Abstract:Distribution network have become one of the most critical and vigorous sectors in developing new power systems. Digital transformation is a widely recognized way to solve the complex operation and control problems of distribution networks. Edge computing is an effective means to utilize the massive data resources and physical resources in digital distribution networks. It also provides a comprehensive platform for implementing operation functions on the edge side, which promotes the development and transformation of the operation architecture for the distribution network. This paper focuses on the digital transformation issues of distribution networks driven by the edge computing technology. The essential technical requirements for edge computing devices in the distribution network are presented. The technical positioning of edge computing and its support to the technical architecture of digital distribution networks are analyzed. Especially aiming at the operation issues of digital distribution networks, starting from three typical features of clustering, distribution, and flexible definition, key issues and technical research directions are summarized and discussed, including typical modes such as edge-side cluster local control, edge-edge cooperative control and cloud-edge cooperative operation.

Abstract:The field of distribution network planning looks forward to achieving intelligent planning, with the vision of achieving fully automated planning with no or minimal human intervention. In the context of digital transformation, the planning of new distribution networks will face three challenges, i.e., diversified graphics, fragmented scenes, and large-scale data. Three key technologies are proposed from the perspective of graph-model-data fusion: the graph-model fusion technology based on electrical drawing recognition and topology intelligent analysis, the model-data fusion technology based on knowledge-driven load/renewable energy deduction analysis and intelligent decision-making, and the graph-data fusion technology based on multi-modal data fusion and multi spatiotemporal data fusion, trying to break down the barriers between theoretical research and digital engineering. Finally, the development of digital planning for future new distribution network is considered and prospected, providing a reference for achieving a large closed-loop model of “machine-centric, human-machine collaboration”.

Abstract:Building the new power system with renewable energy as the main body is a key measure of the energy and power industry to promote the realization of the goal of “carbon emission peaking and carbon neutrality”. With the large-scale integration of multiple types of power electronic equipment into the system, the efficient collaboration of source-grid-load-storage has made the harmonic pollution intensify and become more complex and variable, presenting a globalized characteristic, which affects the high quality and reliable power supply of the power system. This paper focuses on the harmonic source tracing under the interaction of multiple types of harmonic sources, and deeply integrates the advantages of advanced digital technology in data resources and intelligent collaboration to carry out dominant source identification and harmonic contribution evaluation. First, around the concept of harmonic source tracing, the new challenges and opportunities faced by the new power system on the background of digitalization are analyzed. Then, the current status of harmonic source tracing research is elaborated, and the new development requirements of key technologies are pointed out. On this basis, a cloud-edge-end collaboration strategy of harmonic source tracing is designed by using the technical architecture of digital power grid. Under the background of digitalization, the main technologies of harmonic source tracing in data collecting, mechanism analysis, and collaborative application are described. Finally, this paper prospects the technology direction for the secure, reliable, and flexible development of digital power system in the future.

Abstract:Data-driven has become the core paradigm for the construction and digital transformation of new power systems, and related algorithms have shown superior engineering effects and application potential in multiple power system fields, such as load forecasting, condition-based maintenance, and multi-agent scheduling. However, the actual of engineering data often faces problems such as insufficient and imbalanced samples, which restricts the ultimate effectiveness of data-driven algorithms. Therefore, the few-shot learning is needed to address this challenge. This paper explores the few-shot learning technologies from three levels of data, features, and models. It reviews and analyzes the current application status of related technologies in scenario generation, fault diagnosis, and transient stability assessment of power systems. The shortcomings and challenges faced by few-shot learning technologies in new power systems are further presented.

Abstract:The construction of the new power system involves interaction and sharing of massive and heterogeneous data among multiple business systems, departments, and agents. The internal and external network environment and security situation of power data are becoming increasingly complex, and the vulnerability risk of data circulation increases. First, this paper analyzes the types and characteristics of data flow in the new power system, and summarizes the new situation faced by the security protection of power data circulation. Then, based on the high-performance traffic orchestration and multifunctional security gateway capabilities of the data processing unit (DPU), the ubiquitous security boundary is constructed to enhance the security of power data cross-domain circulation. With the help of data-plane programmable technology, the dual-dimension security capabilities of network security and data security are communicated, and a DPU-based application scheme of collaborative protection technology for the cross-domain data circulation is proposed. Finally, this paper explains the deployment methods, values, and key technologies of DPU at different levels of power communication networks, and analyzes the challenges of DPU application in the power industry at present.

Abstract:The digital transformation of distribution networks will further promote the deep coupling of information system and physical systems. Due to the limited information security defense resources of the distribution network, it is difficult to isolate the security risks of the information side from the physical system, which also makes the state estimation of the distribution network face new challenges. Firstly, the architecture of the distribution network cyber-physical system is briefly introduced, and the technical framework of the distribution network state estimation for cyber-physical system is constructed. Secondly, this paper comprehensively reviews the research status of distribution network state estimation technologies at home and abroad on the background of cyber-physical fusion, including the pseudo-measurement modeling and analysis of distribution networks considering cyber-attacks, the analysis and defense of false data injection attacks in the distribution network, and the security risk analysis and reliability assessment of distribution network cyber-physical systems. Finally, the key problems facing the further development of this field are discussed and analyzed.

Abstract:In the context of building new power systems, the time-series production simulation powered by digital transformation has become an important tool for the operation evaluation and planning decision of new power systems. This paper summarizes the domestic and foreign research results on time-series production simulation, and the applications and solving techniques of time-series production simulation in new power systems. First, the structure and characteristics of time-series production simulation are introduced, and the application scenarios of time-series production simulation are reviewed from the aspects of power quantity balance calculation, quantitative analysis of “carbon emission peak and carbon neutrality” measures, and future power grid form and evolution path. Then, the existing solving techniques of time-series production simulation are classified according to their characteristics, and the limitations of different solving techniques are discussed. Finally, the research of time-series production simulation of new power systems is prospected.

Abstract:The decision-making optimization process of planning, operation, and market operation of new power system presents more variables and more complex constraints. The quantum computing has the characteristics of parallel computation operation and state superposition, which can provide effective ideas for avoiding the “curse of dimensionality”. This paper attempts to explore the theoretic feasibility and application prospect of quantum computing technology for the decision-making optimization of the new power system. First, both advantages and limitations about the application of quantum computing to the decision-making optimization of the new power system is analyzed. A hybrid quantum-classical computing framework for variational quantum decision optimization is constructed. On this basis, the common features of the typical optimization problems in the new power system are generalized to form a unified problem structure, whereafter it is transformed into the energy model that can be described by the qubit system. Subsequently, the quantum approximation optimization algorithm is adopted to find the extreme value of the energy model, and the optimal solution of the original problem is determined. Finally, reflection and prospect are put forward from the perspective of hardware, software, algorithmic framework, and industry development.

Abstract:With the development of advanced digital, communication, and Internet technologies, the traditional power system has been transformed into a new power system with digitalization, automation, and efficient management. However, the deep integration of cyber and physical domains makes the network, hierarchy, and components in the new power system more complex, and the frequent access and information interaction of a large number of intelligent electronic devices makes malicious attacks easier, such as data theft and tampering, blocking of communication channels, and damaging key equipment, which poses a great threat to the security, stability and economy of the new power system. This has triggered great concern in the academic community. First, this paper analyzes the structure of the new power system and the potential threats faced by the new power system, and conducts an in-depth analysis of the attack modes to the new power system from the three levels of the control layer, network layer, and physical layer. Then, it summarizes in detail the three-layer security defense methods before, during, and after the attack on the new power system. Finally, the future technological development prospect of the new power system security research is clearly elaborated to provide technical support for the construction of the reliable, secure, and robust new power system.

Abstract:The large language model (LLM) is a deep learning language model that utilizes large-scale text corpora for pre-training and fine-tuning. Nowadays, it has demonstrated powerful capabilities in generalized quizzing, text generation and scientific reasoning. In this context, this paper explores the construction of artificial general intelligence techniques for power systems based on LLM and prospects its potential applications in power systems. Firstly, the basic principles, neural network architecture, and training methods of LLM are introduced, with a particular focus on its breakthroughs in logical reasoning, programming and code understanding, and mathematical reasoning compared with traditional artificial intelligence models. Then, this paper prospects the potential applications of LLM in the areas of load forecasting and renewable energy generation prediction in power systems, power system planning, power system operation, fault diagnosis and system restoration in power systems, and electricity markets. Finally, the challenges in building an artificial general intelligence technology for the power system based on LLM are elaborated upon, including data quality and accessibility in the power system domain, interpretability of output results, and privacy protection concerns.

Abstract:With the construction and development of new power systems, the operation environment of key power equipment has changed, and the operation process is facing more risks. The condition monitoring and diagnosis (CMD) technology of critical power equipment is the guarantees of its normal operation, but there are still shortcomings at present. The sensor chip integrating signal acquisition, data analysis, and information transmission can realize online, real-time, and accurate CMD of key power equipment. Based on the basic concept of the sensor chip for the equipment CMD for new power systems, this paper summarizes the development status of four key technologies of sensing acquisition, signal processing, data analysis, and information transmission of the sensor chip, and points out the challenges faced by the key technologies. Finally, the future research directions of CMD of critical power equipment are prospected.

Abstract:Satellite Internet is a new type of global and all-time network information infrastructure that uses large-scale satellite networking and is supported by aerospace, communication, network, and data technologies. Compared with traditional satellite networks, it offers advantages such as wide coverage, low latency, high bandwidth, and low cost. The challenges faced by new power systems in the construction of information capabilities are analyzed, including wide-area coverage, resilience to damage, and vertical applications. The definition and capability characteristics of high, medium, and low Earth orbit coordination in satellite Internet are refined, and practical pathways of satellite Internet enabling new power systems in areas such as power planning, situational awareness, inspection and maintenance, and disaster prevention and emergency response are proposed. A zero-trust satellite-ground fusion based integrated network information security system is proposed to serve as a foundational reference for the establishment, operation, and advancement of a comprehensive integrated space-air-ground and coordinated communication-navigation-remote-sensing new power system. The new-style productivity level is enhanced.

Abstract:Digitalization is a crucial driving force for the development of the new power system. It has become a hot technology that attracts the attention of both academia and industry. In this regard, the editorial office of “Automation of Electric Power System” has organized the special issue of reviews on key technologies for digitalization of new power system, which systemactically introduces a series of technological achievements in basic digitization components of new power systems, edge computing technology, communication security and protection, intelligent scheduling decision-making, and so on. These papers represent the latest technologies achievements and advanced experiences in this field. Based on the overall trend of the digitization development of the new power system, this paper systematically reviews the articles in the special issue according to their research directions, and summarizes the core achievements and viewpoints. It is hoped that the results in the special issue can be presented in a complete way to support the digitalization of the new power system and provide reference for further deepening the related technical research.