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Optimal Dispatch of Microgrid and Microgrid Cluster

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 (30 July 2022) | Viewed by 3329

Special Issue Editors

School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 15000, China
Interests: power electronics technology and applications; electric drive automation system; information network appliance and its intelligent control technology; lighting electronic technology; grid quality control technology; AC servo motor system
School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 15000, China
Interests: operation and control of microgrids and multi-microgrids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microgrids offer a great opportunity to integrate renewable energies and energy storage into DC and AC power systems in a more efficient and smart manner. Moreover, by connecting multiple microgrids to constitute a cluster, the efficiency of the power system can be further improved, and the utilization of renewable energies can be maximized thanks to the power flow among microgrids. Recently, advanced energy forecast approaches and intelligent optimization algorithms have been applied to distributed power systems. Meanwhile, the energy management and power dispatch of microgrids considering multifactors, e.g., carbon emission and user side response, is an important way to improve system performance. This Special Issue aims at encouraging researchers to address these important issues and other challenges in the optimal dispatch of microgrids and microgrids cluster as follows:

  • Optimal operation and economic dispatch of microgrids;
  • Hierarchical optimal control techniques for microgrids;
  • Advanced control with multifunctional features for microgrids;
  • Multiobjective optimization techniques for power management in microgrids;
  • Advanced power forecast approach for microgrids;
  • Energy management system for microgrid cluster;
  • Demand side management and demand response;
  • Optimal planning and operation of microgrid clusters.

Prof. Dr. Dianguo Xu
Dr. Panbao Wang
Guest Editors

Manuscript Submission Information

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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

  • microgrids
  • microgrids cluster
  • hierarchical control system
  • energy management systems
  • economic dispatch
  • power forecasting
  • demand-side management
  • metaheuristic algorithms

Published Papers (2 papers)

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Research

20 pages, 2505 KiB  
Article
An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids
by Guodong Liu, Maximiliano F. Ferrari, Thomas B. Ollis and Kevin Tomsovic
Energies 2022, 15(19), 6971; https://0-doi-org.brum.beds.ac.uk/10.3390/en15196971 - 23 Sep 2022
Cited by 8 | Viewed by 1323
Abstract
An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system [...] Read more.
An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids. Full article
(This article belongs to the Special Issue Optimal Dispatch of Microgrid and Microgrid Cluster)
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22 pages, 4251 KiB  
Article
A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster
by Mohamed Zaery, Panbao Wang, Wei Wang and Dianguo Xu
Energies 2022, 15(11), 3994; https://0-doi-org.brum.beds.ac.uk/10.3390/en15113994 - 28 May 2022
Cited by 2 | Viewed by 1362
Abstract
A novel, fully distributed controller with a rapid convergence rate is developed to ensure the optimal loading dispatch for interconnected DC MGs. It comprises local and global-control levels, handling the economic load allocations in a finite-time manner, for distinct MGs and cluster of [...] Read more.
A novel, fully distributed controller with a rapid convergence rate is developed to ensure the optimal loading dispatch for interconnected DC MGs. It comprises local and global-control levels, handling the economic load allocations in a finite-time manner, for distinct MGs and cluster of MGs, respectively. The local-control layer guarantees MG’s economic operation by matching the incremental costs (ICs) of all DGs, respecting the power equilibrium among generations and demands, DGs’ generation limits, as well as the transmission line losses. Furthermore, the economic operation of battery energy sources is considered, in the optimization problem, to strengthen the overall reliability and maximize energy arbitrage. The global controller adjusts MGs’ voltage references to determine the optimal exchanged power, between MGs, for reducing the global total generation cost (TGC). A rigorous analysis is developed to confirm the stable convergence of the developed controller. Extensive simulation case studies demonstrate the superiority of the proposed control system. Full article
(This article belongs to the Special Issue Optimal Dispatch of Microgrid and Microgrid Cluster)
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