针对现有数字孪生在特高压直流系统中的应用，分析了数字孪生技术在解决特高压直流系统规模、数据、应用等方面存在的挑战与问题，并且在基础管理、设备管理、安全管理和业务运营等方面，系统地展示了数字孪生技术的应用场景与功能特点。根据业务需求构建了数字孪生场景以及数字孪生技术为关键节点的数字电网创新应用技术体系。以电网数字孪生转型为基础，从数据感知、模型构建、模型应用角度探索其应用场景，提高了系统在虚拟世界中的感知预测能力，同时支撑变电站智能化应用和新型电力系统的数字化服务需求，为电力行业的数字化转型提供了具体有效的路径与参考，提升了电网互动性、安全性，逐步实现电网业务的自动化、智能化、无人化。

Focuses on the application of digital twin technology in ultra-high voltage DC system, this paper analyzes the challenges and problems of digital twin technology in solving the scale, data, and application of ultra-high voltage DC systems, and systematically demonstrates the application scenarios and functional characteristics of digital twin technology in basic management, equipment management, safety management, and business operations. Based on business needs, a digital twin scenario and the innovative application technology system of digital power grid with digital twin technology as the key node are constructed. Based on the digital twin transformation of the power grid, its application scenarios are explored from the perspectives of data perception, model construction, and model application, improving the system′s perception and prediction capabilities in the virtual world. At the same time, it supports the intelligent application of the substations and the digital service demand of the new power system, provides specific and effective paths and references for the digital transformation of the power industry, and enhances the interactivity and security of the power grid, gradually achieves automation, intelligence, and unmanned operation of power grid business.

目的 在能源资源紧缺与环保需求加剧的背景下，分布式供能技术尤其是可再生能源技术因能效高、经济性好、安装灵活而备受关注。对于公共供电网无法覆盖的高原、边防、孤岛等偏远地区，孤岛微电网已然成为解决用电难的关键技术。然而，如何深入优化能量管理效能，仍是当前面临的一大挑战。为此，围绕孤岛微电网中电能的经济性和稳定性两大核心目标展开综述。 方法 首先分析了国内外孤岛微电网的发展现状及研究重点。然后探讨了孤岛微电网的基本功能和管理对象；此外，还介绍了微电网能量管理的技术路线和3种控制策略；最后，结合现有技术缺陷和新型技术的发展对孤岛微电网能量管理系统的研究方向进行了展望。 结论 研究结果能够有效应对可再生能源的波动性和不确定性，保证系统的稳定运行；可以有效降低储能成本，提高能源利用效率，从而实现更高的经济效益；也可为未来孤岛微电网与新型技术的深度融合提供参考和启示。

Objectives Against the backdrop of energy resource scarcity and increasing environmental demands, distributed energy supply technologies, particularly renewable energy technologies, have attracted significant attention due to their high energy efficiency, cost-effectiveness and flexible installation. For remote areas such as plateaus, border regions and islands, which are beyond the coverage of public power grids, islanded microgrids have become the key technology to address electricity access challenges. However, optimizing energy management efficiency remains a major challenge. This paper reviews the two core objectives—economic efficiency and stability—of electric energy in islanded microgrids. Methods The current development status and research priorities of islanded microgrids, both domestically and internationally, are analyzed. The basic functions and management objectives of islanded microgrids are discussed. Additionally, the technical approaches for microgrid energy management and three types of control strategies are introduced. Finally, the paper provides a discussion of future research directions for islanded microgrid energy management systems, based on existing technological limitations and the ongoing development of new technologies. Conclusions The research results can effectively deal with the volatility and uncertainty of renewable energy and ensure the stable operation of the system. It can effectively reduce the cost of energy storage, improve the efficiency of energy utilization, and achieve higher economic benefits. It can also provide references and insights for the future integration of islanded microgrids with new technologies.

Digital twin technology is transforming the way power grid infrastructure is monitored and managed, yet accurate pattern recognition under complex visual conditions remains a significant challenge. Traditional edge- or feature-based methods struggle to maintain robustness in environments affected by fog, shadow, or occlusion. This paper proposes a fusion framework that combines multi-scale edge detection and SIFT-based local descriptors, integrated through a learnable attention mechanism that adaptively weights features at each pixel location. The method is evaluated on a custom UAV-acquired dataset containing high-resolution power grid imagery under diverse environmental scenarios. Experimental results demonstrate that the proposed approach significantly outperforms edge-only, SIFT-only, and U-Net models across SSIM, F1-score, and IoU metrics, while maintaining practical inference speed. The model also achieves the lowest 3D registration error in point cloud alignment. These results confirm the effectiveness of our method and highlight its potential for accurate, robust digital twin construction in real-world grid inspection systems.

This comprehensive review explores the applications and challenges of Digital Twin (DT) technology in smart grids. As power grid systems rapidly evolve to meet the increasing energy demands and the new requirements of renewable source integration, DTs offer promising solutions to enhance the monitoring, control, and optimization of these systems. In this paper, we examine the concept of DTs in the context of smart grids, and their requirements, challenges, and integration with the Internet of Things (IoT) and Artificial Intelligence (AI). We also discuss different applications in asset management, system operation, and disaster response. This paper analyzes current challenges, including data management, interoperability, cost, and ethical considerations. Through case studies from various sectors in Canada, we illustrate the real-world implementation and impact of DTs. Finally, we discuss emerging trends and future directions, highlighting the potential of DTs to revolutionize smart grid networks and contribute to more efficient, reliable, and sustainable power systems.

工程各个阶段项目参与各方之间的信息供给和信息需求平衡，是建筑信息模型(BIM)技术在项目全生命周期管理最大程度发挥作用的重要保证。在交付需求标准化方面，尽管我国从国家到地方再到企业相继出台了诸多标准，但尚缺少高效的完备性审查手段以保证交付双方及时有效进行项目信息交付。此外，当前针对各阶段交付模型信息审查的常规手段是人工校验和机器硬编码审核，二者分别存在人工成本高且容易漏判和灵活性不足，且更新困难的问题。考虑到语义网概念及相关技术在知识组织和管理方面的技术优势和应用情况，结合电网工程现有数字化交付标准成果，提出一种基于语义网的电网工程BIM模型完备性审查方法：利用SKOS建立完备性审查本体、审查对象模型本体；对交付标准中审查知识和实际模型信息进行图谱化；二者通过特定关系进行关联，并在此基础上通过SPARQL检索语言实现自动化完备审查。最后通过案例证明此方法的有效性，并对其他领域工程项目交付完备性审查能够产生借鉴价值。

Ensuring a balance between information supply and information demand among all stakeholders at each project stage is crucial for harnessing the full potential of building information modeling technology in project life cycle management. While many standards have been established at national, local, and corporate levels to standardize delivery requirements, there remains a lack of efficient model integrity checking approach to facilitate participants to deliver project information in a timely and effective manner. Currently, the conventional means of checking model information for each stage of delivery was manual and machine hard-coded. However, they suffered from high labor costs, missed judgments, and limited flexibility for updates. Considering the technical advantages and applications of the semantic web concept and related technologies in knowledge organization and management, and combining the results of existing digital delivery standards for power grid engineering, a semantic web-based BIM model integrity checking approach was proposed. It was composed of three parts: 1) establishing integrity checking ontology and model to-be-checked ontology using SKOS; 2) instantiating knowledge in the delivery standard and actual model information to the knowledge graph; 3) correlating the two through specific relationships and automating integrity checking on this basis through SPARQL. Finally, the validity of this method was demonstrated through case studies, showcasing its applicability in engineering project delivery integrity checking in other fields.

研究目的: 铁路工程数字化建模技术已经取得重大进步,但铁路工程数字化设计交付生态尚未形成。铁路工程包含多个专业领域,现有BIM设计软件对大体量多专业模型的集成效率低,且不易与其他软件进行数据交换,亟需对铁路BIM设计成果集成数字化交付技术开展研究。研究结论: (1)利用GIS对大场景与多源数据的支持,将BIM精细化设计成果与地理信息大场景进行融合,基于B/S模式开发了铁路BIM集成系统,降低了对终端用户设备的硬件要求;(2)该系统可从全局角度展示BIM设计成果,实现微观与宏观相结合的集成数字化交付,有效解决铁路工程信息传递问题;(3)该系统应用于广湛高铁400 km工程BIM设计成果集成以及设计检查与优化,发现问题22处,通过优化可为工程实施提供高质量的设计成果。

<b>Research purposes:</b> Significant progress has been made in the digital modeling technology of railway, but the ecosystem of digital design and delivery of railway has not yet formed. Railway engineering including many domains, the existing BIM software has low integration efficiency for large-scale and multi-disciplinary models, and it is not easy to exchange data with other software. Therefore, it is urgent to research on the integrated digital delivery technology.<br/><b>Research conclusions:</b> (1) GIS can support large scene and multi-source data. Based on this, the integration of BIM and GIS was implemented and an integration system was developed using B/S mode reducing the hardware requirements for end users. (2) The system can visualize BIM design results from an overall perspective to realize integrated digital delivery combining micro and macro, and effectively solve the problem of railway engineering information transfer. (3) The system was used to integrate, check and optimize the design of Guangzhou-Zhanjiang high speed railway with 22 issues being found and the quality was improved.

针对当前电力设计行业中存在轻量化三维模型设计校验方法自动化水平较低的问题,提出了一种计及电网工程全寿命周期的轻量化三维模型自动化校验方法.该方法基于BIM技术和GIM技术构建电网工程的三维模型,并引入了改进的SLAM技术完成工程的点云特征拼接重建,在此基础上利用改进深度学习模型KPConv完成三维模型节点的点云语义分割比对,从而实现模型的自动化校验.仿真实验结果表明,采用所提方法在相关模型的自动化校验中取得了较高的精度,且在校验误差方面具有较优的稳定性,因此其在电网工程轻量化三维模型的设计领域具有良好的应用前景.

To address the problem of lower automation level of lightweight 3D model design calibration method in the current power design industry, a lightweight 3D model automation calibration method considering the whole life cycle of power grid project was proposed. The as-proposed method was based on BIM and GIM technologies to construct the 3D model of power grid project, and the improved SLAM technology was introduced to complete the reconstruction of point cloud feature stitching of the project, in terms of which the improved deep learning model KPConv was used to complete the point cloud semantic segmentation of 3D model nodes, so as to realize the automatic calibration of the model. The simulation results show that the as-proposed method achieves higher accuracy in the automatic calibration of relevant models and has better stability in respect of calibration errors, so it has good potential for application in the field of designing lightweight 3D models for power grid engineering.

Digital twin (DT) framework is introduced in the context of application for power grid online analysis. In the development process of a new power grid real-time online analysis system, an online analysis digital twin (OADT) has been implemented to realize the new online analysis architecture. The OADT approach is presented and its prominent features are discussed. The presentation, discussion, and performance testing are based on a large-scale grid network model (40K+ buses), exported directly from the EMS system of an actual power grid. A plan to apply the OADT approach to digitize power grid dispatching rules is also outlined.

构建新型电力系统是落实能源安全战略和“双碳”目标的重要举措，提升安全韧性是新型电力系统安全稳定发展的核心要义，亟需数字技术发挥关键的赋能作用。本文分析了新型电力系统安全韧性的内涵及特征，从极端事件频发、系统结构复杂、多能协调冲突等方面梳理了新型电力系统安全韧性提升面临的挑战；阐述了数字技术对新型电力系统安全韧性提升的赋能作用，凝练了数字技术赋能新型电力系统安全韧性提升存在的主要问题，进一步提出了数字技术赋能新型电力系统安全韧性提升的关键技术体系，涵盖基于人工智能的多模态数据融合技术、基于云 - 边协同的智能态势感知与预警技术、基于大数据分析的多能协同优化调控技术、基于数字孪生的灾后应急决策技术。注重气候韧性重大工程顶层设计、加强“数字+电力”关键技术研发、建设数据基础设施并完善质量保障机制、优化电力行业复合型人才梯队建设等策略运用，可为新型电力系统建设发展提供理论支撑。

Constructing a new power system is crucial for strengthening energy security and achieving the carbon peaking and carbon neutralization goals in China. Improving the security resilience is the core of the safe and stable development of the system, which requires the digital technology that could play a key enabling role. This study analyzes the implications and characteristics regarding the security resilience of new power systems, and sorts out the challenges faced by the improvement in security resilience, including frequent extreme events, complex system structure, and multi-energy coordination conflicts. This study expounds on the enabling effect of the digital technology on the improvement in security resilience of new power systems, summarizes the major problems existing in the enabling process, and further proposes a key technology system for improving the security resilience of new power systems through the digital technology, involving multimodal data fusion technology based on artificial intelligence, intelligent situation awareness and early-warning technology based on cloud-edge collaboration, multi-energy collaborative optimization and control technology based on big data analysis, and post-disaster emergency decision-making technology based on digital twins. To provide theoretical support for the development of new power systems, this study proposes the following suggestions: (1) emphasizing the top-level design of major projects regarding climate resilience, (2) strengthening the research and development of key digital and power technologies, (3) building data infrastructure while improving the quality assurance mechanism, and (4) optimizing the construction of a compound talent echelon in the power industry.

Natural disasters can cause severe damages to civil infrastructure and lead to extensive economic losses and casualties. To improve the emergency response capability of civil infrastructure under extreme circumstances such as natural disasters and human-caused hazards, intelligent technology for infrastructure emergency management has been extensively studied. As an emerging paradigm of interdisciplinary convergence, digital twins (DTs) can integrate intelligent technology into different stages of emergency management and provide a new solution for the emergency management of civil infrastructure (EMCI). However, applications of DT in EMCI have several limitations and are mostly case by case. However, the sector needs more generalisable lessons to address the greater value of DT in the context of EMCI. To address this gap, we first carry out a systematic literature review and analyse the latest progress and previous research deficiencies of DT by taking the scientometrical approach. Next, a framework is proposed to explain how DT can be applied to the mitigation, preparation, response, and recovery stages of EMCI. Lastly, the trends and prospects of DT applications in EMCI are discussed. Overall, the knowledge gained from this study will promote the research and development of more-viable DTs to address the sector’s demand for emergency management.