Control and Optimization of Networked Microgrids

Topic Information

Dear Colleagues,

The microgrid, as an indispensable part of the smart grid, has received dramatically increasing attention during the past three decades. With prosperous development in distributed generations, the microgrid has been deemed to be an effective solution for future energy systems due to its prominent role in the accommodation of intermittent renewable energy. In particular, networked microgrids have emerged in recent years due to their capability to counteract the strong volatility of new energy, remain stable and provide optimal operation due to mutual support between multiple adjacent subgrids. Control and optimization are the most significant technologies in the operation of networked microgrids. The control and optimization of networked microgrids not only require the source–load coordination inside each subgrid, but also demand the coordinated interaction between multiple subgrids. This is extremely difficult when a large amount of subgrids are participating, which is becoming inevitable for future energy systems. This topic aims to collect the latest developments in the control and optimization of networked microgrids. We are pleased to invite the research community to submit their contributions on the following topics which include, but are not limited to, the following:

• Distributed/decentralized control of networked microgrids;
• Stability analysis of networked microgrids with renewable energy resources;
• Distributed/decentralized energy management of networked microgrids;
• Control and optimization of AC/DC microgrid;
• Cyber-physical networked microgrids;
• Energy trading of networked microgrids;
• Integrated energy systems;
• Virtual power plant considering networked microgrids;
• AI application in networked microgrids;
• Demonstrated projects regarding networked microgrids.

Prof. Dr. Miao Yu
Dr. Zhejing Bao
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Electricity electricity	-	4.8	2020	27.9 Days	CHF 1000
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600
Journal of Low Power Electronics and Applications jlpea	1.6	3.6	2011	20 Days	CHF 1800
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600
Automation automation	-	2.9	2020	24.1 Days	CHF 1000

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Published Papers (6 papers)

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All Electricity Electronics Energies JLPEA Sensors Automation

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21 pages, 4675 KiB  

Open AccessArticle

A Novel Hierarchical Optimal Scheduling and Coordination Control Method for Microgrid Based on Multi-Energy Complementarity

by Li Zhang, Zeyuan Ma, Chenhao Jia, Tao Zhang and Hongwei Zhang

Electronics 2025, 14(9), 1829; https://doi.org/10.3390/electronics14091829 - 29 Apr 2025

Abstract

To address the uncertainty of intermittent energy sources and enhance the economic efficiency and operational performance of microgrids, this paper proposes a novel three-layer coupled microgrid scheduling model based on the principles of model predictive control, optimized and solved using an improved dung [...] Read more.

To address the uncertainty of intermittent energy sources and enhance the economic efficiency and operational performance of microgrids, this paper proposes a novel three-layer coupled microgrid scheduling model based on the principles of model predictive control, optimized and solved using an improved dung beetle algorithm. Firstly, by comprehensively considering time-varying electricity prices and pollution protection costs, the model optimizes and mitigates the impact of uncertain factors in day-ahead scheduling, thereby constructing a new three-layer scheduling framework. Secondly, improvements to the traditional dung beetle algorithm, including population initialization, rolling behavior, and foraging behavior, are validated through simulations, demonstrating enhanced accuracy and convergence speed. Furthermore, the improved dung beetle algorithm is utilized to optimize the economic performance of the scheduling layer, determining optimal controls within the rolling control framework. Finally, through economic comparisons, rolling scheduling analysis, and control effectiveness experiments, this study demonstrates that the proposed model and algorithm significantly improve the environmental economics of microgrids while enhancing system controllability and stability. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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23 pages, 7224 KiB  

Open AccessArticle

Capacity Optimization of Wind–Solar–Storage Multi-Power Microgrid Based on Two-Layer Model and an Improved Snake Optimization Algorithm

by Mintong Zhao, Yuling He, Yunfeng Tian, Kai Sun, Lingyu Jiao and Haipeng Wang

Electronics 2024, 13(21), 4315; https://doi.org/10.3390/electronics13214315 - 2 Nov 2024

Cited by 1 | Viewed by 1446

Abstract

A two-layer optimization model and an improved snake optimization algorithm (ISOA) are proposed to solve the capacity optimization problem of wind–solar–storage multi-power microgrids in the whole life cycle. In the upper optimization model, the wind–solar–storage capacity optimization model is established. It takes wind–solar [...] Read more.

A two-layer optimization model and an improved snake optimization algorithm (ISOA) are proposed to solve the capacity optimization problem of wind–solar–storage multi-power microgrids in the whole life cycle. In the upper optimization model, the wind–solar–storage capacity optimization model is established. It takes wind–solar power supply and storage capacity as decision variables and the construction cost of the whole life cycle as the objective function. At the lower level, the optimal scheduling model is established, considering the output characteristics of various types of power supplies and energy storage, microgrid sales, and purchases of power as constraints. At the same time, the model considers constraints, such as the power balance, the operating state of the energy storage system, the power sales and purchases, and the network fluctuations, to ensure the system operates efficiently. Taking a microgrid in South China as an application scenario, the model is solved and the optimal capacity allocation scheme of the microgrid is obtained. Meanwhile, the demand response mechanism and the influence of planning years are introduced to further optimize the configuration scheme, and the impact of different rigid–flexible load ratios and various planning horizons on microgrid capacity optimization is analyzed, respectively, by a numerical example. The comparison shows that the ISOA has better optimization performance in solving the proposed two-layer model. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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12 pages, 321 KiB  

Open AccessArticle

Resilience Improvement of Microgrid Cluster Systems Based on Two-Stage Robust Optimization

by Shui Ji, Yun Liu, Shanshan Wu and Xiao Li

Energies 2024, 17(17), 4287; https://doi.org/10.3390/en17174287 - 27 Aug 2024

Viewed by 721

Abstract

For microgrids in deep and remote sea areas, ocean currents are widely used as an emerging power generation resource. Implementing ES systems is crucial for smooth power output and grid stability. The stability of power output from sea current energy generation faces challenges [...] Read more.

For microgrids in deep and remote sea areas, ocean currents are widely used as an emerging power generation resource. Implementing ES systems is crucial for smooth power output and grid stability. The stability of power output from sea current energy generation faces challenges due to speed fluctuations. Enhancing resilience requires addressing transmission line failures caused by extreme seabed conditions, and ensuring operational security. An ES configuration method considering line faults based on two-stage robust optimization is presented in this paper. First, in order to simultaneously consider planning and operation, a defender–attacker–defender (DAD) model was established. Additionally, the capacity, rated power, and charging/discharging power of ES during operation were jointly optimized through the column-and-constraint generation (C&CG) algorithm. In addition, the rationality and effectiveness of the proposed method were demonstrated through experiments on modified IEEE six-bus and fifty-seven-bus systems. The results show that a distributed ES configuration increased system resilience by 54.60% and reduced abandoned power rate by 57.06% compared with the situation without ES configuration. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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23 pages, 579 KiB  

Open AccessArticle

Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis

by Mukesh Gautam and Mohammed Ben-Idris

Electronics 2023, 12(20), 4256; https://doi.org/10.3390/electronics12204256 - 14 Oct 2023

Cited by 3 | Viewed by 1434

Abstract

This article introduces a techno-economic analysis aimed at identifying the optimal total size of movable energy resources (MERs) to enhance the resilience of electric power supply. The core focus of this approach is to determine the total size of MERs required within the [...] Read more.

This article introduces a techno-economic analysis aimed at identifying the optimal total size of movable energy resources (MERs) to enhance the resilience of electric power supply. The core focus of this approach is to determine the total size of MERs required within the distribution network to expedite restoration after extreme events. Leveraging distribution line fragility curves, the proposed methodology generates numerous line outage scenarios, with scenario reduction techniques employed to minimize computational burden. For each reduced multiple line outage scenario, a systematic reconfiguration of the distribution network, represented as a graph, is executed using tie-switches within the system. To evaluate each locational combination of MERs for a specific number of these resources, the expected load curtailment (ELC) is calculated by summing the load curtailment within microgrids formed due to multiple line outages. This process is repeated for all possible locational combinations of MERs to determine minimal ELC for each MER total size. For every MER total size, the minimal ELCs are determined. Finally, a techno-economic analysis is performed using power outage cost and investment cost of MERs to pinpoint an optimal total size of MERs for the distribution system. To demonstrate the effectiveness of the proposed approach, case studies are conducted on the 33-node and the modified IEEE 123-node distribution test systems. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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24 pages, 4082 KiB  

Open AccessArticle

Centralized Protection of Networked Microgrids with Multi-Technology DERs

by Adeyemi Charles Adewole, Athula D. Rajapakse, Dean Ouellette and Paul Forsyth

Energies 2023, 16(20), 7080; https://doi.org/10.3390/en16207080 - 13 Oct 2023

Cited by 2 | Viewed by 1468

Abstract

The structure and connections in networked microgrids consisting of two or more interconnected microgrids is influenced by the dynamic behaviors of power markets, the demand and supply interactions between market participants, and the possibility of operating in the grid-connected or islanded modes. Protection [...] Read more.

The structure and connections in networked microgrids consisting of two or more interconnected microgrids is influenced by the dynamic behaviors of power markets, the demand and supply interactions between market participants, and the possibility of operating in the grid-connected or islanded modes. Protection zones in the above-mentioned scenarios are dynamic and should not be determined a priori. Also, fault currents will vary depending on the operating modes, online or offline status of Distributed Energy Resources (DERs), variation of solar irradiation or wind speed, etc. This paper proposes a Centralized Intelligent Station-Level Protection (CISP) approach for the protection of various electric power equipment technologies in networked (interconnected) microgrids using adaptive protective relaying algorithms and a network theory-based zone selection algorithm. The proposed CISP approach utilizes wide area IEC 61869-9 Sampled Values (SVs) measurements and IEC 61850 Generic Object-Oriented Substation Events (GOOSE) messages, intelligently determines the protection zones, and automatically selects the protection algorithms to use in each of the protection zones based on the prevailing system topology and operating conditions. The effectiveness of the proposed CISP approach is demonstrated through real-time simulations using the RTDS^®. The results obtained were promising for the various system configurations, operating conditions, and fault conditions considered. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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24 pages, 1573 KiB  

Open AccessReview

Microgrid Management Strategies for Economic Dispatch of Electricity Using Model Predictive Control Techniques: A Review

by Juan Moreno-Castro, Victor Samuel Ocaña Guevara, Lesyani Teresa León Viltre, Yandi Gallego Landera, Oscar Cuaresma Zevallos and Miguel Aybar-Mejía

Energies 2023, 16(16), 5935; https://doi.org/10.3390/en16165935 - 11 Aug 2023

Cited by 7 | Viewed by 2611

Abstract

In recent years, microgrid (MG) deployment has significantly increased, utilizing various technologies. MGs are essential for integrating distributed generation into electric power systems. These systems’ economic dispatch (ED) aims to minimize generation costs within a specific time interval while meeting power generation constraints. [...] Read more.

In recent years, microgrid (MG) deployment has significantly increased, utilizing various technologies. MGs are essential for integrating distributed generation into electric power systems. These systems’ economic dispatch (ED) aims to minimize generation costs within a specific time interval while meeting power generation constraints. By employing ED in electric MGs, the utilization of distributed energy resources becomes more flexible, enhancing energy system efficiency. Additionally, it enables the anticipation and proper utilization of operational limitations and encourages the active involvement of prosumers in the electricity market. However, implementing controllers and algorithms for optimizing ED requires the independent handling of constraints. Numerous algorithms and solutions have been proposed for the ED of MGs. These contributions suggest utilizing techniques such as particle swarm optimization (PSO), mixed-integer linear programming (MILP), CPLEX, and MATLAB. This paper presents an investigation of the use of model predictive control (MPC) as an optimal management tool for MGs. MPC has proven effective in ED by allowing the prediction of environmental or dynamic models within the system. This study aims to review MGs’ management strategies, specifically focusing on MPC techniques. It analyzes how MPC has been applied to optimize ED while considering MGs’ unique characteristics and requirements. This review aims to enhance the understanding of MPC’s role in efficient MG management, guiding future research and applications in this field. Full article

(This article belongs to the Topic Control and Optimization of Networked Microgrids)

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