S2 (black); the control signal of S1 (turquoise); the current through the inductor (red). (<b>b</b>) A clock frequency of 1 MHz. From top to bottom: the current through the load (dark violet); the control signal of S2 (black); the control signal of S1 (turquoise); the current through the inductor (red).</p>
Full article ">Figure 14 Cont.
<p>(<b>a</b>) A clock frequency of 500 kHz. From top to bottom: the current through the load (dark violet); the control signal of S2 (black); the control signal of S1 (turquoise); the current through the inductor (red). (<b>b</b>) A clock frequency of 1 MHz. From top to bottom: the current through the load (dark violet); the control signal of S2 (black); the control signal of S1 (turquoise); the current through the inductor (red).</p>
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<p>Combination of three LED drivers of type II.</p>
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<p>With parasitic inductance of 0.2 µH, from top to bottom: voltage across S2 (dark green); voltage across S1 (turquoise); current through load (dark violet); current through coil (red); data (blue); control signal of S1 (green), without and with snubber in parallel to S2.</p>
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<p>LED driver and pulser of type III.</p>
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<p>The current through the coil measuring at 2 A. From top to bottom: the current through the load (dark violet); pulses (black); the control signal of the switch S1 (turquoise); the current through the coil (red).</p>
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<p>A current through the coil measuring at 2 A. From top to bottom: the current through the load (dark violet); pulses (black); the control signal of the switch S1 (turquoise); the current through the coil (red).</p>
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<p>Simulation circuit of hysteresis-controlled driving stage of type III.</p>
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<p>Hysteresis-controlled driving stage of type III. From top to bottom: reference value (gray), input voltage (blue), and current through coil (red).</p>
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<p>Start-up of hysteresis-controlled driving stage of type III. From top to bottom: reference value (gray), input voltage (blue), and current through coil (red).</p>
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<p>Hysteresis-controlled driving stage of type III: (<b>a</b>) reference value step; (<b>b</b>) input voltage step. From top to bottom: reference value (gray), input voltage (blue), and current through coil (red).</p>
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<p>Extended version of type III.</p>
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<p>Hysteresis-controlled driving stage of type III: influence of parasitic inductor at load side with 0.2 µH and 0.2 Ω. From top to bottom: current through L1 (red); voltage across load (turquoise); voltage across S2 (blue); input voltage (gray); voltage across S1 (green); input voltage (gray).</p>
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<p>Hysteresis-controlled driving stage of type III: influence of parasitic inductor at load side with 0.2 µH and 0.2 Ω and with RC snubber 10 Ω + 10 nF. From top to bottom: current through L1 (red); voltage across load (turquoise); voltage across S2 (blue); input voltage (gray); voltage across S1 (green); input voltage (gray).</p>
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<p>Combination of three driving stages of type III.</p>
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<p>The removal of the influence of the parasitic inductance at the input side. From top to bottom: the voltage across S1 (turquoise); the current through D1 (red); the voltage across S1 (blue); the control signal of S1 (black). The parasitic inductance is 1 µH and 470 nF is used as the input capacitor.</p>
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<p>Dimming, from top to bottom: current through LEDs (dark violet); current through L1 (red).</p>
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18 pages, 4455 KiB  
Article
A Single-Buyer Model of Imbalance Cost Pass-Through Pricing Forecasting in the Malaysian Electricity Supply Industry
by Fatin Khairunnisa Khairuddin, Farah Anishah Zaini, Mohamad Fani Sulaima, Nur Hazahsha Shamsudin and Mohd Shahrin Abu Hanifah
Electricity 2024, 5(2), 295-312; https://doi.org/10.3390/electricity5020015 - 11 May 2024
Viewed by 823
Abstract
The imbalance cost pass-through (ICPT) is a flexible component of the incentive-based regulation (IBR) that empowers power producers to adjust tariffs in response to variable fuel prices, thereby enhancing the economic resilience of electricity generation. In Malaysia, the Energy Commission has conducted biannual [...] Read more.
The imbalance cost pass-through (ICPT) is a flexible component of the incentive-based regulation (IBR) that empowers power producers to adjust tariffs in response to variable fuel prices, thereby enhancing the economic resilience of electricity generation. In Malaysia, the Energy Commission has conducted biannual reviews of fuel and other generation costs. Any cost savings or increases identified during these reviews will be passed on to customers in the form of rebates or surcharges. Meanwhile, if an increment in the ICPT price signal can be provided to electricity providers and consumers, early preparation for operation budgeting can be realised, and energy management program development can be properly prepared. Due to this reason, this study proposes ICPT price forecasting for the electricity market in Peninsular Malaysia that will benefit the stakeholders. The study aims to construct an ICPT-related baseline model for the peninsular generation data by employing three forecasting methods. The forecasting performance is analysed using the mean absolute percentage error (MAPE). In light of our findings, the ARIMA method is one of the most accurate forecasting methods for fuel prices compared to the moving average (MA) and LSSVM methods. The observed price differences between the ARIMA and LSSVM models for ICPT are minimal. The ICPT price for July–December 2022 and January–June 2023 is MYR 0.21/kWh for the ARIMA and MYR 0.18/kWh for LSSVM, which are close to the actual TNB’s ICPT tariff. As for forecasting, the ICPT price is expected to drop in the next announcement. The findings of this study may have a positive impact on the sustainability of the energy sector in Malaysia. Full article
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<p>The general description of the MESI structure in Peninsular Malaysia comes with two types of tariffs, which are the ICPT and the base tariff, under the IBR.</p>
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<p>Considered ICPT components under IBR.</p>
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<p>Previous ICPT price.</p>
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<p>Flowchart of (<b>a</b>) LLSVM and (<b>b</b>) moving average processes.</p>
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<p>(<b>a</b>) ACF and (<b>b</b>) PACF of coal.</p>
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<p>(<b>a</b>) ACF and (<b>b</b>) PACF of gas.</p>
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<p>(<b>a</b>) ACF and (<b>b</b>) PACF of LNG.</p>
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<p>Summary study flow to obtain the best value of ICPT forecasting.</p>
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<p>Correlation heatmap using Pearson’s regression technique.</p>
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<p>MA fuel price forecasting: (<b>a</b>) coal price; (<b>b</b>) gas price; and (<b>c</b>) LNG price.</p>
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<p>LSSVM fuel price forecasting: (<b>a</b>) coal price; (<b>b</b>) gas price; and (<b>c</b>) LNG price.</p>
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<p>ARIMA fuel price forecasting: (<b>a</b>) coal price; (<b>b</b>) gas price; and (<b>c</b>) LNG price.</p>
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<p>ICPT price for commercial customer.</p>
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24 pages, 2533 KiB  
Article
Evaluating Preparedness and Overcoming Challenges in Electricity Trading: An In-Depth Analysis Using the Analytic Hierarchy Process and a Case Study Exploration
by Suraj Regmi, Abhinav Rayamajhi, Ramhari Poudyal and Sanjeev Adhikari
Electricity 2024, 5(2), 271-294; https://doi.org/10.3390/electricity5020014 - 11 May 2024
Cited by 1 | Viewed by 1726
Abstract
The economy of South Asia is experiencing growth, yet it faces constraints due to heavy reliance on fossil fuels and frequent power outages. Access to diverse energy sources, particularly electricity, is crucial for sustaining this growth. One feasible solution involves neighbouring countries engaging [...] Read more.
The economy of South Asia is experiencing growth, yet it faces constraints due to heavy reliance on fossil fuels and frequent power outages. Access to diverse energy sources, particularly electricity, is crucial for sustaining this growth. One feasible solution involves neighbouring countries engaging in the trade of renewable electrical energy. Hydropower stands as one of the many energy sources available in South Asia. However, sectorial constraints pose significant challenges to energy trade initiatives. This study utilises the Analytic Hierarchy Process (AHP) to evaluate Nepal’s readiness and identify obstacles to its cross-border energy trade with India and Bangladesh. A comprehensive analysis of these obstacles is imperative for formulating effective strategies and policies. Additionally, this study offers recommendations for enhancing preparedness and resolving issues related to energy trading, which may apply to similar cross-border situations. This study ranks energy trading obstacles with neighbouring nations using the AHP, offering key insights for stakeholders and policymakers. Using a non-probabilistic purposeful sampling technique, 25 expert respondents from the energy sector and prominent academicians were selected as part of the data collection procedure. At every level of the interview process, their perspectives were invaluable in guaranteeing a thorough and rigorous investigation. Full article
(This article belongs to the Topic Electricity Demand-Side Management, 2nd Volume)
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<p>Hydropower projects are expected to be commissioned by 2027, with installed capacity in MW [<a href="#B21-electricity-05-00014" class="html-bibr">21</a>]. Reproduced with permission from NEA, Vidyut; published by NEA, 2023.</p>
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<p>Private sector projects under different stages [<a href="#B21-electricity-05-00014" class="html-bibr">21</a>]. Reproduced with permission from NEA, Vidyut; published by NEA, 2023.</p>
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<p>Capacity of private developers awaiting PPA approval from NEA in MW [<a href="#B21-electricity-05-00014" class="html-bibr">21</a>]. Reproduced with permission from NEA, Vidyut; published by NEA, 2023.</p>
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<p>Capacity simulations for power in MW for the 2021/2022 period [<a href="#B21-electricity-05-00014" class="html-bibr">21</a>]. Reproduced with permission from NEA, Vidyut; published by NEA, 2023.</p>
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<p>Capacity simulation of power in MW for the 2025/2026 period [<a href="#B21-electricity-05-00014" class="html-bibr">21</a>]. Reproduced with permission from NEA, <span class="html-italic">Vidyut</span>; published by NEA, 2023.</p>
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<p>Power development map of Nepal [<a href="#B23-electricity-05-00014" class="html-bibr">23</a>]. Reproduced with permission from NEA, Nepal Electricity Authority a Year in Review Fiscal Year 2022/2023; published by NEA, 2023.</p>
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<p>Integrated Nepal power system [<a href="#B23-electricity-05-00014" class="html-bibr">23</a>]. Reproduced with permission from NEA, Nepal Electricity Authority a Year in Review Fiscal Year 2022/2023; published by NEA, 2023.</p>
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<p>Minimum standards to establish multilateral power trade [<a href="#B32-electricity-05-00014" class="html-bibr">32</a>].</p>
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<p>Details about the methodology and workflow of the research.</p>
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<p>Three-tier model of hierarchical structure of AHP analysis.</p>
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17 pages, 4659 KiB  
Article
Green-Powered Electric Public Mobility: Integrating Urban and Interurban Routes—A Case Study Analysis
by Alessandro Franco, Giovanni Lutzemberger, Marco Giorgio Bevilacqua, Francesco Giuseppe Quilici and Matilde Vezzani
Electricity 2024, 5(2), 254-270; https://doi.org/10.3390/electricity5020013 - 8 May 2024
Cited by 1 | Viewed by 858
Abstract
This article proposes a particular strategy to proceed with a progressive electrification of public transport systems in cities. Starting from a bus operation model, the possible electrification of two routes is analyzed, one urban and another extra-urban in the city of Pisa. An [...] Read more.
This article proposes a particular strategy to proceed with a progressive electrification of public transport systems in cities. Starting from a bus operation model, the possible electrification of two routes is analyzed, one urban and another extra-urban in the city of Pisa. An estimate is made of the energy uses associated with certain operating modes. The maximum level of consumption is estimated at approximately 280 kWh per day per bus for the urban route and excluding some special days, less than 215 kWh per day for the extra-urban route, for which a hybrid bus is proposed. Starting from an estimate of the daily consumption for the management of the two routes, the sizing of a photovoltaic (PV) plant distributed on some modular shelters which serves to power the same routes, is carried out. The resulting system has a power of the order of 190–200 kW. The modular solution is also outlined, and an installation is proposed. The analyzed case lends itself to being easily replicated. Full article
(This article belongs to the Topic Integration of Renewable Energy)
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<p>The transition from a sectoral vision to an integrated vision of energy systems.</p>
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<p>A typical operating model of the bus.</p>
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<p>Representation of the urban route round trip with terminus and the two different paths: Outward journey (<b>a</b>) and Return journey (<b>b</b>).</p>
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<p>Model for the urban route.</p>
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<p>Representation of the extra-urban route.</p>
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<p>Simplified schematic architecture of the charging infrastructure, consisting of a photovoltaic system, storage system, charging column and connection to the electricity grid.</p>
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<p>View of the shelter and typical size compared to the dimensions of the buses.</p>
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<p>Detail of the structure defined for the modular shelter.</p>
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<p>A schematic view of the original effect of shelters.</p>
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<p>Disposition of adjacent shelters to obtain a plant of power of the order of 190–200 kW and area of the plant.</p>
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27 pages, 11489 KiB  
Article
Optimized and Sustainable PV Water Pumping System with Three-Port Converter, a Case Study: The Al-Kharijah Oasis
by Mohamed Selmy, Mohsen Z. El sherif, Miral Salah Noah and Islam M. Abdelqawee
Electricity 2024, 5(2), 227-253; https://doi.org/10.3390/electricity5020012 - 4 May 2024
Viewed by 934
Abstract
In this paper an efficient, compact, and cheap power source design for an off-grid PV water pumping system is investigated. The proposed system consists of a PV array, battery, three-port converter (TPC), three-phase voltage source inverter, and induction motor pump. Power is extracted [...] Read more.
In this paper an efficient, compact, and cheap power source design for an off-grid PV water pumping system is investigated. The proposed system consists of a PV array, battery, three-port converter (TPC), three-phase voltage source inverter, and induction motor pump. Power is extracted from PV sources during the daytime and used to charge batteries through the three-port converter, then used later to supply load during the nighttime. An intelligent MPPT method is used to obtain PV maximum power; a jellyfish optimization technique with different control algorithms is used to optimize and tune controllers’ parameters among the system. Different modes for the TPC are discussed depending on PV power availability. The proposed system is simulated to assess system performance under different conditions; also the system is efficient with reduced number of components than conventional converters. A complete unified power management over PV input port, battery port, and load port has occurred for all operation modes. At all operation modes, the system has been feeding load without any unmet loads. A real case study in Al-Kharijah oasis is studied and simulation results are listed; for the Dom case DC bus ripple factor voltage percentage equals 0.8%, in the Dim case equals 3%, and in the Siso mode equals 9%. Full article
(This article belongs to the Topic Integration of Renewable Energy)
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<p>Schematic diagram of the PV water pumping system.</p>
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<p>The PV array has Nser and Npar modules [<a href="#B13-electricity-05-00012" class="html-bibr">13</a>].</p>
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<p>Schematic diagram of the three-port converter.</p>
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<p>TPC operating modes [<a href="#B15-electricity-05-00012" class="html-bibr">15</a>].</p>
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<p>Flow chart of TPC modes.</p>
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<p>Dom circuit diagram.</p>
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<p>Dim circuit diagram.</p>
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<p>PV to load (Siso) circuit diagram.</p>
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<p>Battery to load (Siso) circuit diagram.</p>
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<p>Fuzzy controller block diagram.</p>
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<p>JF movements in ocean [<a href="#B19-electricity-05-00012" class="html-bibr">19</a>].</p>
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<p>System schematic diagram.</p>
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<p>JF algorithm flowchart.</p>
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<p>Average daily incident shortwave solar energy in Al-Kharijah [<a href="#B21-electricity-05-00012" class="html-bibr">21</a>].</p>
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<p>Hours of daylight and twilight in Al-Kharijah [<a href="#B21-electricity-05-00012" class="html-bibr">21</a>].</p>
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<p>(<b>a</b>) DC bus voltage. (<b>b</b>) DC bus percentage voltage ripple factor percentage.</p>
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<p>(<b>a</b>) RMS value of three-phase AC output voltage. (<b>b</b>) RMS value of three-phase AC output current.</p>
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<p>(<b>a</b>) Motor speed. (<b>b</b>) Motor torque.</p>
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<p>(<b>a</b>) PV array output power. (<b>b</b>) Motor power.</p>
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<p>(<b>a</b>) System power management. (<b>b</b>) Battery state of charge.</p>
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<p>(<b>a</b>) DC bus voltage. (<b>b</b>) DC bus voltage ripple factor percentage.</p>
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<p>(<b>a</b>) RMS value for the AC voltage. (<b>b</b>) RMS value for AC current.</p>
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<p>(<b>a</b>) Motor speed. (<b>b</b>) Motor torque.</p>
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<p>(<b>a</b>) PV power. (<b>b</b>) Load power.</p>
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<p>(<b>a</b>) System power management. (<b>b</b>) Battery state of charge.</p>
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<p>(<b>a</b>) DC bus voltage. (<b>b</b>) DC bus voltage ripple factor percentage.</p>
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<p>(<b>a</b>) RMS value of three-phase AC output voltage. (<b>b</b>) RMS value of three-phase AC output current.</p>
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<p>(<b>a</b>) Motor speed. (<b>b</b>) Motor torque.</p>
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<p>(<b>a</b>) Motor power. (<b>b</b>) Battery discharging power.</p>
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<p>Battery state of charge.</p>
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<p>Solar irradiations.</p>
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<p>(<b>a</b>) DC bus voltage. (<b>b</b>) DC bus voltage ripple factor percentage.</p>
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<p>(<b>a</b>) RMS value of three-phase AC output voltage. (<b>b</b>) RMS value of three-phase AC output current.</p>
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<p>(<b>a</b>) Motor speed. (<b>b</b>) Motor torque.</p>
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<p>(<b>a</b>) PV array output power. (<b>b</b>) Motor power.</p>
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<p>Battery state of charge.</p>
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<p>Solar irradiation for a day in August [<a href="#B21-electricity-05-00012" class="html-bibr">21</a>].</p>
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<p>Solar irradiations.</p>
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<p>(<b>a</b>) DC bus voltage. (<b>b</b>) DC bus voltage ripple factor percentage.</p>
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<p>(<b>a</b>) RMS value of three-phase AC output voltage. (<b>b</b>) RMS value of three-phase AC output current.</p>
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<p>(<b>a</b>) Motor speed. (<b>b</b>) Motor torque.</p>
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<p>(<b>a</b>) PV array output power. (<b>b</b>) Motor power.</p>
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<p>Battery state of charge.</p>
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<p>(<b>a</b>) THD value of three-phase AC output voltage. (<b>b</b>) THD value of three-phase AC output current.</p>
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16 pages, 6929 KiB  
Article
Single-Stage LLC Resonant Converter for Induction Heating System with Improved Power Quality
by Anand Kumar, Anik Goswami, Pradip Kumar Sadhu and Jerzy R. Szymanski
Electricity 2024, 5(2), 211-226; https://doi.org/10.3390/electricity5020011 - 26 Apr 2024
Viewed by 802
Abstract
This paper proposes a single-stage direct AC to high-frequency (HF) AC resonant converter based on LLC configuration for induction heating (IH) systems or HF applications. Unlike conventional converters for IH systems, the proposed topology converts the utility frequency to HF AC in a [...] Read more.
This paper proposes a single-stage direct AC to high-frequency (HF) AC resonant converter based on LLC configuration for induction heating (IH) systems or HF applications. Unlike conventional converters for IH systems, the proposed topology converts the utility frequency to HF AC in a single stage without using a DC link inductor and capacitors and takes the advantages of LLC configuration. Additionally, it improves the power factor to 0.9–1, lowers the THD (3.2% experimentally), and protects against the high-frequency components. An embedded control scheme was designed to keep the HF current oscillating at a resonant frequency, ensuring zero-voltage switching. The operating principle of the proposed topology was investigated using mathematical equations and equivalent circuits. Finally, it was verified using computer simulation, and an experimental prototype of 1.1 kW was developed to demonstrate the proposed topology’s uniqueness. Full article
(This article belongs to the Topic Power Converters)
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<p>Proposed configuration of the direct AC–HFAC LLC resonant converter.</p>
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<p>Passive filter.</p>
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<p>Operational modes of the proposed direct AC–HF AC converter: (<b>a</b>) Mode 1; (<b>b</b>) Mode 2; (<b>c</b>) Mode 3; (<b>d</b>) Mode 4.</p>
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<p>Frequency synthesization of the output voltage using the proposed topology: (<b>a</b>) 100 Hz-output voltage synthesization; (<b>b</b>) High-frequency output voltage synthesization.</p>
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<p>Equivalent circuit of the proposed topology.</p>
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<p>Output current (<span class="html-italic">I<sub>o</sub></span>) in p.u at different Q factors.</p>
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<p>Block diagram of the prototype implementation.</p>
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<p>Experimental setup of the proposed IH power supply system.</p>
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<p>Input voltage and current: (<b>a</b>) Simulation result; (<b>b</b>) Experimental result (<span class="html-italic">V<sub>s</sub></span>: 100 V/div; <span class="html-italic">I<sub>in</sub></span>: 20 A/div).</p>
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<p>FFT spectrum of the input current.</p>
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<p>Gate signals: (<b>a</b>) Simulation result; (<b>b</b>) Experimental result (<span class="html-italic">V<sub>g</sub></span><sub>1</sub> and <span class="html-italic">V<sub>g</sub></span><sub>2</sub>: 5 V/div).</p>
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<p>Input voltage and current results: (<b>a</b>) Simulation result; (<b>b</b>) Experimental result (<span class="html-italic">V<sub>o</sub></span>: 80 V/div; <span class="html-italic">I<sub>o</sub></span>: 20 A/div).</p>
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<p>(<b>a</b>) Average output power (<span class="html-italic">P<sub>out</sub></span>) and (<b>b</b>) efficiency analysis.</p>
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37 pages, 25724 KiB  
Article
Development of a New Modelling Concept for Power Flow Calculations across Voltage Levels
by Tobias Riedlinger, Patrick Wintzek and Markus Zdrallek
Electricity 2024, 5(2), 174-210; https://doi.org/10.3390/electricity5020010 - 1 Apr 2024
Viewed by 866
Abstract
In the context of the energy transition, the share of new loads such as charging infrastructure for electromobility and electric heat pumps as well as feed-ins such as photovoltaic systems will steadily increase. This results in an increased degree of complexity for strategic [...] Read more.
In the context of the energy transition, the share of new loads such as charging infrastructure for electromobility and electric heat pumps as well as feed-ins such as photovoltaic systems will steadily increase. This results in an increased degree of complexity for strategic network planning. In particular, the power flow analyses for the dimensioning of transformers and lines per network level currently still require different methods for the correct dimensioning of these equipment. They need to be carried out in separate data sets. For the dimensioning of the equipment simultaneity factors are predominantly used for realistic load assumptions in strategic network planning. These simultaneity factors and resulting load assumptions are determined from the planning perspective of the transformers and from the planning perspective of the lines per network level to be able to dimension the corresponding equipment. This results in different power flow results for the analysis and evaluation of different network levels in particular. This contribution presents a new concept for network modelling in which the simultaneity of the different planning perspectives of the different network levels results from a single power flow calculation in a coherent data set. Full article
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<p>Planning perspectives considering the respective simultaneity factors (SFs).</p>
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<p>Presentation of the modelling concepts for each planning perspective (concept 1).</p>
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<p>Presentation of the basic data structure of the new modelling concept (concept 2).</p>
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<p>Exemplary illustration of concept 2 with compensation feed-ins.</p>
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<p>Application of concept 2 with compensation feed-ins on an example network.</p>
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<p>Assumed voltage band distribution for concept 1a in the operation point peak load.</p>
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<p>(<b>Left</b>): Voltage values of the HV/MV transformer nodes, (<b>right</b>): Loadings of the HV/MV transformers; both concept 1a.</p>
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<p><b>(Left</b>): Voltage values of the MV nodes, (<b>right</b>): Loadings of the MV line sections; both concept 1a.</p>
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<p><b>(Left</b>): Voltage values of the MV/LV transformer nodes, (<b>right</b>): Loadings of the MV/LV transformers; both concept 1a.</p>
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<p>(<b>Left</b>): Voltage values of the LV nodes, (<b>right</b>): Loadings of the LV line sections; both concept 1a.</p>
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<p>(<b>Left</b>): Voltage values of the HV/MV transformer nodes, (<b>right</b>): Loadings of the HV/MV transformers; both concept 1b.</p>
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<p>(<b>Left</b>): Voltage values of the MV nodes, (<b>right</b>): Loadings of the MV line sections; both concept 1b.</p>
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<p>(<b>Left</b>): Voltage values of the MV/LV transformer nodes, (<b>right</b>): Loadings of the MV/LV transformers; both concept 1b.</p>
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<p>(<b>Left</b>): Voltage values of the LV nodes, (<b>right</b>): Loadings of the LV line sections; both concept 1b.</p>
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<p>(<b>Left</b>): Voltage values of the HV/MV transformer nodes, (<b>right</b>): Loadings of the HV/MV transformers; both concept 2.</p>
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<p>(<b>Left</b>): Voltage values of the MV nodes, (<b>right</b>): Loadings of the MV line sections; both concept 2.</p>
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<p>(<b>Left</b>): Voltage values of the MV/LV transformer nodes, (<b>right</b>): Loadings of the MV/LV transformers; both concept 2.</p>
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<p>(<b>Left</b>): Voltage values of the LV nodes, (<b>right</b>): Loadings of the LV line sections; both concept 2.</p>
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<p>Comparison of the examined concepts 1a, 1b and 2.</p>
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<p>Voltage values of the HV/MV transformer nodes in concept 2 and concept 1a.</p>
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<p>Voltage value deviations of the MV nodes between concept 2 and concept 1a (Inverted square brackets exclude the number from the specified range).</p>
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<p>Voltage value deviations of the MV nodes between concept 2 and concept 1a as functions of the node voltage values.</p>
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<p>Voltage drop deviations of the MV/LV transformers between concept 2 and concept 1a. (Inverted square brackets exclude the number from the specified range).</p>
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<p>Voltage drop deviations of the MV/LV transformers between concept 2 and concept 1a as a function of the loading deviations of the MV/LV transformers.</p>
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<p>(<b>Left</b>): Distribution of the voltage value deviations on the high voltage sides of the MV/LV transformers between concept 2 and concept 1a, (<b>right</b>): Distribution of the voltage value deviations on the low voltage sides of the MV/LV transformers between concept 2 and concept 1a (Inverted square brackets exclude the number from the specified range).</p>
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<p>Voltage value deviations of the LV nodes between concept 2 and concept 1a (Inverted square brackets exclude the number from the specified range).</p>
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<p>Voltage value deviations of the LV nodes between concept 2 and concept 1a as functions of the node voltage values.</p>
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<p>(<b>Left</b>): Loadings of the HV/MV transformers in concept 2 and concept 1a, (<b>right</b>): Power flows of the HV/MV transformers in concept 2 and concept 1a.</p>
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<p>Loading deviations of the MV line sections between concept 2 and concept 1a (Inverted square brackets exclude the number from the specified range).</p>
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<p>Loading deviations of the MV line sections between concept 2 and concept 1a as a function of the line loadings.</p>
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<p>Percentage deviations of the load of the LV networks from the MV line planning perspective (load incl. LV line losses and MV/LV transformer losses from MV line planning perspective) between concept 2 and concept 1a.</p>
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<p>Loading deviations of the MV/LV transformers between concept 2 and concept 1a. (Inverted square brackets exclude the number from the specified range).</p>
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<p>Loading deviations of the MV/LV transformers between concept 2 and concept 1a (only distribution transformers) as a function of the deviations of the network losses (apparent power in kVA).</p>
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<p>Loading deviations of the LV line sections between concept 2 and concept 1a (Inverted square brackets exclude the number from the specified range).</p>
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<p>(<b>Left</b>): Percentage loading deviations of the absolute loadings of the LV line sections between concept 2 and concept 1a as a function of the voltage value deviations of the starting nodes of the LV lines between concept 2 and concept 1a, (<b>right</b>): Loading deviations of the LV line sections between concept 2 and concept 1a as a function of the LV line loadings.</p>
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<p>Network losses per planning perspective in concept 2 and concept 1a.</p>
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<p>(<b>Left</b>): Deviation of the equipment losses of the equipment in the respective network level between concept 2 and concept 1a, (<b>right</b>): Deviation of the network losses of equipment in the different planning perspectives of concept 1a between concept 2 and concept 1a.</p>
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<p>(<b>Left</b>): Voltage value deviations of the MV nodes between concept 2 and concept 1b, (<b>right</b>): Voltage value deviations of the MV nodes between concept 1b and concept 1a.</p>
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<p>(<b>Left</b>): Voltage drop deviations of the MV/LV transformers between concept 2 and concept 1b, (<b>right</b>): Voltage drop deviations of the MV/LV transformers between concept 1a and concept 1b.</p>
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<p>(<b>Left</b>): Voltage value deviations of the LV nodes between concept 2 and concept 1b (further decimal places were not output in the network calculation software), (<b>right</b>): Voltage value deviations of the LV nodes between concept 1a and concept 1b.</p>
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<p>(<b>Left</b>): Loading deviations of the MV line sections between concept 2 and concept 1b, (<b>right</b>): Loading deviations of the MV line sections between concept 1a and concept 1b.</p>
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<p>(<b>Left</b>): Loading deviations of the MV/LV transformers between concept 2 and concept 1b, (<b>right</b>): Loading deviations of the MV/LV transformers between concept 1a and concept 1b.</p>
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<p>(<b>Left</b>): Loading deviations of the LV line sections between concept 2 and concept 1b, (<b>right</b>): Loading deviations of the LV line sections between concept 1a and concept 1b.</p>
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<p>Network losses per planning perspective in concept 2 and concept 1b.</p>
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