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Journals
Processes
Special Issues
Applications of Smart Microgrids in Renewable Energy Development
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Applications of Smart Microgrids in Renewable Energy Development

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 20 May 2026 | Viewed by 4220

Special Issue Editors

Dr. Hui Li

E-Mail Website
Guest Editor
State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao 999078, China
Interests: power system planning; low-inertia systems; optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Kuan Zhang

E-Mail Website
Guest Editor
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Interests: optimal operation of electricity-hydrogen integrated energy system; optimal scheduling and energy management of virtual power plant
Special Issues, Collections and Topics in MDPI journals
Dr. Yikui Liu

E-Mail Website
Guest Editor
College of Electrical Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
Interests: optimal operation of power systems; power market
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The global pursuit of carbon neutrality has accelerated energy transitions and the development of renewable energy sources within modern power systems. As a complementary solution to centralized power supply, smart microgrids facilitate renewable energy integration due to their flexible, efficient, and modular nature. Additionally, these decentralized systems contribute significantly to grid enhancement in areas such as frequency stabilization, voltage regulation, demand-side management, etc., which have become more pronounced with the increasing penetration of renewable energy resources. Despite the growing application scenarios for smart microgrids, advancements in microgrid allocation, energy management, and transaction mechanisms are required to adapt to these evolving trends in renewable energy. Addressing these aspects is essential for optimizing the performance of smart microgrids and supporting the development of renewable power systems.

This Special Issue invites original research articles that explore cutting-edge applications of smart applications in renewable energy development. Topics of interest for this Special Issue include, but are not limited to, the following areas:

  1. Allocation of renewable energy resources in smart microgrids;
  2. Energy management of smart microgrids using renewable energy;
  3. Renewable energy sharing in clustered smart microgrids;
  4. Enhancing renewable energy integration through smart microgrids;
  5. Synergies between renewable energy and dispatchable resources in smart microgrids;
  6. Modeling and forecasting of uncertain renewable energy.

Dr. Hui Li
Dr. Kuan Zhang
Dr. Yikui Liu
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. Processes is an international peer-reviewed open access monthly 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 2400 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
  • renewable energy
  • planning
  • energy management
  • energy sharing
  • uncertainty

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Published Papers (6 papers)

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Research

18 pages, 962 KiB  
Article
Linearized Power Flow Calculation of Flexible Interconnected Distribution Network Driven by Data–Physical Fusion
by Wanyuan Li, Yang You, Tianze Liu, Yuntao Ju and Yuxuan Ma
Processes 2025, 13(5), 1582; https://doi.org/10.3390/pr13051582 - 19 May 2025
Abstract
In a modern flexible interconnected distribution network, the dynamic coupling effect between the traditional AC network model and the power electronic converter significantly enhances the nonlinearity and non-convexity of power flow calculations. In particular, when a one-end converter station quits operating due to [...] Read more.
In a modern flexible interconnected distribution network, the dynamic coupling effect between the traditional AC network model and the power electronic converter significantly enhances the nonlinearity and non-convexity of power flow calculations. In particular, when a one-end converter station quits operating due to a fault, it is necessary to ensure that the remaining converter stations can continue to maintain the normal operation of the interconnected system, which leads to the convergence problem of the traditional physical-driven iterative method. Aiming to address this problem, this study discusses the data-driven linearization method of the current distribution network power flow in depth and proposes a linearized power flow calculation (LPFC) of a flexible interconnected distribution network based on a data–physical fusion drive. Based on the traditional linearization method based on physical characteristics and first-order Taylor expansion, the model uses the partial least squares method to compensate for the linearization error and can normally cope with the failure of the flexible interconnected system. The proposed model greatly improves the convergence and computational efficiency of the power flow model under the premise of ensuring the linearization accuracy and can adapt to different load levels to achieve accurate error compensation. In addition, based on an actual engineering example, this paper introduces the converter station model, constructs a flexible interconnected system, and verifies the applicability of the proposed model. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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23 pages, 2987 KiB  
Article
Considering Active Support Capability and Intelligent Soft Open Point for Optimal Scheduling Strategies of Urban Microgrids
by Zhuowen Zhu, Tuyou Si, Zejian Qiu, Lili Yu, Qian Zhou, Xiao Liu and Kuan Zhang
Processes 2025, 13(5), 1338; https://doi.org/10.3390/pr13051338 - 27 Apr 2025
Viewed by 163
Abstract
With the increasing penetration of renewable energy in the power system, how to ensure the normal operation of urban microgrids is gradually receiving attention. It is necessary to evaluate the overall active support capability and provide optimal operation strategies for urban microgrids. The [...] Read more.
With the increasing penetration of renewable energy in the power system, how to ensure the normal operation of urban microgrids is gradually receiving attention. It is necessary to evaluate the overall active support capability and provide optimal operation strategies for urban microgrids. The paper proposes an active–reactive power coordinated optimization method for urban microgrids with a high proportion of renewable energy. Firstly, a quantification model of the active support capability is established to evaluate the active support capacity and reactive support capacity of urban microgrids, respectively. Then, an active–reactive power collaborative optimization model, which considers multiple types of distributed resources, is established to provide optimal scheduling strategies for urban microgrids. Consequently, a platform integrating evaluation and regulation functions is constructed to enable the evaluation of the active support capability for distributed resources in urban microgrids and the scheduling of distributed resource operations. This paper aims to solve the key technical challenges of the safe operation of new urban microgrids. The simulation results demonstrate that the proposed optimal scheduling method can reduce the comprehensive operating costs of urban microgrids with high renewable energy penetration by up to 19.86% and decrease the voltage deviation rate by up to 7.25%, simultaneously improving both economic efficiency and operational security. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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18 pages, 6973 KiB  
Article
Two-Layer Optimal Scheduling Model of Microgrid Considering Demand Response Based on Improved Nutcracker Optimization Algorithm
by Bing Zeng, Shitao Hao, Dilin He, Haoran Li, Yu Zhou, Zihan Jin, Xiaopin Yang and Yunmin Xie
Processes 2025, 13(2), 585; https://doi.org/10.3390/pr13020585 - 19 Feb 2025
Viewed by 640
Abstract
To comprehensively address the interests of both the supply and demand sides within a microgrid, a two-layer optimal scheduling model incorporating demand response was formulated. The upper tier aims to optimize the load profile, focusing on maximizing electricity consumption satisfaction and minimizing user [...] Read more.
To comprehensively address the interests of both the supply and demand sides within a microgrid, a two-layer optimal scheduling model incorporating demand response was formulated. The upper tier aims to optimize the load profile, focusing on maximizing electricity consumption satisfaction and minimizing user electricity costs. Meanwhile, the lower tier targets the optimization of output from each controllable generation unit, with the goal of reducing operational costs. Given the nonlinear and multi-constrained nature of this model, an improved nutcracker optimization algorithm (INOA) is proposed. This enhancement introduces chaotic sequences into the original nutcracker optimization algorithm (NOA) for population initialization, employs a hybrid butterfly optimization algorithm to enhance the algorithm’s local search capabilities, and integrates dynamic selection adaptive T-distribution for updating individual positions. The solution tests involving INOA, NOA, dung beetle optimizer (DOB), particle swarm optimization (PSO), grey wolf optimization (GWO), and sparrow search algorithm (SSA) were conducted using the CEC2022 intelligent algorithm test suite. Analysis reveals that INOA exhibits superior comprehensive optimization performance compared to other algorithms, validating the effectiveness of the improvements introduced in this paper. Ultimately, a simulation analysis of the microgrid was performed, demonstrating that, despite a 3.58% reduction in user satisfaction, participation in demand response led to a 25.16% decrease in electricity costs and a 5.92% reduction in microgrid operational costs. These findings substantiate the model’s capability to effectively balance the economic interests of both the supply and demand sides within the microgrid. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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17 pages, 3033 KiB  
Article
An Improved Scheduling Approach for Multi-Energy Microgrids Considering Scenario Insufficiency and Computational Complexity
by Song Gao, Yuqi Wang, Yuzhou Zhou and Haixia Yu
Processes 2025, 13(2), 576; https://doi.org/10.3390/pr13020576 - 18 Feb 2025
Cited by 1 | Viewed by 500
Abstract
With the increasing energy demands and concern for environmental protection, researching and optimizing multi-energy systems have become prominent issues in the energy field. To improve the overall performance of multi-energy systems, there are two main difficulties that must be overcome: the first is [...] Read more.
With the increasing energy demands and concern for environmental protection, researching and optimizing multi-energy systems have become prominent issues in the energy field. To improve the overall performance of multi-energy systems, there are two main difficulties that must be overcome: the first is the issue regarding the coupling relationships between energy sources, and the second is the uncertainties related to multiple types of energy and loads. Particularly with regard to the second difficulty, it is necessary to generate a large number of effective scenarios, as many multi-energy systems have only been built recently, and operational data exhibit uncertainties. However, at the same time, the introduction of a large number of random scenarios can lead to computational difficulties, making it impossible for a model to solve this problem. To this end, in this paper, we propose an improved scheduling approach for multi-energy microgrids, balancing scenario insufficiency and computational complexity. Latin Hypercube sampling is creatively used to generate enough uncertain scenarios, and hierarchical clustering is employed to create representative scenarios to reduce the computational complexity. Then, based on these effective clustered scenarios, a multi-energy collaborative optimization method considering the coupling relationship between energy sources is proposed. The effectiveness of this method is verified through numerical tests and sensitivity analysis. The results show that the economic cost of this method is only 0.305% higher than that of the deterministic method and that it has a certain degree of robustness and a good economic performance, but it is limited by its computational efficiency. In summary, this study provides an effective solution for collaboratively optimizing the operation of multi-energy systems, aiming to provide valuable insights for research in the energy field. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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20 pages, 3387 KiB  
Article
A Fuzzy Inertia-Based Virtual Synchronous Generator Model for Managing Grid Frequency Under Large-Scale Electric Vehicle Integration
by Yajun Jia and Zhijian Jin
Processes 2025, 13(1), 287; https://doi.org/10.3390/pr13010287 - 20 Jan 2025
Viewed by 971
Abstract
The rapid proliferation of EVs has ushered in a transformative era for the power industry, characterized by increased demand volatility and grid frequency instability. In response to these challenges, this paper introduces a novel approach that combines fuzzy logic with adaptive inertia control [...] Read more.
The rapid proliferation of EVs has ushered in a transformative era for the power industry, characterized by increased demand volatility and grid frequency instability. In response to these challenges, this paper introduces a novel approach that combines fuzzy logic with adaptive inertia control to improve the frequency stability of grids amidst large-scale electric vehicle (EV) integration. The proposed methodology not only adapts to varying charging scenarios but also strikes a balance between steady-state and dynamic performance considerations. This research establishes a solid theoretical foundation for the inertia-adaptive virtual synchronous generator (VSG) concept and introduces a pioneering fuzzy inertia-based VSG methodology. Additionally, it incorporates adaptive output scaling factors to enhance the robustness and adaptability of the control strategy. These contributions offer valuable insights into the evolving landscape of adaptive VSG strategies and provide a pragmatic solution to the pressing challenges arising from the integration of large-scale EVs, ultimately fostering the resilience and sustainability of contemporary power systems. Finally, simulation results illustrate that the new proposed fuzzy adaptive inertia-based VSG method is effective and has superior advantages over the traditional VSG and droop control strategies. Specifically, the proposed method reduces the maximum frequency change by 25% during load transitions, with a peak variation of 0.15 Hz compared to 0.2 Hz for the traditional VSG. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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12 pages, 2554 KiB  
Article
A Real-Time Accounting Method for Carbon Dioxide Emissions in High-Energy-Consuming Industrial Parks
by Hongli Liu, Lianfang Xie, Yang Wei, Yumin Chen, Xueyuan Liu, Yibin Zhang, Deming Liu and Qian Li
Processes 2024, 12(12), 2657; https://doi.org/10.3390/pr12122657 - 25 Nov 2024
Viewed by 967
Abstract
Industrial parks play a crucial role in carbon control and reduction. With energy-intensive enterprises at their core, such parks feature highly concentrated carbon emission sources and a significant demand for carbon trading. Nonetheless, the absence of precise and real-time carbon accounting methods makes [...] Read more.
Industrial parks play a crucial role in carbon control and reduction. With energy-intensive enterprises at their core, such parks feature highly concentrated carbon emission sources and a significant demand for carbon trading. Nonetheless, the absence of precise and real-time carbon accounting methods makes it difficult for them to effectively manage and regulate carbon emissions. The real-time accounting methods for carbon dioxide emissions in high-energy-consuming industrial parks urgently need further study. Therefore, this paper initially examines three areas—fuel combustion, industrial engineering, and electricity usage—and proposes a real-time framework to account for carbon dioxide emissions in high-energy industrial parks. Secondly, it extracts real-time elements from each part and proposes a real-time carbon dioxide emission accounting method tailored to the actual needs of high-energy-consuming industrial parks. Finally, an empirical analysis is carried out on an aluminum production park as an example to verify the feasibility and effectiveness of the real-time accounting method for carbon dioxide emissions in high-energy-consuming industrial parks. Full article
(This article belongs to the Special Issue Applications of Smart Microgrids in Renewable Energy Development)
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