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Planning and Operation of Microgrids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 26835

Special Issue Editors

Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 22012, Korea
Interests: resilience of power systems; integration of EVs and DR; microgrid operation; energy management in buildings; renewables and CHP systems; distribution automation
Special Issues, Collections and Topics in MDPI journals
Department of Electrical Engineering, School of Engineering, State University of New York (SUNY), Maritime College, 6 Pennyfield Avenue, Throggs Neck, New York, NY 10465, USA
Interests: deep learning; deep reinforcement learning; distributed energy resource integration; energy management system; operation and control of microgrid; optimization
Special Issues, Collections and Topics in MDPI journals
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Interests: control of power electronics; decentralized energy systems; energy storage; renewable energy systems.ms.

Special Issue Information

Dear Colleagues,

It is our pleasure to invite submissions to the Special Issue on “Planning and Operation of Microgrids”.

In recent years, microgrids have attracted significant attention due to their ability to sustain the penetration of renewables and supply power locally during emergencies. In order to achieve those benefits, microgrids need to be optimally planned and operated. Specifically, microgrids need to be planned and economically operated during normal operations while maximizing service reliability/resiliency during system contingencies. Planning and operation of microgrids can be realized via mathematical formulations using either centralized or decentralized methods. The recent advancements in AI, especially learning methods, have enabled us to carry out these tasks in a better and more efficient manner. In this Special Issue, we are looking for novel methods, algorithms, and technologies to enhance energy efficiency as well as to handle the aforementioned problems in the planning and/or operation of microgrids. Review and survey articles on the following topics are also encouraged for submission.

Topics of interest for publication include, but are not limited to:

- Energy management systems for microgrids

- Demand-side management and demand response

- Energy management of combined cooling, heating, and power systems

- Applications of artificial intelligence in planning and operation of microgrids

- Resilience enhancement through/for microgrids

- Multiagent systems for microgrids

- Integration of renewables and EVs in microgrids

- Optimal operation of energy storage systems

- Optimal economic dispatch of microgrids

- Self-healing strategies for islanded microgrids

- Off-grid microgrids and power systems

- Centralized, decentralized, and hierarchical operation of microgrids

Dr. Akhtar Hussain
Dr. Van-Hai Bui
Dr. Leong Kit Gan
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. Energies 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 2600 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

  • microgrid
  • microgrid operation
  • distributed energy resources
  • demand response
  • electric vehicles
  • microenergy networks
  • renewable energy resources
  • r esiliency
  • self-healing
  • energy storage system
  • grid-connected and islanded modes
  • artificial intelligent in microgrids
  • multiagent system
  • optimization.

Published Papers (6 papers)

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Research

Jump to: Review

16 pages, 2811 KiB  
Article
Modeling Residential Electricity Consumption from Public Demographic Data for Sustainable Cities
by Muhammad Ali, Krishneel Prakash, Carlos Macana, Ali Kashif Bashir, Alireza Jolfaei, Awais Bokhari, Jiří Jaromír Klemeš and Hemanshu Pota
Energies 2022, 15(6), 2163; https://0-doi-org.brum.beds.ac.uk/10.3390/en15062163 - 16 Mar 2022
Cited by 11 | Viewed by 2343
Abstract
Demographic factors, statistical information, and technological innovation are prominent factors shaping energy transitions in the residential sector. Explaining these energy transitions requires combining insights from the disciplines investigating these factors. The existing literature is not consistent in identifying these factors, nor in proposing [...] Read more.
Demographic factors, statistical information, and technological innovation are prominent factors shaping energy transitions in the residential sector. Explaining these energy transitions requires combining insights from the disciplines investigating these factors. The existing literature is not consistent in identifying these factors, nor in proposing how they can be combined. In this paper, three contributions are made by combining the key demographic factors of households to estimate household energy consumption. Firstly, a mathematical formula is developed by considering the demographic determinants that influence energy consumption, such as the number of persons per household, median age, occupancy rate, households with children, and number of bedrooms per household. Secondly, a geographical position algorithm is proposed to identify the geographical locations of households. Thirdly, the derived formula is validated by collecting demographic factors of five statistical regions from local government databases, and then compared with the electricity consumption benchmarks provided by the energy regulators. The practical feasibility of the method is demonstrated by comparing the estimated energy consumption values with the electricity consumption benchmarks provided by energy regulators. The comparison results indicate that the error between the benchmark and estimated values for the five different regions is less than 8% (7.37%), proving the efficacy of this method in energy consumption estimation processes. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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6 pages, 291 KiB  
Communication
Uncovering Hidden Factors in Electricity Consumption Based on Gaussian Mixture Estimation
by Shiwen Liao, Lu Wei and Wencong Su
Energies 2022, 15(1), 319; https://0-doi-org.brum.beds.ac.uk/10.3390/en15010319 - 04 Jan 2022
Viewed by 988
Abstract
Load characteristics play an essential role in the planning of power generation and distribution. Various undiscovered factors, which could be socioeconomic, geographic, or climatic, make it possible to describe the electricity demand by a multimodal distribution. This letter proposes a novel method based [...] Read more.
Load characteristics play an essential role in the planning of power generation and distribution. Various undiscovered factors, which could be socioeconomic, geographic, or climatic, make it possible to describe the electricity demand by a multimodal distribution. This letter proposes a novel method based on multimodal distributions to characterize the hidden factors in electricity consumption. Consequently, a new approach is developed to evaluate the impact of the underlying factors of electricity consumption. Some quantifiable and predictable factors are analyzed in developing multimodal distribution to describe the expected demand. Simulations based on synthetic and real-world data have been conducted to demonstrate the usefulness and robustness of the proposed method. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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19 pages, 4134 KiB  
Article
Optimal Sizing of Energy Storage System for Operation of Wind Farms Considering Grid-Code Constraints
by Van-Hai Bui, Xuan Quynh Nguyen, Akhtar Hussain and Wencong Su
Energies 2021, 14(17), 5478; https://0-doi-org.brum.beds.ac.uk/10.3390/en14175478 - 02 Sep 2021
Cited by 5 | Viewed by 1774
Abstract
Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also [...] Read more.
Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wind farm operators to find out the optimal size of the energy storage systems considering grid-code constraints and the local information of wind farms. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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22 pages, 1608 KiB  
Article
Rightsizing the Design of a Hybrid Microgrid
by Daniel Reich and Giovanna Oriti
Energies 2021, 14(14), 4273; https://0-doi-org.brum.beds.ac.uk/10.3390/en14144273 - 15 Jul 2021
Cited by 8 | Viewed by 2164
Abstract
Selecting the sizes of distributed energy resources is a central planning element when designing a microgrid. Decision makers may consider several important factors, including, but not limited to, capacity, cost, reliability and sustainability. We introduce a method for rightsizing capacity that presents a [...] Read more.
Selecting the sizes of distributed energy resources is a central planning element when designing a microgrid. Decision makers may consider several important factors, including, but not limited to, capacity, cost, reliability and sustainability. We introduce a method for rightsizing capacity that presents a range of potential microgrid design solutions, allowing decision makers to weigh their upsides and downsides based on a variety of measurable factors. We decouple component-specific modeling assumptions, energy management system logic and objective measurements from our simulation-based nested binary search method for rightsizing to meet power loads. In doing so, we develop a flexible, customizable and extensible approach to microgrid design planning. Aspects which have traditionally been incorporated directly in optimization-centric frameworks, such as resilience and reliability, can be treated as complementary analyses in our decoupled approach. This enables decision makers to gain exposure to a wide range of relevant information and actively participate in the microgrid design assessment process. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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20 pages, 4092 KiB  
Article
Optimal Operation of Networked Microgrids for Enhancing Resilience Using Mobile Electric Vehicles
by Asfand Yar Ali, Akhtar Hussain, Ju-Won Baek and Hak-Man Kim
Energies 2021, 14(1), 142; https://0-doi-org.brum.beds.ac.uk/10.3390/en14010142 - 29 Dec 2020
Cited by 23 | Viewed by 3002
Abstract
The increased intensity and frequency of natural disasters have attracted the attention of researchers in the power sector to enhance the resilience of power systems. Microgrids are considered as a potential solution to enhance the resilience of power systems using local resources, such [...] Read more.
The increased intensity and frequency of natural disasters have attracted the attention of researchers in the power sector to enhance the resilience of power systems. Microgrids are considered as a potential solution to enhance the resilience of power systems using local resources, such as renewable energy sources, electric vehicles (EV), and energy storage systems. However, the deployment of an additional storage system for resilience can increase the investment cost. Therefore, in this study, the usage of existing EVs in microgrids is proposed as a solution to increase the resilience of microgrids with outages without the need for additional investment. In the case of contingencies, the proposed algorithm supplies energy to islanded microgrids from grid-connected microgrids by using mobile EVs. The process for the selection of EVs for supplying energy to islanded microgrids is carried out in three steps. Firstly, islanded and networked microgrids inform the central energy management system (CEMS) about the required and available energy stored in EVs, respectively. Secondly, CEMS determines the microgrids among networked microgrids to supply energy to the islanded microgrid. Finally, the selected microgrids determine the EVs for supplying energy to the islanded microgrid. Simulations have shown the effectiveness of the proposed algorithm in enhancing the resilience of microgrids even in the absence of power connection among microgrids. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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Review

Jump to: Research

32 pages, 796 KiB  
Review
A Review of DC-AC Converters for Electric Vehicle Applications
by Khairy Sayed, Abdulaziz Almutairi, Naif Albagami, Omar Alrumayh, Ahmed G. Abo-Khalil and Hedra Saleeb
Energies 2022, 15(3), 1241; https://0-doi-org.brum.beds.ac.uk/10.3390/en15031241 - 08 Feb 2022
Cited by 22 | Viewed by 14946
Abstract
This paper comprehensively reviews the current status of multidisciplinary technologies in electric vehicles. Because the electric vehicle market will expand dramatically in the coming few years, research accomplishments in power electronics technology for electric vehicles will be highly attractive. Challenges in power electronics [...] Read more.
This paper comprehensively reviews the current status of multidisciplinary technologies in electric vehicles. Because the electric vehicle market will expand dramatically in the coming few years, research accomplishments in power electronics technology for electric vehicles will be highly attractive. Challenges in power electronics technology for driving electric vehicles, charging batteries, and circuit topologies are being explored. This paper aims primarily to address the practical issues of the future electric vehicles and help researchers obtain an overview of the latest techniques in electric vehicles, focusing on power electronics-based solutions for both current and future electric vehicle technologies. In this work, different medium-and high-voltage DC-AC inverter topologies are investigated and compared in terms of power losses and component requirements. Recent research on electric vehicle power converters is also discussed, with highlighting on soft-switching and multilevel inverters for electric vehicle motor drives. In this paper, a methodical overview and general classification of DC-AC power converters are presented. In specific topologies, drawbacks such as voltage stresses on active switches and control complications may occur, which can make them difficult for immediate commercialization. However, various modified circuit topologies have been recommended to overcome these drawbacks and enhance the system performance. Full article
(This article belongs to the Special Issue Planning and Operation of Microgrids)
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