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Operational Optimization of Networked Microgrids

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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 October 2022) | Viewed by 9214

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Special Issue Editors

Dr. Nanpeng Yu

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Guest Editor

Department of Electrical and Computer Engineering, University of California, Riverside, Riverside, CA 92521, USA
Interests: machine learning; big data analytics; smart grid technology; electricity market; water energy nexus

Dr. Mikhail A. Bragin

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Guest Editor

Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Interests: power systems; mixed-integer programming; machine learning; nonlinear optimization; operations research

Dr. Peng Li

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: distributed energy and microgrid; operation analysis and optimization control of active distribution network; power system transient simulation and calculation method

Special Issue Information

Dear Colleagues,

The widespread and rapid proliferation of distributed energy resources such as wind and solar has a far-reaching impact on traditional power system paradigms and broad implications for the entire power grid. A microgrid can disconnect from the central grid and operate independently, thereby allowing the continued supply of power to customers when a storm or other disastrous event causes an outage of the main grid. Under normal operations, microgrids create energy for local customers, thereby avoiding the need to deliver electricity from power plants over long distances via traditional transmission lines, which typically results in huge losses. It is expected that the number of microgrids will grow to form a network of microgrids to avoid cascading failures inherent to the traditional grid and to improve the resilience and robustness of the entire system. Microgrids can thus provide a great way to enhance local reliability. The pressing concerns when considering microgrids are the following: due to the presence of the intermittent renewables, 1) the time resolution of the associated operation optimization problems can no longer be 1 hour as in traditional grids, but rather, much shorter time periods are advised to accommodate for the fluctuations in demand; 2) the number of stochastic levels to capture low-probability high-impact events is expected to grow significantly; and 3) nonlinear AC power flow is needed to obtain feasible schedules of the microgrids.

This Special Issue is focused on 1) identifying current and potential issues and advantages of networked microgrids; and 2) developing efficient solutions methodologies to efficiently manage and coordinate networked microgrids.

Potential topics include, but are not limited to:
Networked Microgrids:

Energy storage systems and PV panels
Demand response
Microgrid fault management
Intelligent energy management systems
AC Power Flow
Stochastic modeling
Wind/solar integration
Cybersecure operations of microgrids

Operation Optimization Methods as Related to Networked Microgrids:

Linear and nonlinear programming
Integer and mixed-integer programming
Stochastic programming
Lagrangian relaxation-based methods
Other decomposition and coordination-based methods
Machine learning
Multi-objective optimization
Parallel/distributed computing

Dr. Nanpeng Yu
Dr. Mikhail A. Bragin
Prof. Dr. Peng Li
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

Energy storage systems and PV panels
Demand response
Microgrid fault management
Intelligent energy management systems
AC Power Flow
Stochastic modeling
Wind/solar integration
Droop control
Software-defined microgrids
Cybersecure operations of microgrids
Linear and nonlinear programming
Integer and mixed-integer programming
Stochastic programming
Lagrangian relaxation-based methods
Other decomposition and coordination-based methods
Machine learning
Multi-objective optimization
Parallel/distributed computing

Published Papers (4 papers)

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Research

13 pages, 1154 KiB

Open AccessEditor’s ChoiceArticle

Adaptive Resilient Control of AC Microgrids under Unbounded Actuator Attacks

by Shan Zuo, Yi Zhang and Yichao Wang

Energies 2022, 15(20), 7458; https://doi.org/10.3390/en15207458 - 11 Oct 2022

Cited by 3 | Viewed by 1221

Abstract

Existing secondary control methods using fault-tolerant and/or

H_{\infty}

Existing secondary control methods using fault-tolerant and/or

H_{\infty}

control techniques for multi-inverter microgrids generally assume bounded faults and/or disturbances. Herein, we study unknown unbounded attacks on the input channels of both frequency and voltage control loops of inverters that could deteriorate the cooperative performance and affect the microgrid stability. We propose a fully distributed attack-resilient control framework using adaptive control techniques that, using stability analysis with Lyapunov techniques, are shown to preserve the uniformly ultimately bounded consensus for frequency regulation and voltage containment. Moreover, the ultimate bound can be set by adjusting the tuning parameters. The proposed result is validated for a modified IEEE 34-bus test feeder benchmark system augmented with four inverters. Full article

(This article belongs to the Special Issue Operational Optimization of Networked Microgrids)

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13 pages, 575 KiB

Open AccessArticle

Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints

by Mikhail A. Bragin, Bing Yan, Akash Kumar, Nanpeng Yu and Peng Zhang

Energies 2022, 15(10), 3662; https://doi.org/10.3390/en15103662 - 17 May 2022

Viewed by 1665

Abstract

Micro-grids’ operations offer local reliability; in the event of faults or low voltage/frequency events on the utility side, micro-grids can disconnect from the main grid and operate autonomously while providing a continued supply of power to local customers. With the ever-increasing penetration of renewable generation, however, operations of micro-grids become increasingly complicated because of the associated fluctuations of voltages. As a result, transformer taps are adjusted frequently, thereby leading to fast degradation of expensive tap-changer transformers. In the islanding mode, the difficulties also come from the drop in voltage and frequency upon disconnecting from the main grid. To appropriately model the above, non-linear AC power flow constraints are necessary. Computationally, the discrete nature of tap-changer operations and the stochasticity caused by renewables add two layers of difficulty on top of a complicated AC-OPF problem. To resolve the above computational difficulties, the main principles of the recently developed “

l_{1}

-proximal” Surrogate Lagrangian Relaxation are extended. Testing results based on the nine-bus system demonstrate the efficiency of the method to obtain the exact feasible solutions for micro-grid operations, thereby avoiding approximations inherent to existing methods; in particular, fast convergence of the method to feasible solutions is demonstrated. It is also demonstrated that through the optimization, the number of tap changes is drastically reduced, and the method is capable of efficiently handling networks with meshed topologies. Full article

(This article belongs to the Special Issue Operational Optimization of Networked Microgrids)

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24 pages, 1052 KiB

Open AccessArticle

Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies

by José Luis Ruiz Duarte and Neng Fan

Energies 2022, 15(7), 2350; https://doi.org/10.3390/en15072350 - 23 Mar 2022

Cited by 5 | Viewed by 2224

Abstract

The international community has set ambitious targets to replace the use of fossil fuels for electricity generation with renewable energy sources. The use of large-scale (e.g., solar farms) and small-scale solutions (e.g., onsite green technologies) represents one way to achieve these goals. This paper presents a mathematical optimization framework to coordinate the energy decisions between the distribution network and the networked microgrids embedded within it. Utility-scale renewable and conventional generators are considered in the distribution network, while the microgrids include onsite renewable generation and energy storage. The distribution network operator utilizes demand-side management policies to improve the network’s efficiency, and the microgrids operate under these programs by reducing their energy usage, scheduling the electricity usage under dynamic tariffs, and supplying energy to the grid. The uncertainty of renewable energy sources is addressed by robust optimization. The decisions of the distribution network and the microgrids are made independently, whereas the proposed collaboration scheme allows for the alignment of the systems’ objectives. A case study is analyzed to show the capability of the model to assess multiple configurations, eliminating the necessity of load shedding, and increasing the power supplied by the microgrids (22.3 MW) and the renewable energy share by up to 5.03%. Full article

(This article belongs to the Special Issue Operational Optimization of Networked Microgrids)

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19 pages, 2315 KiB

Open AccessArticle

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

by Guodong Liu, Thomas B. Ollis, Maximiliano F. Ferrari, Aditya Sundararajan and Kevin Tomsovic

Energies 2022, 15(6), 2249; https://doi.org/10.3390/en15062249 - 19 Mar 2022

Cited by 13 | Viewed by 1785

Abstract

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply. Full article

(This article belongs to the Special Issue Operational Optimization of Networked Microgrids)

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