New Technologies for Smart Distribution Grid

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

Deadline for manuscript submissions: closed (15 September 2020) | Viewed by 17659

Special Issue Editors


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Guest Editor
Department of Electrical and Energy Engineering, University of Cantabria, Avda. Los Castros s/n, 39005 Santander, Spain
Interests: smart grids; power quality; grid integration of renewable energies; energy efficiency
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy
Interests: power systems analysis; reliable computing; decentralized optimization; self-organizing sensor networks; renewable power generators
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electrical networks have undergone a great transformation during the last decade due to the technological advances in all fields of knowledge related to the generation, transport and distribution of electrical energy.

As electricity is becoming the key player in a low carbon economy, researchers are devoting more effort towards improving control and measurement systems.

At the same time, distribution networks incorporate new usage paradigms, such as electric vehicles and distributed generation systems based on renewable energies.

In this new scenario, power quality and the resilience of electrical networks to overcome fault conditions are critical issues.

The main aim of this Special Issue is to seek top-quality contributions that underline emerging applications and address recent breakthroughs in all aspects of “New Technologies for Smart Grids”. Potential topics include but are not limited to the following:

  • EV charging technologies.
  • Distributed generation.
  • Protection and fault detection.
  • Power quality issues.
  • Metering.
  • Blockchain.
  • Cyber security.
  • Maintenance.
  • New IT and communications technologies in smart grids.
  • AI techniques applied to distribution networks.
  • Smart appliances and electronic power conditioning devices.
  • Technology for self-healing and resilience networks.
  • Pilots, POC and demonstrations of applications of digital processing and communications to distribution networks.

Dr. Mario Mañana
Dr. Alfredo Vaccaro
Dr. Ahmed F. Zobaa
Guest Editors

Manuscript Submission Information

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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

  • Electric vehicles
  • Charging stations
  • Distributed power generation
  • Power system protection
  • Power distribution faults
  • Fault diagnosis and location
  • Renewable energy sources
  • Smart grids
  • Power quality
  • Artificial intelligence
  • Substation automation
  • Substation maintenance

Published Papers (6 papers)

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Research

23 pages, 387 KiB  
Article
A Second-Order Cone Programming Reformulation of the Economic Dispatch Problem of BESS for Apparent Power Compensation in AC Distribution Networks
by Oscar Danilo Montoya, Walter Gil-González, Federico Martin Serra, Jesus C. Hernández and Alexander Molina-Cabrera
Electronics 2020, 9(10), 1677; https://doi.org/10.3390/electronics9101677 - 14 Oct 2020
Cited by 19 | Viewed by 2653
Abstract
The problem associated with economic dispatch of battery energy storage systems (BESSs) in alternating current (AC) distribution networks is addressed in this paper through convex optimization. The exact nonlinear programming model that represents the economic dispatch problem is transformed into a second-order cone [...] Read more.
The problem associated with economic dispatch of battery energy storage systems (BESSs) in alternating current (AC) distribution networks is addressed in this paper through convex optimization. The exact nonlinear programming model that represents the economic dispatch problem is transformed into a second-order cone programming (SOCP) model, thereby guaranteeing the global optimal solution-finding due to the conic (i.e., convex) structure of the solution space. The proposed economic dispatch model of the BESS considers the possibility of injecting/absorbing active and reactive power, in turn, enabling the dynamical apparent power compensation in the distribution network. A basic control design based on passivity-based control theory is introduced in order to show the possibility of independently controlling both powers (i.e., active and reactive). The computational validation of the proposed SOCP model in a medium-voltage test feeder composed of 33 nodes demonstrates the efficiency of convex optimization for solving nonlinear programming models via conic approximations. All numerical validations have been carried out in the general algebraic modeling system. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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10 pages, 4067 KiB  
Article
Research on Simplified Model of AC/DC Hybrid Microgrid for Fault Analysis
by Tianliang Yao, Zhiwei Li, Jiping Qu, Zhaoxiong Li, Qi Zhao and Guopeng Zhao
Electronics 2020, 9(2), 358; https://doi.org/10.3390/electronics9020358 - 20 Feb 2020
Cited by 6 | Viewed by 2965
Abstract
The AC/DC hybrid microgrid, which takes into account the access requirements of AC and DC sources and loads, optimizes the structure of traditional distribution networks. The application of power electronic transformers as the core of its energy management, with electrical isolation and accurate [...] Read more.
The AC/DC hybrid microgrid, which takes into account the access requirements of AC and DC sources and loads, optimizes the structure of traditional distribution networks. The application of power electronic transformers as the core of its energy management, with electrical isolation and accurate control of the voltage, current and power flow by the control system, enables the microgrid to achieve a more flexible and stable transmission mode. Because the power electronic transformer combines the power electronic device and the high-frequency transformer, its frequent switching causes the electromagnetic transient simulation to take too long. Therefore, by simplifying control loops and converters, this paper proposes a simplified model for the microgrid system power flow and the dynamic response under exposure to a fault. The mathematical model equivalent simplification method is used in this paper. This method is concise and efficient and does not rely on the performance of a computer or change the program algorithm of the software. The simplified model was built based on PSCAD (Power System Computer Aided Design) simulation software and was carried out under short circuit fault conditions to verify its validity. The comparison of the simulation’s time consumption and accuracy shows that model simplification can significantly improve the simulation speed, with an acceptable error rate, and its dynamic response maintains good consistency with that of the detailed electromagnetic transient model. Therefore, it can be applied to the transient electromagnetic simulation fault analysis of the AC/DC hybrid microgrid. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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16 pages, 1259 KiB  
Article
Decentralized Smart Grid Voltage Control by Synchronization of Linear Multiagent Systems in the Presence of Time-Varying Latencies
by Amedeo Andreotti, Bianca Caiazzo, Alberto Petrillo, Stefania Santini and Alfredo Vaccaro
Electronics 2019, 8(12), 1470; https://doi.org/10.3390/electronics8121470 - 03 Dec 2019
Cited by 6 | Viewed by 2008
Abstract
Modern power distribution systems require reliable, self-organizing and highly scalable voltage control systems, which should be able to promptly compensate the voltage fluctuations induced by intermittent and non-programmable generators. However, their deployment in realistic operation scenarios is still an open issue due, for [...] Read more.
Modern power distribution systems require reliable, self-organizing and highly scalable voltage control systems, which should be able to promptly compensate the voltage fluctuations induced by intermittent and non-programmable generators. However, their deployment in realistic operation scenarios is still an open issue due, for example, to the presence of non-ideal and unreliable communication systems that allow each component within the power network to share information about its state. Indeed, due to technological constraints, time-delays in data acquisition and transmission are unavoidable and their effects have to be taken into account in the control design phase. To this aim, in this paper, we propose a fully distributed cooperative control protocol allowing the voltage control to be achieved despite the presence of heterogeneous time-varying latencies. The idea is to exploit the distributed intelligence along the network, so that it is possible to bring out an optimal global behavior via cooperative distributed control action that leverages both local and the outdated information shared among the devices within the power network. Detailed simulation results obtained on the realistic case study of the IEEE 30-bus test system are presented and discussed in order to prove the effectiveness of the proposed approach in the task of solving complex voltage control problems. Finally, a robustness analysis with respect to both loads variations and hard communication delays was also carried to disclose the efficiency of the approach. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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20 pages, 1016 KiB  
Article
An Economical Energy Management Strategy for Viable Microgrid Modes
by Samia Abid, Turki Ali Alghamdi, Abdul Haseeb, Zahid Wadud, Abrar Ahmed and Nadeem Javaid
Electronics 2019, 8(12), 1442; https://doi.org/10.3390/electronics8121442 - 01 Dec 2019
Cited by 16 | Viewed by 2977
Abstract
In the last couple of decades, numerous energy management strategies have been devised to mitigate the effects of greenhouse gas emission, hence introducing the concept of microgrids. In a microgrid, distributed energy generators are used. Microgrid enables a point which ameliorates in exchanging [...] Read more.
In the last couple of decades, numerous energy management strategies have been devised to mitigate the effects of greenhouse gas emission, hence introducing the concept of microgrids. In a microgrid, distributed energy generators are used. Microgrid enables a point which ameliorates in exchanging power with the main grid during different times of day. Based on the system constraints, in this work, we aim to efficiently minimize the operating cost of the microgrid and shave the power consumption peaks. For this purpose, we introduce an improved binary bat (iBBat) algorithm which helps to schedule the load demand of smart homes and energy generation from distributed generator of microgrid to the load demand and supply. The proposed energy management algorithm is applied to both grid-connected and islanded modes of the microgrid. The constraints imposed on the algorithm ensure that the load of electricity consumer does not escalate during peak hours. The simulation results are compared with BBat and binary flower pollination algorithm, which validate that the iBBat reflects substantial reduction in operating cost of microgrid. Moreover, results also show a phenomenal reduction in the peak-to-average ratio of load demand from main the main grid. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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21 pages, 717 KiB  
Article
Optimal Home Energy Demand Management Based Multi-Criteria Decision Making Methods
by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi and Tamer Khatib
Electronics 2019, 8(5), 524; https://doi.org/10.3390/electronics8050524 - 10 May 2019
Cited by 7 | Viewed by 2655
Abstract
From the growth of residential energy demands has emerged new approaches for load scheduling to realize better energy consumption by shifting the required demand in response to cost changes or incentive offers. In this paper, a hybrid method is proposed to optimize the [...] Read more.
From the growth of residential energy demands has emerged new approaches for load scheduling to realize better energy consumption by shifting the required demand in response to cost changes or incentive offers. In this paper, a hybrid method is proposed to optimize the load scheduling problem for cost and energy saving. The method comprises a multi-objective optimization differential evolution (MODE) algorithm to obtain a set of optimal solutions by minimizing the cost and peak of a load simultaneously, as a multi-objective function. Next, an integration of the analytic hierarchy process (AHP) and a technique for order preferences by similarity to ideal solution (TOPSIS) methods are used as multi-criteria decision making (MCDM) methods for sorting the optimal solutions’ set from the best to the worst, to enable the customer to choose the appropriate schedule time. The solutions are sorted based on the load peak and energy cost as multi-criteria. Data are for ten appliances of a household used for 24 h with a one-minute time slot. The results of the proposed method demonstrate both energy and cost savings of around 47% and 46%, respectively. Furthermore, the results are compared with other recent methods in the literature to show the superiority of the proposed method. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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17 pages, 1176 KiB  
Article
Two-Stage Energy Management of Multi-Smart Homes With Distributed Generation and Storage
by Efe Isa Tezde, Halil Ibrahim Okumus and Ibrahim Savran
Electronics 2019, 8(5), 512; https://doi.org/10.3390/electronics8050512 - 08 May 2019
Cited by 6 | Viewed by 3631
Abstract
This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such [...] Read more.
This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such as PV and wind turbines, distributed storage systems (DSS) such as electric vehicle (EV), and batteries. HEMS organizes the controllable appliances considering user preferences, amount of energy generated/stored and electricity price. A group of optimum consumption schedules for each HEMS is calculated by a Genetic Algorithm (GA). In the second stage, a neighborhood energy management system (NEMS) is established based on Bayesian Game (BG). In this game, HEMSs are players and their pre-determined optimal schedules are their actions. NEMS regulates the total power fluctuations by allowing the energy transfer among households. In the proposed algorithm, HEMS decreases the electricity cost of the users, while NEMS flats the load curve of the neighborhood to prevent overloading of the distribution transformer. The proposed HEMS and NEMS models are implemented from scratch. A survey of 250 participants was conducted to determine user habits. The results of the survey and the proposed system were compared. In conclusion, the proposed hybrid energy management system saves power by up to 25% and decreases cost by 8.7% on average. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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