Project Name

Key Technology Applications for Equipment Health Status Early Warning and Diagnosis under Smart Operations in Multiple Scenarios for New Energy Systems

Nominating Unit

Hebei Provincial Department of Education

Project Overview

In our country Carbon peaking, carbon neutrality Strategic objectives and Driven by the "New Infrastructure" initiative, new energy sources on the power generation side have become an important component of the new power system and will in the future become the mainstay of the energy supply side. Meanwhile, the rapid development of new-energy electric vehicles and charging infrastructure on the energy consumption side is helping to make carbon reduction a new normal. On the one hand, after large-scale integration of new energy sources into the new power system, operators face challenges such as low operational efficiency, low utilization of data assets, difficulty in early warning of equipment health status, and difficulties in fault diagnosis—all due to complex operating conditions of equipment, close coupling between fault characteristics and fault evolution processes, and uncertain demand for source-load coordination across multiple scenarios. On the other hand, fire accidents involving electric vehicle charging are becoming increasingly frequent. As the service life of charging stations and vehicles declines, it becomes increasingly difficult to accurately predict safety warning thresholds, leading to challenges in real-time, precise detection of charging safety, coordinated early warning between vehicles and charging stations, effective diagnosis, and proactive safety protection.

Under the joint efforts of scientific and technological projects involving industry, academia, research, and application—such as those funded by the National Natural Science Foundation, State Grid Tianjin Electric Power Company, Guoneng Sida Technology Co., Ltd., and Shijiazhuang Tonghe Electronic Technology Co., Ltd.—this project has conducted research on new-energy network control systems comprising wind power, photovoltaic energy, energy storage, and vehicle-to-grid infrastructure. Through theoretical analysis of the operational stability of complex network systems, from... Joint research and development efforts were carried out across three dimensions—system theory, key technologies, and demonstration applications—bringing together industry, academia, research institutions, and users. Over an eight-year period, we developed and refined a new energy network switching control system, proposed a modeling approach that integrates equipment mechanism models with multi-source data-driven methods for various new-energy scenarios, and created digital twin models of systems and equipment suitable for multiple application scenarios. We also developed a cloud-based optimization and fault early-warning diagnostic system for new-energy operations, intelligent monitoring and diagnostic equipment for charging safety, and a big-data security protection platform. These efforts addressed the challenges of real-time monitoring and intelligent early warning as well as accurate diagnosis of charging faults, resulting in a comprehensive digital solution that has significantly improved operation and maintenance efficiency and has been widely adopted and promoted. The key innovations are as follows:

( 1) A novel switching control system for new energy networks, incorporating nodes such as wind power, photovoltaic systems, energy storage, and charging stations, is proposed. The event-triggered control mechanism of the network switching control system is elaborated upon. A zero-obstacle function is designed based on safety protection requirements, and the stability of the network switching system under the multi-Lyapunov theory framework is analyzed.

( 2) A modeling approach was proposed that combines equipment mechanism models with multi-source data-driven methods across multiple scenarios, establishing a digital twin system model for equipment in various scenarios. This approach enhances the model’s situational awareness capability and improves the modeling accuracy of new-energy equipment. Furthermore, by employing acceleration at different rates, it enables full-cycle operational simulations of the equipment.

( 3) A health assessment, early warning, and diagnostic system has been developed for the entire lifecycle of equipment across multiple scenarios, including wind power, photovoltaic systems, and electric vehicle charging stations. An improved particle swarm optimization algorithm has been proposed to optimize deep belief networks, enabling a comprehensive health assessment and diagnostic approach for new-energy equipment throughout its entire lifecycle. This approach accurately characterizes the intrinsic information of the equipment and the mechanisms underlying fault evolution, thereby enhancing the practicality of the equipment health assessment, early warning, and diagnostic system.

( 4) An improved RNN neural network-based technology for charging pile fault monitoring and diagnosis has been proposed, resulting in an intelligent early-warning database with self-updating capabilities. Furthermore, an integrated vehicle-pile safety state evaluation model based on an improved fuzzy evaluation method using grey relational analysis has been developed, establishing a cloud-edge collaborative proactive safety protection system.

The project has been granted an invention patent. 18 utility model patents, 15 software copyrights; published 88 papers, including 43 papers indexed by SCI and 35 papers indexed by EI or included in Chinese core journals; supervised 10 doctoral students and 45 master’s students.

The project generates direct economic benefits of approximately 3 billion yuan, with an additional profit of approximately 500 million yuan. On the new energy generation side, the project’s achievements have been promoted and applied in over 120 wind farms and more than 20 photovoltaic power stations across 21 provinces and regions and 9 power generation groups nationwide. On the power distribution and consumption side, the project’s results were first demonstrated in Tianjin and have since been extended to over 150 large-scale charging stations in 21 provincial-level administrative regions across the country, including Shandong and Hebei. Over the past three years, the project’s achievements have cumulatively increased power generation by 290 million kilowatt-hours, reduced carbon emissions by approximately 2.502 million tons, and saved about 92,700 tons of standard coal. The project has fostered the sustained development of the new energy industry and “new infrastructure,” providing crucial support for the nation’s strategic goals of peaking carbon emissions and achieving carbon neutrality.

Main completing unit and contributions to innovation and promotion

The main implementing units are: Hebei University, State Grid Tianjin Electric Power Company, Guoneng Sida Technology Co., Ltd., Shijiazhuang Tonghe Electronic Technology Co., Ltd.

( 1) Hebei University, as the lead institution for the project, has developed a comprehensive modeling framework for new-energy networks that encompass numerous renewable energy sources—including power generation, energy storage, and charging stations—and has established a unified network control system switching theory to handle state transitions such as grid connection of nodes and fault isolation. Based on safety protection requirements, a zero-barrier function was designed, and the system’s stability was analyzed within the multi-Lyapunov theory framework for switching systems. A modeling approach combining equipment mechanism models with multi-source data-driven methods was proposed for various new-energy scenarios, and digital twin models of systems and equipment under multiple new-energy scenarios were constructed. The error in key parameters is controlled within ±1%, while other parameters do not exceed ±2%. A full-lifecycle health assessment, early warning, and diagnostic system tailored to multiple scenarios—including wind power, photovoltaic power, energy storage, and charging stations—has been established. An improved RNN neural network-based technology for monitoring and diagnosing charging-station faults was proposed, creating an intelligently self-updating early-warning database. Furthermore, an innovative integrated safety-state evaluation model for vehicles and charging stations, based on an improved gray relational fuzzy evaluation method, was developed, forming a cloud-edge collaborative proactive safety protection system. Significant contributions have been made to innovation points 1, 2, 3, and 4.

( 2) State Grid Tianjin Electric Power Company, through industry-academia-research-application collaboration, has assisted in conducting research on the modeling of digital twin systems for new energy systems and equipment across multiple application scenarios. It has also participated in the development of a comprehensive health assessment, early warning, and diagnostic system covering the entire lifecycle of energy storage devices, charging piles, and other related equipment. Leveraging charging pile fault diagnosis technologies and multi-body information interaction technologies among vehicles, stations, roads, and networks, the company has jointly developed intelligent monitoring and diagnostic equipment for charging safety, as well as a big data security protection platform. The company has made significant contributions to innovation points 2, 3, and 4, and is responsible for promoting the application of these project outcomes at 754 large-scale charging stations—including the Tianjin Jinmen Lake New Energy Vehicle Comprehensive Service Center, Tianjin Station, and Haitai Comprehensive Charging Station—under the company’s operation. This provides solid support for the development of the electric vehicle industry and the successful implementation of the “dual-carbon” strategy.

( 3) Guoneng Sida Technology Co., Ltd., through industry-academia-research-application collaboration, has established digital twin system models for new-energy facilities such as wind farms and photovoltaic power stations at Sida Academy, and is participating in the construction of a platform oriented toward... Equipment health in scenarios such as wind power, photovoltaics, and energy storage. Evaluation, Early Warning, and Diagnostic System: Assisted in the technical research on the health evaluation, early warning, and diagnostic system for new energy generation equipment, and jointly developed a cloud-based system for optimizing new energy operations as well as for fault early warning and diagnosis. Key innovations: 2. Made significant contributions and took charge of promoting the application of project outcomes to over 120 wind farms and more than two photovoltaic power stations under the company’s operation and maintenance management, thereby enhancing the operational efficiency of new-energy facilities, effectively increasing operating hours and power generation, and creating substantial economic benefits for the client entities. At the same time, this has markedly strengthened the company’s digitalization, informatization, and intelligentization in new-energy power generation, thus fostering the sustained development of the new-energy industry.

( 4) Shijiazhuang Tonghe Electronic Technology Co., Ltd. is primarily responsible for conducting research aimed at engineering and practical application of the project’s outcomes, as well as supporting on-site demonstration applications. The company has participated in the engineering implementation of charging pile fault diagnosis technology and the charging guidance strategy technology for multi-body information interaction among vehicles, stations, roads, and networks. It has made significant contributions to innovation points 3 and 4.

Application Promotion and Socioeconomic Benefits

Application and Promotion: On the new energy generation side, the project’s achievements have been applied to hundreds of wind farms and photovoltaic power stations operated by power generation companies including Longyuan Power of the State Energy Group, Guodian Power of the State Energy Group, and the Liaoning Branch of China Huaneng New Energy Co., Ltd., achieving large-scale, high-quality implementation of the project. On the distribution and consumption side, the project’s results were first piloted in Tianjin and have since been extended to other regions across the country, such as Shandong and Hebei. More than 150 large-scale charging stations across 21 provincial-level administrative regions have achieved user-friendly operation and robust safety protection for urban charging infrastructure, ensuring green mobility for residents and providing strong support for the development of China’s new energy industry, thereby steadily advancing the country’s “dual-carbon” goals.

( 1) Large-scale, high-quality applications. The research and development results of the project—including the new energy operation optimization and fault early warning and diagnosis system—began to be gradually implemented starting in January 2019. Bowang (Zhangbei) New Energy Co., Ltd.’s Haiziwawa Wind Farm, Guohong New Energy Power Generation Co., Ltd.’s Luotaitaizi Wind Farm, and the Xiayingdi Wind Farm of the Zahanuor Branch of Inner Mongolia Huo Coal Hongjun Aluminum & Electricity Co., Ltd. ， The Fuxin, Jinzhou, Panjin, Tieling, and Yingkou branches under the Liaoning Branch of China Huaneng New Energy Co., Ltd. Over a hundred wind farms have adopted these technologies on a large scale; more than twenty photovoltaic power stations, including the Guodian Investment Hebei Quyang Photovoltaic Power Station and the Laiyuan Photovoltaic Power Station, have also widely implemented these solutions. The application of these project outcomes has effectively enhanced the overall efficiency and operational stability of new-energy power stations, reduced the frequency of failures in new-energy generation equipment, increased the number of available operating hours for new-energy power stations, and improved the economic benefits of these stations.

( 2) The project has significantly enhanced China’s level of digitalization, informatization, and intelligentization in the new energy sector. The project’s outcomes have been promoted and applied by Guoneng Sida Technology Co., Ltd. and Shijiazhuang Tonghe Electronic Technology Co., Ltd., and are now being utilized at numerous new-energy power stations under companies such as China General Nuclear New Energy Company, Mingyang Smart Energy Group, and the State Energy Group. Relying on these project results, a smart management system for wind farms—built with technical support from Beijing Gengton and Baoding ManNiu Information Technology Co., Ltd.—has been established. Currently, the system has already connected data from approximately 20,000 wind turbine units worldwide, and it will continue to integrate data from additional units in the future. Under the condition of meeting the stability and safety constraints of the power system, the project’s outcomes provide a comprehensive system platform for centralized monitoring, information sharing, fault diagnosis, and maintenance of new-energy power stations, thereby elevating the intelligence and digitalization levels of domestic new-energy stations. This has enabled an operational model featuring unmanned or minimally-staffed operation while ensuring the safe, reliable, and cost-effective operation of the entire new-energy station complex.

( 3) The project has enhanced the operational service technology for China’s new energy power stations, refined the operational service system, and strengthened the skills of new energy operation personnel. The project’s outcomes have been implemented and applied at Guoneng Sida Technology Co., Ltd., where a smart new-energy operation service system has been established, elevating the level of refined operations and maintenance. This has expanded the company’s comprehensive new-energy operation service capabilities while effectively promoting technological innovation in the operation, inspection, maintenance, and training of new-energy power stations. As a result, the technical competence, technical proficiency, and management capabilities of operation, inspection, maintenance, and management personnel have been improved, providing highly qualified and skilled new-energy operation and maintenance technicians for the post-new-energy era and overall enhancing the operational standards of China’s new-energy power stations.

( 4) On the user-side, leveraging the project’s achievements, the Tianjin Jinmen Lake New Energy Vehicle Comprehensive Service Center has been established, featuring 63 charging piles with an online availability rate of 95.2%. The accuracy of charging demand forecasting has improved by 6.3%, and users’ average waiting time has been reduced by 10%. The center now serves over 200,000 vehicle trips annually, and its overall utilization rate of charging stations has reached 70%, twice the national average. This center provides a model for the safe, efficient, and low-carbon operation of large-scale urban charging stations, strongly promoting the development and technological advancement of the electric vehicle industry. The project’s outcomes have been widely adopted and implemented by 21 provincial grid companies in Shandong, Hebei, and other regions, effectively enhancing the safety and operational reliability of large-scale urban charging stations. Moreover, these results have improved the lean management level and operational efficiency of charging stations, further enhancing the charging experience and user loyalty.

The large-scale, high-quality application of the project’s outcomes has effectively enhanced the overall efficiency and operational stability of new-energy power stations, reduced the frequency of failures in critical components, increased the number of available operating hours, boosted power generation and economic benefits, and facilitated the establishment of an intelligent new-energy operation and service system, thereby elevating the level of refined operations and maintenance and achieving the following for new-energy power stations: The levels of “refinement, intelligence, and digitalization.” On the charging-side, this has effectively enhanced the safe operation of large-scale urban charging stations; improved the lean management level and operational efficiency of charging stations; further boosted the charging experience and user loyalty; and laid a solid foundation for achieving the nation’s dual carbon goals of “peaking carbon emissions and achieving carbon neutrality.”

Economic benefits ：

Deadline By the end of 2022, the large-scale implementation of this project had generated approximately 3 billion yuan in additional sales revenue over the past three years (including revenue from increased power generation and cost savings), with cumulative additional profits reaching about 500 million yuan, yielding significant economic benefits.

Social benefits ：

The project’s outcomes have enhanced the digital, informational, and intelligent operation service system for new energy power plants, thereby improving the operational efficiency of these plants. The “lean and intelligent” approach has enabled the “orderly and efficient” operation of new-energy power stations, fostering deep integration of emerging technologies such as intelligent algorithms, data mining, and cloud computing with the new-energy industry. This has played a demonstrative and leading role, further accelerating the rapid development of green energy in our province and providing crucial technological support for building a “Green Hebei.”

The project’s outcomes have enhanced talent development and boosted the skills and competence of operations and maintenance personnel: During the project’s research period, a total of doctoral students were trained. Ten individuals and 45 master’s students; dozens of training sessions have been conducted for personnel from new-energy operation and maintenance companies or operating companies, boosting the intensity of technological innovation in new-energy O&M training, enhancing the technical competence of staff, and building a talent pool to support the nation’s “carbon peak and carbon neutrality” dual-carbon goals.

The project’s outcomes have reduced carbon emissions and increased the integration rate of new energy sources: As of... By the end of 2022, the large-scale implementation of the project had cumulatively increased power generation by approximately 290 million kilowatt-hours over the past three years, reduced carbon emissions by about 2.502 million tons, and saved roughly 92,700 tons of standard coal, laying a solid foundation for China’s green development and the establishment of a resource-conserving society.

The project’s outcomes have enhanced China’s capabilities in intelligent wind power operations and digital wind farms.

The project’s outcomes ensure residents’ green and convenient travel while enhancing the State Grid’s charging service capabilities: It has achieved user-friendly operation, robust safety protection, and intelligent management of large-scale urban charging stations. By leveraging cutting-edge power technologies, it supports residents’ green mobility, strongly underpins the development of China’s new energy industry, and provides crucial assistance. The “dual carbon” goals are steadily advancing.

List of Representative Papers and Monographs

1.  Zhaoyan Zhang , Peiguang Wang*, Ping Jiang Zhiheng Liu, Lei Fu. Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network[J]. Energy, 2021, 240: 122790.

2.  Xia Wang , Jun Zhao Autonomous Switched Control of Load Shifting Robot Manipulators [J] .  IEEE Transactions on INDUSTRIAL   Industrial Electronics , 20 17, 64(9) : 7161-7170.

3.  Zhaoyan Zhang , Yong Zhuang, Xianbao Zha, Kun Zhang, Peiguang Wang *, Shaoke Wang, Shuai Liu Stability analysis of doubly-fed wind generation systems under weak conditions   Power grid based on virtual synchronous control combined with adaptive robust control. Energy Reports, 20 22, 8: 46-56.

4.  Zhibin Liu , Feng Guo, Jiaqi Liu, Xinyan Lin, Ao LI, Zhaoyan Zhang* Zhiheng Liu. A compound coordinated optimal operation strategy for day-ahead, rolling, and real-time operations in an integrated energy system[J], Energies, 2023, 16, 500.

5.  Lei Li , Jian Zhang*, Jing Zhang, Taoyong Li, Weidong Liu , Dan Li, Zhibin Liu* Research on Coordinated Charging and Discharging Operation Mode of Electric Vehicle Based on Time-Space Double-layer Optimization[C]. IOP Conference Series: Earth and Environmental Science, 2020, DOI: 10.1088/1755-1315/ 510/6/062031.

6.  Jiang Ping , Luan Yanjun, Zhang Wei, Tian Jing, Dai Jinchao. Improved PSO-Based Approach Under Partial Shading Multi-peak MPPT Research [J]. Journal of Solar Energy, 2021, 42(8): 140-145.

List of Major Intellectual Property Certificates

1. A big-data-based fault early-warning and diagnosis system for wind turbine units. Invention patent, 202010027269.4, Inventor(s): Zhang Zhaoyan Wang Peiguang; Hao Lei; Zhang Bin; Gao Chunxia, Inventor’s Institution: Hebei University

2. A fault prediction method for wind turbine gearboxes. Invention patent, 202110078440.9, Inventor(s): Zhang Zhaoyan Wang Shaoke; Wang Peiguang; Tian Yaru; Fu Lei; Jiang Ping ; Inventing Institution: Hebei University

3. A fault prediction method for wind turbine generators. Invention patent, 202111290483.X; Inventors: Zhang Zhaoyan Wang Shaoke; Wang Peiguang; Jiang Ping Tian Hua; Tian Yaru; Liu Zhiheng; Fu Lei; Wang Xia ; Inventing Institution: Hebei University

4. A New Energy Vehicle Charging Early-Warning and Protection System. Invention Patent, 202210947849.4, Inventor(s): Liu Zhibin Zhang Liancheng; Ren Siyuan, Inventor’s Institution: Hebei University

5. A charging safety early-warning method and charging pile based on big data. Invention patent, 202011037318.9, Inventor(s): Liu Zhibin Zhao Yizhi; Liu Yajing; Ma Junhua, Inventor’s Institution: Hebei University

6. A Vehicle-Road-Network Load Control Method and System Based on Multi-Source Information Fusion. Invention Patent, 202011037714.1, Inventor(s): Liu Zhibin Liu Yajing; Liu Boqian, Inventor’s Institution: Hebei University

7. An orderly charging method and system for electric vehicles that meets the needs of multiple scenarios. Invention Patent, 202010941378.7, Inventor: Liu Zhibin Liu Yajing; Peng Zihang; Han Yanfan, Inventor’s Institution: Hebei University

8. Shadow Removal Algorithm for UAV Aerial Images of Photovoltaic Arrays. Invention Patent, 202010397671.1. Inventor(s): Jiang Ping Luan Yanjun; Tian Jing; Dai Jinchao, Inventor’s Institution: Hebei University

9. A Low-Power Standby Circuit Method for Power Monitoring of Pure Electric Vehicle Power Batteries. Invention Patent, 202011127253.7. Inventor(s): Zhang Long ; Wu Yan, Inventor’s Institution: Shijiazhuang Tonghe Electronic Technology Co., Ltd.

List of Key Contributors (Rank, Name, Technical Title, Affiliation, Technical Creative Contribution to This Project, Awards Received)

Ranking

Name

Technical Title

Workplace

Completing Unit

Contribution

Awards Received

1

Zhang Zhaoyan

Professor

Hebei University

Hebei University

I am fully responsible for the research on key technologies for equipment health status early warning and diagnosis under smart operations across multiple scenarios in the new energy sector. I have proposed a new energy network switching control theory system that integrates switching control theory with specialized knowledge of new energy technologies, formulated a technical roadmap and real-time implementation plan, and laid a solid theoretical foundation for the stable operation of new energy systems. I also led the development of a digital twin system model and created a cloud-based new energy operation optimization, fault early warning, and diagnostic system. Regarding the innovative aspects... 1, 2, 3, and 4 made creative contributions.

Recipient of the Second Prize for Scientific and Technological Progress in Hebei Province 1 item

2

Liu Zhibin

Senior Engineer

Hebei University

Hebei University

Responsible for developing the overall plan for the project’s research, participated in the development of a digital twin system model for new energy sources, and deeply engaged in the research on a cloud-based operational optimization and fault early-warning and diagnosis system for new energy, intelligent monitoring and diagnostic equipment for charging safety, and a big data security protection platform. Regarding the innovative aspects of this project... 2, 3, and 4 made significant contributions.

Has received the Second Prize of the China Invention Award. One First Prize for Science and Technology from State Grid Tianjin Electric Power Company; two First Prizes for Science and Technology from State Grid Tianjin Electric Power Company.

3

Li Lei

Senior Engineer

State Grid Tianjin Electric Power Company

State Grid Tianjin Electric Power Company

Responsible for the development and implementation of project demonstration applications and promotion plans; assisted in conducting research on digital twin modeling of systems and equipment in various new-energy scenarios; participated in the completion of research on a comprehensive lifecycle health assessment, early warning, and diagnostic system for energy storage devices, charging stations, and other related equipment; led the organization of demonstration applications at several large-scale charging stations; and highlighted the innovative aspects of this project. 2, 3, and 4 made contributions.

Has received the First Prize for Scientific and Technological Progress of Tianjin Municipality. One first-class award and one second-class award; five first-class awards, two second-class awards, and one third-class award for scientific and technological progress from State Grid Tianjin Electric Power Company.

4

Zhuang Yong

Engineer

Guoneng Sida Technology Co., Ltd.

Guoneng Sida Technology Co., Ltd.

I was responsible for the engineering implementation of the digital twin system for new energy power plants and participated in the development of an equipment health assessment, early warning, and diagnostic system tailored to scenarios such as wind power, photovoltaic power, and energy storage. I also took part in the technical research on the health assessment, early warning, and diagnostic system for new energy generation equipment, and contributed to identifying the innovative aspects of this project. 2. Make contributions to 3.

Recipient of the Second Prize for Scientific and Technological Progress in Hebei Province 1 item

5

Dong Jiang

Senior Engineer

Shijiazhuang Tonghe Electronic Technology Co., Ltd.

Shijiazhuang Tonghe Electronic Technology Co., Ltd.

Participated in the research on an active identification method for charging anomalies based on simulated responses and real-time status information; conducted research on second-level, real-time, precise monitoring of charging safety at the edge side and its engineering application; carried out research on integrating fault diagnosis algorithms with hardware products; provided assistance in demonstration applications and promotion of project outcomes; and highlighted the innovative aspects of this project. 3 and 4 made contributions.

6

Cha Xianbao

Senior Engineer

Guoneng Sida Technology Co., Ltd.

Guoneng Sida Technology Co., Ltd.

Assisted in establishing digital twin system models for new energy facilities such as wind farms and photovoltaic power stations, participated in the technical research on health assessment, early warning, and diagnostic systems for new energy generation equipment, and jointly developed a cloud-based system for optimizing new energy operations as well as for fault early warning and diagnosis. Highlighting the innovative aspects of this project. 2. Make contributions to 3.

7

Wang Xia

Professor

Hebei University

Hebei University

Responsible for conducting a comprehensive characterization of new-energy networks that include numerous new energy generation units, energy storage nodes, charging stations, and other components. Established a theoretical framework for network control system switching in new-energy systems and carried out research on multi-switching systems. The research on analyzing system stability and performance within the Lyapunov theoretical framework has involved the development of digital twin models for systems and equipment in multiple scenarios related to new energy sources, contributing to innovation points 1 and 2 of this project.

8

Liu Weidong

Engineer

State Grid Tianjin Electric Power Company

State Grid Tianjin Electric Power Company

I was deeply involved in the implementation of the project and participated in the development of charging pile fault diagnosis technology and vehicle... —Research on charging guidance strategies for multi-body information interaction among stations, roads, and networks, coupled with the development of intelligent monitoring and diagnostic equipment for charging safety and a big-data security protection platform. The project’s outcomes have been implemented and widely applied on-site, contributing to innovation points 3 and 4 of this project.

Recipient of the First Prize for Scientific and Technological Progress from State Grid Tianjin Electric Power Company. 3 items

9

Jiang Ping

Associate Professor

Hebei University

Hebei University

Research was conducted on designing zero-barrier functions based on security protection requirements and on refining conventional controller outputs using optimization algorithms. We also participated in the development of digital twin models for systems and equipment in multiple scenarios involving new energy sources, and provided assistance in demonstrating their practical applications. These efforts highlight the innovative aspects of this project. 1. 2 made contributions.

10

Zhang Long

Senior Engineer

Shijiazhuang Tonghe Electronic Technology Co., Ltd.

Shijiazhuang Tonghe Electronic Technology Co., Ltd.

Responsible for research on the engineering practical application of project outcomes and for supporting on-site demonstration applications. Participated in the development of charging pile fault diagnosis technology and vehicle... The engineering application of the charging guidance strategy technology for multi-body information interaction among stations, roads, and networks has been implemented, promoting the widespread adoption of the project and contributing to innovation points 3 and 4 of this project.

Statement on Collaborative Relationships Among Completion Personnel

The project has established a collaborative research team involving industry, academia, research, and application. The team comprises Hebei University, State Grid Tianjin Electric Power Company, Guoneng Sida Technology Co., Ltd., and Shijiazhuang Tonghe Electronic Technology Co., Ltd. The project team consists of researchers from four institutions. With Zhang Zhaoyan as the primary contributor, the team worked collaboratively to overcome challenges and ensure the project’s efficient advancement and high-quality completion.

Based on the R&D needs of the project, the project team has organized work in the following areas: theoretical research and operational stability optimization for network switching systems in the new energy sector; digital twin technology that integrates equipment mechanism models with multi-source data-driven approaches in various new-energy scenarios; a comprehensive health assessment and diagnostic system covering the entire lifecycle of equipment for diverse scenarios including wind power, photovoltaic, energy storage, and charging stations; and intelligent monitoring and diagnostic technologies for charging safety. Each team member has been assigned tasks appropriately according to their research expertise and industrial strengths, working collaboratively and synergistically. Through industry partnerships, joint intellectual property rights, and co-authored publications, they have made significant contributions to the project’s R&D efforts.

( 1) The first author, Zhang Zhaoyan, and the second author, Liu Zhibin, both work at Hebei University. They have collaborated extensively on research projects for a long time. Together, they have completed work on stable operation and optimized control of new-energy power stations, equipment fault early warning, and charging optimization. They jointly carried out the projects titled “Research on Coordinated Optimal Control Algorithms for Distributed Generation Involving Wind Power and Development & Integration of Control Algorithm Packages” and “Module Processing and Testing Services for a Photovoltaic-Storage-Charging-Usage Simulation Platform.” They also co-authored the paper titled “A Compound Coordinated Optimal Operation Strategy of Day-Ahead-Rolling-Realtime in Integrated Energy System.”

( 2) First author Zhang Zhaoyan, fourth author Zhuang Yong, sixth author Cha Xianbao Jointly complete and publish the paper « Stability Analysis of Doubly-fed Wind Generation Systems under Weak Power Grid Based on Virtual Synchronous Control Combined with Adaptive Robust Control.

( 3) The first inventor, Zhang Zhaoyan, the seventh inventor, Wang Xia, and the ninth inventor, Jiang Ping, all work at Hebei University. Together, they have completed the central government-funded local science and technology development project titled “Online Early Warning System for Wind Turbine Units Throughout Their Entire Lifecycle Based on Cloud Architecture and Its Demonstration Application,” as well as the joint invention patent entitled “A Fault Early Warning Method for Wind Turbine Generators.”

( 4) The first author, Zhang Zhaoyan, and the ninth author, Jiang Ping, both work at Hebei University. They co-authored the paper titled “Energy Management of Ultra-Short-Term Optimal Scheduling of Integrated Energy System Considering the Characteristics of Heating Network,” and jointly hold the invention patent titled “A Fault Prediction Method for Wind Turbine Gearboxes.”

( 5) During his tenure at Beihua Aerospace Industry College, the second contributor, Liu Zhibin, together with the fifth contributor, Dong Jiang, and the tenth contributor, Zhang Long, jointly completed the project “Development of an Early Warning and Protection System for Electric Vehicle Charging.”

( 6) The second author, Liu Zhibin, the third author, Li Lei, and the eighth author, Liu Weidong, jointly published the paper titled “Research on Coordinated Charging and Discharging Operation Mode of Electric Vehicle Based on Time-Space Double-layer Optimization.”

( 7) The third author, Li Lei, and the eighth author, Liu Weidong, both work at Tianjin Electric Power Company of State Grid. They have long-term collaborated on research into charging pile fault diagnosis technology and charging guidance strategies for multi-body information interaction among vehicles, stations, roads, and networks. Together, they have completed and published papers such as “Research on Coordinated Charging and Discharging Operation Mode of Electric Vehicle Based on Time-Space Double-layer Optimization.” They have also jointly completed the Tianjin Key R&D Program project titled “Research and Application of Key Technologies for Intelligent Grid and Multi-Source Information Fusion and Regulation.”

( 8) The seventh contributor, Wang Xia, and the ninth contributor, Jiang Ping, jointly completed the National Natural Science Foundation project titled “Adaptive Control of Switching Systems for Constrained Problems in Aero-Engines.”

Summary Table of Completed Human Collaboration Partnerships

Serial number

Cooperation method

Collaborator / Project Ranking

Cooperation period

Collaborative Outcomes

Note

1

Co-authored paper

Zhang Zhaoyan /1, Liu Zhibin /2

2018-2022

A compound coordinated optimal operation strategy for day-ahead, rolling, and real-time operations in an integrated energy system

2

Project

Zhang Zhaoyan /1, Liu Zhibin /2

2018-2022

Research on Coordinated Optimization Control Algorithms for Distributed Generation Involving Wind Power and Development & Integration of a Control Algorithm Package

3

Project

Zhang Zhaoyan /1, Liu Zhibin /2

2018-2022

Light-Storage-Charging-Usage Simulation Platform Module Processing and Testing Services

3

Co-authored paper

Zhang Zhaoyan /1, Zhuang Yong /4, Cha Xianbao /6

2017–2022

Stability Analysis of Doubly-Fed Wind Generation Systems Under Weak Power Grids Based on Virtual Synchronous Control Combined with Adaptive Robust Control

4

Joint project initiation

Zhang Zhaoyan /1, Wang Xia /7, Jiang Ping /9

2017–2022

Cloud-Based Online Early Warning System for the Entire Lifecycle of Wind Turbines and Its Demonstration Application

5

Joint intellectual property

Zhang Zhaoyan /1, Wang Xia /7, Jiang Ping /9

2017–2022

A fault prediction method for wind turbine generators

6

Co-authored paper

Zhang Zhaoyan /1, Jiang Ping /9

2017–2022

Energy management for ultra-short-term optimal scheduling of integrated energy systems, taking into account the characteristics of heating networks.

7

Joint intellectual property

Zhang Zhaoyan /1, Jiang Ping /9

2017–2022

A Fault Prediction Method for Wind Turbine Gearboxes

8

Project

Liu Zhibin /2, Dong Jiang /5, Zhang Long /10

2019-2022

Development of an Electric Vehicle Charging Early-Warning and Protection System

9

Co-authored paper

Liu Zhibin /2, Li Lei /3, Liu Weidong /8

2019-2022

Research on Coordinated Charging and Discharging Operation Mode of Electric Vehicles Based on Time-Space Double-Layer Optimization

10

Joint project initiation

Li Lei /3, Liu Weidong /8

2019-2022

Research and Application of Key Technologies for Intelligent Grid Integration and Multi-Source Information Fusion Control

11

Joint project initiation

Wang Xia /7, Jiang Ping /9

2015–2022

Adaptive Control of Switching Systems for Constrained Problems in Aero-Engines