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Smart Grids and Contemporary Electricity Markets
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Smart Grids and Contemporary Electricity Markets

A special issue of Applied System Innovation (ISSN 2571-5577).

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 13983

Special Issue Editors

Prof. Dr. Emmanuel Karapidakis

E-Mail Website
Guest Editor
Electrical and Computer Engineering Department, Hellenic Mediterranean University, 71410 Heraklion, Greece
Interests: Power Systems; RES; Microgrids; Smart Grids; Energy Transition
Special Issues, Collections and Topics in MDPI journals
Dr. Alexandros Paspatis

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Hellenic Mediterranean University, GR-71410 Heraklion, Greece
Interests: inverter control; converter-driven stability; microgrids; power systems; laboratory testing

Special Issue Information

Dear Colleagues,

Contemporary power systems are facing a significant structural change. The steadily increasing share of renewable energy technologies (RETs) in the energy balance, the enhancement of their performance and competitiveness, and the extensive use of information and communication technologies (ICTs) in power system operation are leading to a new era in a process known as an energy transition.

From another point of view, considering the energy transition as a pathway toward the transformation of the global energy sector from centralized and fossil-fuel-based power systems to sustainable and resilient grids, this Special Issue will focus on the most reliable means of achieving this goal, namely information technologies, renewable energy technologies, energy automation systems, policy frameworks, and market instruments.

Furthermore, new concepts of electricity trading have emerged, with very interesting but complicated algorithms. This Special Issue will also focus on the future operation of smart grids in new electricity markets.

Aims and Scope

The aims of this Special Issue are as follows:

  1. To enhance the knowledge of reliability and resilience improvements;
  2. To introduce better utilization of current resources and grid assets;
  3. To promote more efficient operational regulations and policies;
  4. To define an adequate power quality and relevant services for end-users;
  5. To advance electricity market transactions.

The scope of this Special Issue includes the following topics:

  1. Resilience in the face of faults and disasters;
  2. Load management and load balancing;
  3. Customer participation;
  4. Integration of renewable energy applications;
  5. Security and reliability of the electricity network;
  6. Smart algorithms and devices;
  7. Smart grid modeling;
  8. Application of smart grid concepts to residential and distribution systems;
  9. Architectures for smart grids;
  10. Power quality;
  11. Power transmission in a smart grid;
  12. Electricity trading and energy market transactions.

Prof. Dr. Emmanuel Karapidakis
Dr. Alexandros Paspatis
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. Applied System Innovation 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 1400 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

  • Photovoltaics
  • Wind power
  • Energy storage
  • Dispersed generation
  • Microgrids
  • Smart grid architecture
  • Grid reliability and stability
  • Grid monitoring and control
  • Energy transition
  • Energy markets and electricity trading
  • Grid codes
  • Aggregators
  • Demand response

Published Papers (6 papers)

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Research

16 pages, 1192 KiB  
Article
Machine Learning and Bagging to Predict Midterm Electricity Consumption in Saudi Arabia
by Dhiaa A. Musleh and Maissa A. Al Metrik
Appl. Syst. Innov. 2023, 6(4), 65; https://0-doi-org.brum.beds.ac.uk/10.3390/asi6040065 - 10 Jul 2023
Cited by 1 | Viewed by 1793
Abstract
Electricity is widely regarded as the most adaptable form of energy and a major secondary energy source. However, electricity is not economically storable; therefore, the power system requires a continuous balance of electricity production and consumption to be stable. The accurate and reliable [...] Read more.
Electricity is widely regarded as the most adaptable form of energy and a major secondary energy source. However, electricity is not economically storable; therefore, the power system requires a continuous balance of electricity production and consumption to be stable. The accurate and reliable assessment of electrical energy consumption enables planning prospective power-producing systems to satisfy the expanding demand for electrical energy. Since Saudi Arabia is one of the top electricity consumers worldwide, this paper proposed an electricity consumption prediction model in Saudia Arabia. In this work, the authors obtained a never-before-seen dataset of Saudi Arabia’s electricity consumption for a span of ten years. The dataset was acquired solely by the authors from the Saudi Electrical Company (SEC), and it has further research potential that far exceeds this work. The research closely examined the performance of ensemble models and the K* model as novel models to predict the monthly electricity consumption for eighteen service offices from the Saudi Electrical Company dataset, providing experiments on a new electricity consumption dataset. The global blend parameters for the K* algorithm were tuned to achieve the best performance for predicting electricity consumption. The K* model achieved a high accuracy, and the results of the correlation coefficient (CC), mean absolute percentage error (MAPE), root mean squared percentage error (RMSPE), mean absolute error (MAE), and root mean squared error (RMSE) were 0.9373, 0.1569, 0.5636, 0.016, and 0.0488, respectively. The obtained results showed that the bagging ensemble model outperformed the standalone K* model. It used the original full dataset with K* as the base classifier, which produced a 0.9383 CC, 0.1511 MAPE, 0.5333 RMSPE, 0.0158 MAE, and 0.0484 RMSE. The outcomes of this work were compared with a previous study on the same dataset using an artificial neural network (ANN), and the comparison showed that the K* model used in this study performed better than the ANN model when compared with the standalone models and the bagging ensemble. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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24 pages, 5319 KiB  
Article
Data-Mining Techniques Based Relaying Support for Symmetric-Monopolar-Multi-Terminal VSC-HVDC System
by Abha Pragati, Debadatta Amaresh Gadanayak, Tanmoy Parida and Manohar Mishra
Appl. Syst. Innov. 2023, 6(1), 24; https://0-doi-org.brum.beds.ac.uk/10.3390/asi6010024 - 05 Feb 2023
Cited by 3 | Viewed by 1566
Abstract
Considering the advantage of the ability of data-mining techniques (DMTs) to detect and classify patterns, this paper explores their applicability for the protection of voltage source converter-based high voltage direct current (VSC-HVDC) transmission systems. In spite of the location of fault occurring points [...] Read more.
Considering the advantage of the ability of data-mining techniques (DMTs) to detect and classify patterns, this paper explores their applicability for the protection of voltage source converter-based high voltage direct current (VSC-HVDC) transmission systems. In spite of the location of fault occurring points such as external/internal, rectifier-substation/inverter-substation, and positive/negative pole of the DC line, the stated approach is capable of accurate fault detection, classification, and location. Initially, the local voltage and current measurements at one end of the HVDC system are used in this work to extract the feature vector. Once the feature vector is retrieved, the DMTs are trained and tested to identify the fault types (internal DC faults, external AC faults, and external DC faults) and fault location in the particular feeder. In the data-mining framework, several state-of-the-art machine learning (ML) models along with one advanced deep learning (DL) model are used for training and testing. The proposed VSC-HVDC relaying system is comprehensively tested on a symmetric-monopolar-multi-terminal VSC-HVDC system and presents heartening results in diverse operating conditions. The results show that the studied deep belief network (DBN) based DL model performs better compared with other ML models in both fault classification and location. The accuracy of fault classification of the DBN is found to be 98.9% in the noiseless condition and 91.8% in the 20 dB noisy condition. Similarly, the DBN-based DMT is found to be effective in fault locations in the HVDC system with a smaller percentage of errors as MSE: 2.116, RMSE: 1.4531, and MAPE: 2.7047. This approach can be used as an effective low-cost relaying support tool for the VSC-HVDC system, as it does not necessitate a communication channel. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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20 pages, 3495 KiB  
Article
A Graph-Theoretic Approach for Modelling and Resiliency Analysis of Synchrophasor Communication Networks
by Amitkumar V. Jha, Bhargav Appasani, Nicu Bizon and Phatiphat Thounthong
Appl. Syst. Innov. 2023, 6(1), 7; https://0-doi-org.brum.beds.ac.uk/10.3390/asi6010007 - 05 Jan 2023
Cited by 1 | Viewed by 1335
Abstract
In recent years, the Smart Grid (SG) has been conceptualized as a burgeoning technology for improvising power systems. The core of the communication infrastructure in SGs is the Synchrophasor Communication Network (SCN). Using the SCN, synchrophasor data communication is facilitated between the Phasor [...] Read more.
In recent years, the Smart Grid (SG) has been conceptualized as a burgeoning technology for improvising power systems. The core of the communication infrastructure in SGs is the Synchrophasor Communication Network (SCN). Using the SCN, synchrophasor data communication is facilitated between the Phasor Measurement Unit (PMU) and Phasor Data Concentrator (PDC). However, the SCN is subjected to many challenges. As a result, the components, such as the links, PMUs, PDCs, nodes, etc., of the SCN are subjected to failure. Such failure affects the operation of the SCN and results in the performance degradation of the SG. The performance degradation of the smart grid is observed either temporarily or permanently due to packet loss. To avoid dire consequences, such as a power blackout, the SCN must be resilient to such failures. This paper presents a novel analytical method for the resiliency analysis of SCNs. A graph-theoretic approach was used to model SCN from the resiliency analysis perspective. Furthermore, we proposed a simulation framework for validating the analytical method using the Network Simulator-3 (ns-3) software. The proposed non-intrusive simulation framework can also be extended to design and analyse the resiliency of generic communication networks. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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17 pages, 8120 KiB  
Article
Economic Assessment of Photovoltaics Sizing on a Sports Center’s Microgrid Equipped with PEV Chargers
by Emmanuel Karapidakis, George Konstantinidis, Nectarios Vidakis and Sofia Yfanti
Appl. Syst. Innov. 2022, 5(4), 78; https://0-doi-org.brum.beds.ac.uk/10.3390/asi5040078 - 11 Aug 2022
Viewed by 1396
Abstract
Large sports centers are characterized by special energy demand profiles compared to other facilities. The aim of this work is to assess the economic investment of photovoltaics (PVs) on a sport center microgrid using different charging methods and by efficiently exploiting the PV [...] Read more.
Large sports centers are characterized by special energy demand profiles compared to other facilities. The aim of this work is to assess the economic investment of photovoltaics (PVs) on a sport center microgrid using different charging methods and by efficiently exploiting the PV generation. The overall work is performed in the following three steps. The first step is the energy requirement analysis, the second focuses on a PEV charging strategy proposition in order to exploit the PV generation, grid electricity price, and Vehicle-to-Grid (V2G), and the third step is the net present value (NPV) analysis of the PV investment in the different scenarios. The simulations showed that the proposed charging strategy increases the NPV. In addition, the increment of PEV penetration rate leads to the maximization of the NPV. The energy and costs analysis are carried out for an application case in the Olympic Athletic Centre of Athens. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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14 pages, 4100 KiB  
Article
LVRT and Stability Enhancement of Grid-Tied Wind Farm Using DFIG-Based Wind Turbine
by Jannatul Mawa Akanto, Md. Rifat Hazari and Mohammad Abdul Mannan
Appl. Syst. Innov. 2021, 4(2), 33; https://0-doi-org.brum.beds.ac.uk/10.3390/asi4020033 - 12 May 2021
Cited by 11 | Viewed by 3416
Abstract
According to the grid code specifications, low voltage ride-through (LVRT) is one of the key factors for grid-tied wind farms (WFs). Since fixed-speed wind turbines with squirrel cage induction generators (FSWT-SCIGs) require an adequate quantity of reactive power throughout the transient period, conventional [...] Read more.
According to the grid code specifications, low voltage ride-through (LVRT) is one of the key factors for grid-tied wind farms (WFs). Since fixed-speed wind turbines with squirrel cage induction generators (FSWT-SCIGs) require an adequate quantity of reactive power throughout the transient period, conventional WF consisting of SCIG do not typically have LVRT capabilities that may cause instability in the power system. However, variable-speed wind turbines with doubly fed induction generators (VSWT-DFIGs) have an adequate amount of LVRT enhancement competency, and the active and reactive power transmitted to the grid can also be controlled. Moreover, DFIG is quite expensive because of its partial rating (AC/DC/AC) converter than SCIG. Accordingly, combined installation of both WFs could be an effective solution. Hence, this paper illustrated a new rotor-side converter (RSC) control scheme, which played a significant role in ensuring the LVRT aptitude for a wide range of hybrid WF consisting of both FSWT-SCIGs and VSWT-DFIGs. What is more, the proposed RSC controller of DFIG was configured to deliver an ample quantity of reactive power to the SCIG during the fault state to make the overall system stable. Simulation analyses were performed for both proposed and traditional controllers of RSC of the DFIG in the PSCAD/EMTDC environment to observe the proposed controller response. Overall, the presented control scheme could guarantee the LVRT aptitude of large-scale SCIG. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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13 pages, 4400 KiB  
Article
Study of a Synchronization System for Distributed Inverters Conceived for FPGA Devices
by Leonardo Saccenti, Valentina Bianchi and Ilaria De Munari
Appl. Syst. Innov. 2021, 4(1), 5; https://0-doi-org.brum.beds.ac.uk/10.3390/asi4010005 - 15 Jan 2021
Viewed by 3169
Abstract
In a multiple parallel-connected inverters system, limiting the circulating current phenomenon is mandatory since it may influence efficiency and reliability. In this paper, a new control method aimed at this purpose and conceived to be implemented on a Field Programmable Gate Array (FPGA) [...] Read more.
In a multiple parallel-connected inverters system, limiting the circulating current phenomenon is mandatory since it may influence efficiency and reliability. In this paper, a new control method aimed at this purpose and conceived to be implemented on a Field Programmable Gate Array (FPGA) device is presented. Each of the inverters, connected in parallel, is conceived to be equipped with an FPGA that controls the Pulse-Width Modulation (PWM) waveform without intercommunication with the others. The hardware implemented is the same for every inverter; therefore, the addition of a new module does not require redesign, enhancing system modularity. The system has been simulated in a Simulink environment. To study its behavior and to improve the control method, simulations with two parallel-connected inverters have been firstly conducted, then additional simulations have been performed with increasing complexity to demonstrate the quality of the algorithm. The results prove the ability of the method proposed to limit the circulating currents to negligible values. Full article
(This article belongs to the Special Issue Smart Grids and Contemporary Electricity Markets)
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