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Energies
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Optimal Operation and Control of Microgrid Systems
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Optimal Operation and Control of Microgrid Systems

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 July 2020) | Viewed by 5964

Special Issue Editor

Prof. Dr. Hak-Man Kim

E-Mail Website
Guest Editor
Department of Electrical Engineering, Incheon National University, Incheon 13557, Korea
Interests: microgrid operation & control; AI applications in microgrids; micro-energy networks; wind farm control

Special Issue Information

Dear Colleagues,

Optimal operation and control of microgrids are required to operate the microgrids in a stable and an economic way. The upper level control (operation) is required for the economic scheduling and dispatch of the power sources. At the operation level, integration of demand response, electric vehicles, and energy storage are considered, and the optimization is carried out with several objectives, such as cost minimization, emission minimization, service reliability maximization, etc. The lower level control is responsible for maintaining stabilities and improving the power qualities of microgrids. Advanced control techniques play an important role in achieving a reliable, robust, and economic operation of microgrid systems. Optimal operation and control of microgrids has been an active research area for the last decade.

This Special Issue will deal with novel optimization and control techniques for microgrids. Topics of interest for publication include, but are not limited to:

  • Optimial operation of microgrids in grid-connected and islanded modes
  • Optimal operation for off-grid microgrids
  • Integration of demand respons and electric vehicles in microgrids
  • Impact of uncertainties on operation of microgrids
  • Integration of renewables and energy storage in microgrids
  • Combined cooling, heat, and power management in microgrids
  • AI-based microgrid operation and control
  • Inverter-based distributed generator
  • Advanced control techniques for inverter-based distributed generators in microgrids
  • Centralized, decentralized, and distributed control of microgrids
  • Microgrid stability

Prof. Dr. Hak-Man Kim
Guest Editor

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
  • Demand response
  • Electric vehicles
  • Energy storage system
  • Grid-connected and islanded modes
  • Off-grid microgrids
  • AI in microgrids
  • Microgrid control
  • Distributed control
  • Microgrid stability

Published Papers (2 papers)

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Research

31 pages, 7069 KiB  
Article
Functional Analysis of the Microgrid Concept Applied to Case Studies of the Sundom Smart Grid
by Katja Sirviö, Kimmo Kauhaniemi, Aushiq Ali Memon, Hannu Laaksonen and Lauri Kumpulainen
Energies 2020, 13(16), 4223; https://doi.org/10.3390/en13164223 - 15 Aug 2020
Cited by 10 | Viewed by 3630
Abstract
The operation of microgrids is a complex task because it involves several stakeholders and controlling a large number of different active and intelligent resources or devices. Management functions, such as frequency control or islanding, are defined in the microgrid concept, but depending on [...] Read more.
The operation of microgrids is a complex task because it involves several stakeholders and controlling a large number of different active and intelligent resources or devices. Management functions, such as frequency control or islanding, are defined in the microgrid concept, but depending on the application, some functions may not be needed. In order to analyze the required functions for network operation and visualize the interactions between the actors operating a particular microgrid, a comprehensive use case analysis is needed. This paper presents the use case modelling method applied for microgrid management from an abstract or concept level to a more practical level. By utilizing case studies, the potential entities can be detected where the development or improvement of practical solutions is necessary. The use case analysis has been conducted from top-down until test use cases by real-time simulation models. Test use cases are applied to a real distribution network model, Sundom Smart Grid, with measurement data and newly developed controllers.. The functional analysis provides valuable results when studying several microgrid functions operating in parallel and affecting each other. For example, as shown in this paper, ancillary services provided by an active customer may mean that both the active power and reactive power from customer premises are controlled at the same time by different stakeholders. Full article
(This article belongs to the Special Issue Optimal Operation and Control of Microgrid Systems)
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14 pages, 4657 KiB  
Article
Distributed Operation of Microgrids Considering Secondary Frequency Restoration Based on the Diffusion Algorithm
by Su-Been Hong, Thai-Thanh Nguyen, Jinhong Jeon and Hak-Man Kim
Energies 2020, 13(12), 3207; https://doi.org/10.3390/en13123207 - 20 Jun 2020
Cited by 2 | Viewed by 1939
Abstract
This paper proposes a distributed control of the microgrid (MG) system based on the diffusion algorithm. Unlike the existing decentralized strategy that focuses on the economic operation of the MG system, the proposed strategy performs secondary frequency regulation in addition to the optimization [...] Read more.
This paper proposes a distributed control of the microgrid (MG) system based on the diffusion algorithm. Unlike the existing decentralized strategy that focuses on the economic operation of the MG system, the proposed strategy performs secondary frequency regulation in addition to the optimization of the MG system. The hierarchical control technique is employed in this study, where the primary layer is responsible for power control and the secondary layer is responsible for the frequency control and economic operation of the MG system. A tested MG system with four distributed generations (DGs) is considered. Three types of communication topologies are evaluated in this study, which are line, ring, and full topologies. The proposed controller is compared to the conventional consensus controller to show the effectiveness of the proposed diffusion controller. Simulation results show that the proposed diffusion strategy improves the convergence speed of the distributed control, resulting in the improvement of power responses and frequency quality of the MG system. The tested system is implemented in the MATLAB/Simulink environment to show the feasibility of the proposed diffusion controller. Full article
(This article belongs to the Special Issue Optimal Operation and Control of Microgrid Systems)
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