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Symmetry
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Symmetry in Digitalisation of Distribution Power System
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Symmetry in Digitalisation of Distribution Power System

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 4201

Special Issue Editors

Dr. Wei Qiu

E-Mail Website
Guest Editor
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Interests: grid-synchronized measurement; big data analysis; cyber security of the distribution network
Special Issues, Collections and Topics in MDPI journals
Dr. Mengxiang Liu

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK
Interests: smart grid; cyber physical security; cyber physical simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Suhan Zhang

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, The University of Sheffield, Sheffield S10 2TN, UK
Interests: multi-energy system; cyber-physical system; power system simulation; optimization; low carbon

Special Issue Information

Dear Colleagues,

In a digital distribution power system, the concepts of symmetry and asymmetry are pivotal for optimizing system performance, reliability, and efficiency. Symmetry ensures balanced operations, crucial for stable power delivery and effective fault diagnoses. In digital networks, symmetrical data flow and communication protocols enhance real-time control and monitoring, mitigating issues from distributed energy resources' variability. Asymmetrical challenges, like uneven load distribution or cyber-physical uncertainties, can destabilize operations, impacting power quality and economic operations. Leveraging symmetry in planning and design facilitates intelligent management and co-regulation technologies, improving adaptability to new energy sources. Addressing both symmetrical and asymmetrical aspects is essential for integrating advanced technologies that ensure the secure, high-quality, and economic operations of modern power systems amidst growing complexities.

Topics:

  • Emerging technologies in smart grids (e.g., 5G, digital twin, blockchain, P2P energy trading);
  • Attack detection, defense, and recovery of cyber–physical power systems;
  • Resilient operations of distribution power systems against extreme weather;
  • Smart metering, communication, and control in smart grids;
  • Modeling and simulations of power electronic-dominated distribution power systems;
  • Smart coordination of heterogeneous energy systems like electricity, transportation, heating, and gas systems;
  • Communications and networking for distribution power systems;
  • Artificial intelligence and data analytics for distribution power systems;
  • Smart management of energy demand, storage, and electric vehicles.

Dr. Qiu Wei
Dr. Mengxiang Liu
Dr. Suhan Zhang
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 250 words) can be sent to the Editorial Office for assessment.

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. Symmetry 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

  • smart grids
  • distribution power systems
  • energy systems
  • modern power systems
  • cyber-physical power systems

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Published Papers (6 papers)

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Research

16 pages, 1312 KB  
Article
A Power Decoupling Strategy for Virtual Synchronous Generator Based on Active Disturbance Rejection Control Strategy
by Yu Ji, Hai Zhang, Ming Wu, Lijuan Hu, Ran Chen, Lijing Sun and Yini Xu
Symmetry 2025, 17(12), 2016; https://doi.org/10.3390/sym17122016 - 21 Nov 2025
Viewed by 255
Abstract
The renewable power grid is a complex system with multiple symmetries, in which active power and reactive power play different but symmetrical roles. In weak power grid condition, the virtual synchronous generators (VSGs) are prone to large power angles and high impedance ratios [...] Read more.
The renewable power grid is a complex system with multiple symmetries, in which active power and reactive power play different but symmetrical roles. In weak power grid condition, the virtual synchronous generators (VSGs) are prone to large power angles and high impedance ratios in the transmission lines, leading to severe coupling between active and reactive power. This coupling causes mutual interference between the active and reactive power outputs of the VSG, increasing the dynamic oscillations and prolonging the regulation time. To solve this problem, a power decoupling strategy for VSGs based on active disturbance rejection control (ADRC) is proposed in this paper. The ADRC control decouples the VSG, a dual-input, dual-output coupled system, into two single-input, single-output systems by observing and compensating for disturbances. This approach eliminates the coupling between the VSG’s power loops without considering virtual impedance. Compared with the conventional virtual impedance power decoupling method for VSGs, the proposed ADRC strategy can deal with multi-variable systems with different orders without complex and detailed high-order models, effectively decoupling the active power and reactive power of the VSG and improving the stability of the power grid. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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15 pages, 1810 KB  
Article
Hierarchical Allocation of Grid-Following and Grid-Forming Devices for Oscillation Stability Enhancement in Renewable Energy Plants
by Junchao Ma, Jianing Liu, Zhimin Cui, Yan Peng, Wen Hua and Qianhao Sun
Symmetry 2025, 17(11), 1912; https://doi.org/10.3390/sym17111912 - 8 Nov 2025
Viewed by 356
Abstract
The oscillation stability of renewable energy plants under varying grid strengths can be improved through the optimized allocation of grid-following (GFL) and grid-forming (GFM) power converter devices. However, in practical operation, the wide variations in both the output of renewable energy plants and [...] Read more.
The oscillation stability of renewable energy plants under varying grid strengths can be improved through the optimized allocation of grid-following (GFL) and grid-forming (GFM) power converter devices. However, in practical operation, the wide variations in both the output of renewable energy plants and the strength of the grid present significant challenges in simultaneously ensuring stability, economic efficiency, and robustness. To address this, this paper proposes a two-level optimization method for the allocation of GFL and GFM devices, aiming to enhance oscillation stability in renewable energy plants. The method considers the complementary dynamic behaviors of GFL and GFM strategies, whose complementary dynamic behaviors contribute to balanced and stable operation. The upper-level optimization model accounts for the wide range of variability in renewable plant outputs, with the primary objective and constraint being the assurance of oscillation stability under low short-circuit ratio (SCR) conditions at a minimal cost. Based on the GFM configuration determined by the upper-level model, the lower-level optimization model further evaluates the upper SCR limit within which oscillation stability can still be maintained. This prevents instability that may arise from GFM devices operating under high-SCR conditions. By iteratively solving the upper- and lower-level models, an optimized GFL-GFM allocation strategy is obtained, which ensures oscillation stability across a wide SCR range while balancing cost-effectiveness and practical operability. Case studies are also conducted to validate the method. It is indicated that when SCR = 1.5, configuring 15% of the wind generators in the GFM strategy can ensure stability of the wind plant across typical operating scenarios, while when SCR > 3, switching these generators to the GFL strategy can likewise avoid the oscillation issues. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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24 pages, 5142 KB  
Article
A Collaborative Optimization Strategy for Photovoltaic Array Layout Based on the Lemur Optimization Algorithm
by Guanhong Dai, Qianhan Chen, Yangyu Chen, Yu Wang, Zhan Shen and Xiaoqiang Li
Symmetry 2025, 17(11), 1870; https://doi.org/10.3390/sym17111870 - 5 Nov 2025
Viewed by 437
Abstract
The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized [...] Read more.
The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized cost of electricity. To achieve multi-objective comprehensive optimization of array layout parameters for a PV power generation system, a collaborative optimization strategy for PV array layout based on the lemur optimization (LO) algorithm is proposed in this paper. The method couples the Perez anisotropic irradiance model with a dynamic shading irradiance geometric model to simulate the effective insolation, incorporating land availability, shading thresholds, and maintenance access requirements. In addition, the LO algorithm is employed to solve resulting nonlinear and constrained problems, enabling an efficient global search across large parameter spaces. The case studies in Lianyungang, Dalian, and Fuzhou City show that the proposed scheme based on the LO algorithm improves annual energy yield compared with the existing optimization schemes, providing new theoretical methods and engineering application paths for the optimal layout of PV arrays. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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20 pages, 4382 KB  
Article
A Wasserstein Distance-Based Distributionally Robust Optimization Strategy for a Renewable Energy Power Grid Considering Meteorological Uncertainty
by Yao Liu, Lei Luo, Xiaoteng Li, Haolu Liu, Zihan Yu and Yu Wang
Symmetry 2025, 17(10), 1602; https://doi.org/10.3390/sym17101602 - 26 Sep 2025
Cited by 1 | Viewed by 1225
Abstract
With the large-scale integration of renewable energy into the power system, meteorological uncertainty poses challenges to the safe and stable operation of the system. Traditional uncertainty optimization methods struggle to balance robustness and economy. This paper proposes a Wasserstein distance-based distributionally robust optimization [...] Read more.
With the large-scale integration of renewable energy into the power system, meteorological uncertainty poses challenges to the safe and stable operation of the system. Traditional uncertainty optimization methods struggle to balance robustness and economy. This paper proposes a Wasserstein distance-based distributionally robust optimization strategy that considers covariate factors for a renewable energy power grid considering meteorological uncertainty. By introducing covariate factors to construct the Wasserstein ambiguity set, the intrinsic connection between weather uncertainty and the output of new energy is effectively depicted. The optimization problem is transformed into a solvable form of mixed integer linear programming by using linear decision rules and duality theorems, and the distributionally robust optimization scheduling problem is solved based on the improved cross optimization algorithm. Simulation results based on the IEEE 33 system show that under the same worst-case expected energy shortage of 20 kWh, the proposed method achieves an expected total dispatch cost of approximately CNY 0.534 million, reducing cost by about 0.4%, 0.9%, and 1.8% compared with conventional Wasserstein DRO, KL-divergence DRO, and Moment Information DRO; when the radius of the Wasserstein ball is 1, using the CSO algorithm reduces the runtime by 59.4% compared with the solver. It effectively reduces operating costs and solution speed while ensuring system security, offering a new approach for the optimal dispatch of power systems with a high penetration of renewable energy. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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19 pages, 4317 KB  
Article
Stochastic Programming-Based Annual Peak-Regulation Potential Assessing Method for Virtual Power Plants
by Yayun Qu, Chang Liu, Xiangrui Tong and Yiheng Xie
Symmetry 2025, 17(5), 683; https://doi.org/10.3390/sym17050683 - 29 Apr 2025
Cited by 1 | Viewed by 829
Abstract
The intervention of distributed loads, propelled by the swift advancement of distributed energy sources and the escalating demand for diverse load types encompassing electricity and cooling within virtual power plants (VPPs), has exerted an influence on the symmetry of the grid. Consequently, a [...] Read more.
The intervention of distributed loads, propelled by the swift advancement of distributed energy sources and the escalating demand for diverse load types encompassing electricity and cooling within virtual power plants (VPPs), has exerted an influence on the symmetry of the grid. Consequently, a quantitative assessment of the annual peak-shaving capability of a VPP is instrumental in mitigating the peak-to-valley difference in the grid, enhancing the operational safety of the grid, and reducing grid asymmetry. This paper presents a peak-shaving optimization method for VPPs, which takes into account renewable energy uncertainty and flexible load demand response. Firstly, wind power (WP), photovoltaic (PV) generation, and demand-side response (DR) are integrated into the VPP framework. Uncertainties related to WP and PV generation are incorporated through the scenario method within deterministic constraints. Secondly, a stochastic programming (SP) model is established for the VPP, with the objective of maximizing the peak-regulation effect and minimizing electricity loss for demand-side users. The case study results indicate that the proposed model effectively tackles peak-regulation optimization across diverse new energy output scenarios and accurately assesses the peak-regulation potential of the power system. Specifically, the proportion of load decrease during peak hours is 18.61%, while the proportion of load increase during off-peak hours is 17.92%. The electricity loss degrees for users are merely 0.209 in summer and 0.167 in winter, respectively. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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18 pages, 2196 KB  
Article
A Cooperative MHE-Based Distributed Model Predictive Control for Voltage Regulation of Low-Voltage Distribution Networks
by Yongqing Lv, Xiaobo Dou, Kexin Zhang and Yi Zhang
Symmetry 2025, 17(4), 513; https://doi.org/10.3390/sym17040513 - 28 Mar 2025
Viewed by 579
Abstract
This paper presents a moving horizon estimator-based cooperative model predictive control strategy for a low-voltage distribution area equipped with symmetric distributed generators (DGs). First, DGs have their symmetries in the control structures that can be utilized for the control design. Then, a simplified [...] Read more.
This paper presents a moving horizon estimator-based cooperative model predictive control strategy for a low-voltage distribution area equipped with symmetric distributed generators (DGs). First, DGs have their symmetries in the control structures that can be utilized for the control design. Then, a simplified model using feedback linearization theory for the symmetric DGs with hierarchical control reduces the high-order detailed models to low-order ones. To supplement the loss of accuracy and reliability in the proposed model, the controller introduces a moving horizon estimator to observe the unmeasured state variables under the poor communication condition of a low-voltage distribution network. Compared to the conventional method, the moving horizon estimator has advantages in handling uncertain disturbances, communication delays, constraints, etc. Furthermore, with all measured and observed state information, a cooperative distributed model predictive controller can be executed, and the stability and feasibility of controller are given. Finally, the effectiveness of the proposed control technique is verified through simulation based on Matlab/Simulink. Full article
(This article belongs to the Special Issue Symmetry in Digitalisation of Distribution Power System)
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