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Special Issue "Advanced Control in Microgrid Systems"

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

Deadline for manuscript submissions: 10 July 2019

Special Issue Editor

Guest Editor
Prof. Dr. Andrey V. Savkin

University of New South Wales, School of Electrical Engineering and Telecommunications, Sydney, NSW, Australia
Website | E-Mail
Interests: robot navigation; deployment of drones; control of power systems; robust control and filtering; hybrid dynamical systems; control engineering; biomedical engineering

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of Energies on the subject area of “Advanced Control in Microgrid Systems”. With the increasing integration of renewable energy and the development of a smart grid, the topic of microgrids has attracted a lot of attention in recent years.

Microgrids are distributed electric power systems that autonomously coordinate power generations and demands. Modern microgrids often include renewable energy generations, such as wind and solar, supported by distributed energy storage systems. The distributed nature of microgrids and the uncertain, intermittent nature of power demands and renewable energy generations pose significant challenges in the operation of microgrids. Advanced methods of modern control play an important role in achieving a reliable, robust, secure, and cost-effective functioning of microgrid systems. Researchers and engineers worldwide are working together to develop novel and efficient tools of control in microgrids. This Special Issue is focused on new developments in the field of advanced control in microgrid systems.

Potential topics include, but are not limited to, the following:

Model predictive control of microgrid systems;
Robust control of microgrid systems;
Optimization of microgrids;
Control of battery energy storage systems;
Sliding mode control of microgrid systems;
Multi-agent systems approach to control of microgrids;
Advanced control systems for market-oriented energy storage dispatch;
Control of microgrid systems with high penetrations of wind power;
Control of microgrid systems with high penetrations of solar power;
Optimization and control of microgrid systems with thermostatically controlled loads;
Minimizing the energy cost for microgrid systems;
Control of microgrid systems with communication delays.

Prof. Dr. Andrey V. Savkin
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 papers will be 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 1800 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

  • Microgrids
  • Energy storage systems
  • Modern control
  • Robust control
  • Sliding mode control
  • Optimization of microgrids
  • Renewable generation
  • Wind energy
  • Solar energy
  • Nonlinear control
  • Optimal control
  • Smart grid
  • Microgrids with thermostatically controlled loads
  • Market-oriented energy storage dispatch

Published Papers (4 papers)

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Research

Open AccessArticle
Robust Control Method for DC Microgrids and Energy Routers to Improve Voltage Stability in Energy Internet
Energies 2019, 12(9), 1622; https://doi.org/10.3390/en12091622
Received: 23 March 2019 / Revised: 23 April 2019 / Accepted: 23 April 2019 / Published: 29 April 2019
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Abstract
The energy internet (EI) is a wide area power network that efficiently combines new energy technology and information technology, resulting in bidirectional on-demand power transmission and rational utilization of distributed energy resources (DERs). Since the stability of local network is a prerequisite for [...] Read more.
The energy internet (EI) is a wide area power network that efficiently combines new energy technology and information technology, resulting in bidirectional on-demand power transmission and rational utilization of distributed energy resources (DERs). Since the stability of local network is a prerequisite for the normal operation of the entire EI, the direct current (DC) bus voltage stabilization for each individual DC microgrid (MG) is a core issue. In this paper, the dynamics of the EI system is modeled with a continuous stochastic system, which simultaneously considers related time-varying delays and norm-bounded modeling uncertainty. Meanwhile, the voltage stabilization issue is converted into a robust H control problem solved via a linear matrix inequality approach. To avoid the situation of over-control, constraints are set in controllers. The problem of finding a balance between voltage regulation performance and constraints for the controllers was also extensively investigated. Finally, the efficacy of the proposed methods is evaluated with numerical simulations. Full article
(This article belongs to the Special Issue Advanced Control in Microgrid Systems)
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Open AccessArticle
An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch
Energies 2019, 12(8), 1457; https://doi.org/10.3390/en12081457
Received: 16 March 2019 / Revised: 9 April 2019 / Accepted: 12 April 2019 / Published: 17 April 2019
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Abstract
This work presents the operation of an autonomous direct current (DC) DC microgrid for residential house controlled by an energy management system based on low complexity fuzzy logic controller of only 25-rules to manage the power flow that supply house load demand. The [...] Read more.
This work presents the operation of an autonomous direct current (DC) DC microgrid for residential house controlled by an energy management system based on low complexity fuzzy logic controller of only 25-rules to manage the power flow that supply house load demand. The microgrid consists of photovoltaic (PV), wind turbine, fuel cell, battery energy storage and diesel generator. The size of the battery energy storage is determined based on the battery sizing algorithm depending on the generation of renewables during all seasons of the year in the eastern region of Saudi Arabia. Two scenarios are considered in this work. In the first scenario: the microgrid consists of solar PV, wind turbine, battery energy storage and fuel cell. The fuzzy logic controller is optimized using an artificial bee colony technique in order to increase the system energy saving efficiency and to reduce the cost. In the second scenario: wind turbine is replaced by a diesel generator, also the rated power of the fuel cell is reduced. In this scenario, a new method is proposed to reduce the generation cost of the dispatchable sources in the microgrid by considering economic dispatch within the optimized fuzzy logic energy management system. To obtain the most suitable technique for solving the economic dispatch problem, three optimization techniques were used which are particle swarm optimization, genetic algorithm and artificial bee colony based on real environmental data and real house load demand. A comparison in terms of energy saving between the two scenarios and a comparison in terms of cost reduction between conventional economic dispatch method and the proposed method are presented. Full article
(This article belongs to the Special Issue Advanced Control in Microgrid Systems)
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Open AccessArticle
Economic Load Dispatch of a Grid-Tied DC Microgrid Using the Interior Search Algorithm
Energies 2019, 12(4), 634; https://doi.org/10.3390/en12040634
Received: 18 December 2018 / Revised: 13 February 2019 / Accepted: 13 February 2019 / Published: 16 February 2019
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Abstract
This paper presents the effectiveness of the interior search algorithm in economic power scheduling of a grid-tied DC microgrid with renewable generation (wind and photovoltaic) and battery energy storage. The study presents the modelling and simulation of various DC/DC converters for tracking maximum [...] Read more.
This paper presents the effectiveness of the interior search algorithm in economic power scheduling of a grid-tied DC microgrid with renewable generation (wind and photovoltaic) and battery energy storage. The study presents the modelling and simulation of various DC/DC converters for tracking maximum power from wind and photovoltaic sources and the bidirectional power flow of battery energy storage. The DC microgrid and its controllers were modelled and simulated in MATLAB/Simulink. The generating units were dispatched economically using the interior search algorithm with the objective to minimize the operating cost of the microgrid. The simulated results verify the effectiveness of the interior search algorithm as the daily cost of microgrid operation was reduced by 11.25%. Full article
(This article belongs to the Special Issue Advanced Control in Microgrid Systems)
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Open AccessArticle
Control Design, Stability Analysis and Experimental Validation of New Application of an Interleaved Converter Operating as a Power Interface in Hybrid Microgrids
Energies 2019, 12(3), 437; https://doi.org/10.3390/en12030437
Received: 24 December 2018 / Revised: 24 January 2019 / Accepted: 25 January 2019 / Published: 30 January 2019
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Abstract
This paper presents a new and specific use of a bidirectional interleaved converter to perform a power interface in hybrid microgrids. The converter is responsible for regulating the power flow between the direct-current (DC) microgrid and the rest of the hybrid microgrid by [...] Read more.
This paper presents a new and specific use of a bidirectional interleaved converter to perform a power interface in hybrid microgrids. The converter is responsible for regulating the power flow between the direct-current (DC) microgrid and the rest of the hybrid microgrid by controlling the DC microgrid voltage. The authors present a detailed modeling of the mentioned system in order to develop the system control design and a stability analysis. In addition, the authors propose a new control design strategy aiming at improving the voltage control disturbance rejection characteristic, while maintaining a good dynamic behavior regarding the reference tracking functionality. In this hybrid microgrid topology, a back-to-back converter connects the main grid to the AC microgrid. The main objective of this converter is to provide a high-power-quality voltage to critical and sensitive loads connected to the microgrid. The interleaved converter adjusts the DC microgrid voltage according to the operational voltage of the back-to-back converter DC link. In the DC microgrid case, the variation of load and generation connection could lead to serious voltage sag and oscillations that could be harmful to the sensitive loads. The voltage controller must be capable of rejecting these disturbances in order to maintain a high-power-quality voltage. Furthermore, experimental results are provided in order to validate this specific application of the interleaved converter and the presented control design strategy. Full article
(This article belongs to the Special Issue Advanced Control in Microgrid Systems)
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