China Electric Power Research Articles

Preface

Against the backdrop of the rapidly evolving global energy transition, power, grid and energy storage technology are receiving unprecedented attention as key forces in promoting cleaner, smarter and more efficient energy sources. The Proceedings of the 2024 2nd International Conference on Power, Grid and Energy Storage (PGES 2024) brings together the latest research results and cutting-edge explorations of experts and scholars in the field of power energy from all over the world, demonstrating the vigorous vitality and unlimited potential of this field. The PGES 2024 took place virtually in Kunming, China from June 21st to 23rd, 2024. The conference was organized in order to provide an international academic forum for promoting research and other academic activities as well as developing research cooperation in field of power, grid and energy. It is worth mentioning that the number of international participants in this conference hit a record high. Experts and scholars from Canada, Malaysia, Italy, New Zealand, China, and many other countries and regions gathered together to contribute to the development of power, grid and energy. They brought cutting-edge technologies and research results in their respective fields, injecting new vitality and momentum into the conference. The conference fully demonstrated the characteristics of globalized exchanges. Participants from different countries and regions promoted international academic exchanges and cooperation by sharing their research achievements and experiences. At the same time, the conference also invited a number of internationally renowned experts and scholars to give keynote speeches, bringing participants cutting-edge academic views and profound insights. The keynote speakers include Hossam A. Gabbar (full Professor of Ontario Tech University, Canada), Tao Lin (Professor of Wuhan University, China), M A Hannan (Professor of Sunway University, Malaysia), Pierluigi Siano (Full Professor of University of Salerno, Italy), Udaya Madawala (Professor of The University of Auckland, New Zealand), as well as Guobing Zhou (Professor of North China Electric Power University, China). In addition, the conference also organized oral and poster presentations, which provided participants with more opportunities for in-depth exchanges and discussions. These activities not only helped to enhance the friendship and cooperation among the attendees, but also laid a solid foundation for promoting international exchanges and cooperation in the field of information education and artificial intelligence. The topics of papers collected and undergone rigorous peer review in the Proceedings of PGES 2024 can be classified as follows: Power Systems and Automation, Energy Storage Equipment and Systems, Smart Grid Information Engineering, Electrical Power Generation Technology, Power Transmission and Distribution, Communication and Control in The Power System, etc. We would like to express our sincere thanks and gratitude to all the keynote speakers, authors, committee members and other colleagues for the success of PGES 2024, which has given rise to this present volume of selected papers. We would also like to acknowledge the staff of Journal of Physics: Conference Series for their effective work to make this Proceedings published. The Committee of PGES 2024 List of Committee Member is available in this Pdf.

Intelligent Power System Stability Assessment and Dominant Instability Mode Identification Using Integrated Active Deep Learning.

Simulation analysis is critical for identifying possible hazards and ensuring secure operation of power systems. In practice, large-disturbance rotor angle stability and voltage stability are two frequently intertwined stability problems. Accurately identifying the dominant instability mode (DIM) between them is important for directing power system emergency control action formulation. However, DIM identification has always relied on human expertise. This article proposes an intelligent DIM identification framework that can discriminate among stable status, rotor angle instability, and voltage instability based on active deep learning (ADL). To reduce human expert efforts required to label the DIM dataset when building DL models, a two-stage batch-mode integrated ADL query strategy (preselection and clustering) is designed for the framework. It samples only the most helpful samples to label in each iteration and considers both information contents and diversity in them to improve query efficiency, significantly reducing the required number of labeled samples. Case studies conducted on a benchmark power system (China Electric Power Research Institute (CEPRI) 36-bus system) and a practical large-area power system (Northeast China Power System) reveal that the proposed approach outperforms conventional methods in terms of accuracy, label efficiency, scalability, and adaptability to operational variability.

A spatiotemporal analysis of personal casualty accidents in China's electric power industry

The electric power industry in China has experienced significant growth in recent years. Despite efforts to improve safety management in the industry, accidents still occur frequently. This study aimed to analyze the personal casualty accidents in the electric power industry from 2012 to 2021. Specific methods used include descriptive analysis, principal component analysis, and Theil index model. The results indicated that fall, electric shock, and collapse were the primary types of accidents, accounting for 59.65 % of all accidents. Accidents were higher in April and August, but lower in February. While the accident rate was relatively low on Mondays, the fatality rate was higher on Mondays, Thursdays, and Fridays. Taking into account accidents, workload, and labor, we found that Ningxia, Hainan, and Guangxi exhibited subpar levels of safety management within the electric power industry. The overall difference in the number of deaths in 31 provinces was significant in 2012 and 2016. It was significantly reduced in 2021. In terms of the proportion of intraregional and interregional differences, there were significant differences in the number of accidents and fatalities between provinces in the Central China and North China regions. This study provides valuable insights for enterprises to formulate accident prevention strategies and for the government to develop relevant policies.

Water availability may not restrict the implementation of carbon capture utilization and storage technology: Evidence from China's electric power sector

Carbon capture, utilization and storage (CCUS), a water resource-intensive technology, has been projected to be restricted by water resources in the future. However, the water-saving effects resulting from technology progress and CO2-Enhanced water recovery (CO2-EWR) process are not been fully considered. Based on the learning curve theory, this study proposes a new water accounting system for CCUS retrofitting of coal-fired power plants (CFPPs) from a dynamic perspective considering power generation, carbon capture, and CO2-EWR technology. The results show that the total water withdrawal per unit of CCUS retrofitting with the first-generation capture technology will decrease by 66.89 %, and the total water consumption per unit of that will decrease by 74.70 % from 2021 to 2050. By contrast, the water withdrawal and consumption per unit with the second-generation capture technology will decrease by 74.12 % and 82.51 %, with the overall unit water consumption below 0.5 m3/MWh. Moreover, the water usage caused by CCUS retrofitting will be greatly relieved through the progress of geological sequestration technology (especially the CO2-EWR). In addition, the water usage during the capture process for circulation cooling and air-cooling would present an “inverted U” shaped trend affected by the capture scale and technology progress. Remarkably, the water withdrawal and consumption intensity of CFPPs with air-cooling technology is significantly lower than those of the circulation cooling technology for power generation, while the opposite happens if the capture technology is applied. Even so, CCUS retrofitting for the CFPPs with air-cooling technology can save 60 × 104 m3 of water resource after 2040, which is positive for the CCUS deployment in the arid areas of China.

Evaluation index system for carbon information disclosure quality in China's electric power sector based on a mutual information and back propagation neural network model

This paper employs the Mutual Information (MI) and Back Propagation (BP) neural network model to screen the preliminarily constructed evaluation index system for carbon information disclosure (CID) quality of public companies in China's electric power sector (EPS), which is subsequently incorporated into the fuzzy comprehensive evaluation (FCE) method for evaluation application. The results show that (1) after screening, 19 out of the 31 preliminarily constructed indicators constitute an optimal index set, and (2) the evaluation application of the screened index system validates the feasibility and applicability of the index system. Simultaneously, the evaluation results reveal a generally low CID quality in the EPS.

Preface

Available on the latest research progress of clean energy and power generation technology, this paper volume gathers a bunch of papers collected from 2023 8th International Conference on Clean Energy and Power Generation Technology (CEPGT 2023), held via virtual form in Zhuhai, China during December 15th to 17th, 2023.The Conference was attended by about 100 delegates around the globe. In the opening ceremony speech, all academicians, experts and scholars were welcomed to attend the Conference and to share insightful speeches and presentations. Then in the keynote speech part, Prof. Marc A. Rosen (Ontario Tech University, Canada), Prof. Haiping Yang (Huazhong University of Science and Technology, China), Prof. Qinmin Yang (Zhejiang University, China), Prof. Qiang Lu (North China Electric Power University, China) and other professors made wonderful academic reports on international frontier hot spots. Apart from the keynote speeches, oral and poster presentation parts were also held and displayed by various scholars, leading to a warm atmosphere of academic discussion.We received a number of submissions from the Conference. After rigorous review and review rebuttal process by related top experts, various excellent papers were accepted and included in this paper volume. These papers cover many topics of the Conference theme, including Energy Security and Clean Use, Energy Conservation and Emission Reduction, Biomass Energy Engineering, Hydroelectric Power Generation, Solar Photovoltaic Power Generation System, etc. The works of this volume can promote the development of clean energy and power generation technology, and thereby enhance scientific information interchange among scholars from top universities, research centers and high-tech enterprises working all around the world.Featuring the most cutting-edge research directions and achievements related to clean energy and power generation technology, this Conference provided the most comprehensive research in related fields and a more comprehensive understanding of the latest results of cross researches in the fields. Meanwhile, it also helped researchers and engineers understand the research frontier, as well as discover the solutions to potential problems.We would like to acknowledge the authors for their contributions and the reviewers for their time to review the submissions. We are thankful to all the committee members and advisors of this volume. Finally, our appreciation also goes to the editors and members of Journal of Physics: Conference Series for their efforts in publishing this volume.We hope that it will serve as a reference for researchers and practitioners in academia and industry in the areas related to clean energy and power generation technology.The Committee of CEPGT 2023List of Committee Member is available in this pdf.

Preface

The advent of the fourth information revolution has made the digital economy a major driver of energy transition and low-carbon development. The overall architecture of smart energy is based on intelligence as the core, and based on infrastructure platforms such as intelligent cloud and IoT, as well as AI middle platform, Data middle office ether, etc. And with the help of cloud computing, artificial intelligence, big data, blockchain, digital twins and other technologies, smart energy can promote the intelligent transformation of energy enterprises ultimately.Against such background, the 2023 2nd International Conference on Smart Energy and Electrical Engineering (SEEE 2023) was held via hybrid form during December 22nd to 24th, 2023 in Malaysia. It was attended by about 50 researchers, scientists, engineers, and students working in the fields of smart energy and electrical engineering.The aims of SEEE 2023 are:To create an academic forum for sharing, communication and research at the international level, so that participants can be informed of the latest research directions, contents and results of smart energy and electrical engineering.To provide approaches to the main problems facing smart energy and electrical engineering, creating spaces that encourage discussion and joint development of research, technology development, and innovation.The excellent papers selected form the submissions were approved for presentation at the Conference and publication in this Conference Proceedings. Among the submissions are some submitted from abroad, but are unfortunately not accepted after rigorous review processes.There was an enabling environment for discussion and exchange of ideas, during which topics such as Core Technology of Intelligent Energy Equipment, Smart Transmission and Distribution, Power Grid Dispatching and Automatic Control, Power Systems and Energy, Electrical Theory and New Technology, etc. were presented. Some of the important issues were the sharing and discussion of Wireless Power Transfer and its Application on Electric Vehicle Wireless Charging by Prof. Yiming Zhang (Fuzhou University, China), Corona Loss Characteristics of EHV/UHV AC Transmission Lines by A. Prof. Shilong Huang (North China Electric Power University, China), Integrated Renewable Energy System based on Hydrogen by Prof. Mohan Lal Kolhe (University of Agder, Norway), etc.As in the last meeting, SEEE 2023 was again a space for the integration of undisputed knowledge and sharing of peer experiences within the specific areas of smart energy and electrical engineering. Both conference and presentation sessions were attended by many conference attendees, allowing closer relationships, both academic, as well as scientific and personal. The cordiality and good treatment of the attendees promoted a climate of friendship, which we could enjoy during all the development of the conference agenda.We would like to extend an enthusiastic round of thanks to all our conference authors and speakers for their excellent contributions. We are indebted to the Technical Program Committee for their efforts in making and pushing the conference program. Thanks also to the members of Journal of Physics: Conference Series for making the publication of SEEE 2023’s Proceedings possible.List of Committee Member is available in this pdf.

The new situation and optimization strategy of China's power grid management system

The system mechanism of power grid management is an important institutional basis to support the development of electric power industry, and has always been an important controversial issue in China's electric power system reform. Based on the current situation of China's power grid management system, this paper analyzes the new situation, analyzes the main problems, and finally, based on the background of new power system construction, systematically puts forward the overall thinking and specific strategies of China's power grid management system optimization.

An Analysis on the Typicality of Language Landscape in North China Electric Power University

This paper takes the typical language landscape of the campus of North China Electric Power University as the research object. The purpose of this paper is to analyze and explore the emergence of the problematic language landscape of the university campus found in the field investigation and investigation of the team. The top-down language landscape of the campus is investigated, summarized and analyzed from the aspects of the combination form, arrangement mode, naming mode and function of the code.

Utilisation of Deep Learning (DL) and Neural Networks (NN) Algorithms for Energy Power Generation: A Social Network and Bibliometric Analysis (2004-2022)

The research landscape on the applications of advanced computational tools (ACTs) such as machine/deep learning and neural network algorithms for energy and power generation (EPG) was critically examined through publication trends and bibliometrics data analysis. The Elsevier Scopus database and the PRISMA methodology were employed to identify and screen the published documents, whereas the bibliometric analysis software VOSviewer was used to analyse the co-authorships, citations, and keyword occurrences. The results showed that 152 documents have been published on the topic comprising conference proceedings (58.6%) and articles (41.4%) between 2004 and 2022. Publication trends analysis revealed the number of publications increased from 1 to 31 or by 3,000% over the same period, which was ascribed to the growing scientific interest and research impact of the topic. Stakeholder analysis revealed the top authors/researchers are Anvari M, Ghaderi SF and Saberi M, whereas the most prolific affiliation and nations actively engaged in the topic are the North China Electric Power University, and China, respectively. Conversely, the top funding agency actively backing research on the topic is the National Natural Science Foundation of China (NSFC). Co-authorship analysis revealed high levels of collaboration between researching nations compared to authors and affiliations. Hotspot analysis revealed three major thematic focus areas namely; Energy Grid Forecasting, Power Generation Control, and Intelligent Energy Optimization. In conclusion, the study showed that the application of ACTs in EPG is an active, multidisciplinary, and impact area of research with potential for more impactful contributions to research and society at large.

Effect of combining valsartan and amlodipine in the treatment of type 2 diabetes mellitus complicated by hypertension

Purpose: To investigate the efficacy of combining valsartan and amlodipine on patients who were co-morbid with type 2 diabetes mellitus (T2DM) and hypertension.
 Methods: The medical records of 110 patients treated in North China Electric Power University Hospital, Beijing, China from July 2018 to October 2022 were retrospectively analyzed. Control group (CG; n = 50) was administered oral amlodipine (5 mg daily for 6 months), while the study group (SG; n = 60) received one tablet of co-formulated valsartan (80 mg)) and amlodipine (5 mg) daily for 6 months. All the patients, in addition to the above drugs, were also placed on insulin and atorvastatin calcium. After a 6-month treatment period, the therapeutic effect and incidence of adverse effects were compared between CG and SG. Blood glucose-related indices (glycosylated hemoglobin (HbA1c), 2 h postprandial blood glucose (2 h PG), and fasting blood glucose (FBG)) and blood pressure indices, viz, (diastolic blood pressure (DBP), systolic blood pressure (SBP)) were compared.
 Results: Compared to the pre-treatment values, both groups showed significant decrease in 2 h PG, FBG, HbA1c, SBP and DBP after treatment (p < 0.05), but the 2 h PG, FBG, HbA1c, SBP and DBP in SG were significantly lower in comparison to CG (p < 0.05). The overall response rate (ORR) of CG was significantly lower in comparison to SG (p < 0.05). In SG, there was significant reduction in the incidence of adverse effects compared to CG (p < 0.05).
 Conclusion: The combination of valsartan and amlodipine is effective in treating T2DM co-morbid with hypertension, and satisfactorily controls blood glucose level and blood pressure with a relatively high level of safety. Further experiments would be required to ascertain the reliability of these findings.

Financial Risk Evaluation and Prevention and Control Methods of Listed Companies in China's Electric Power Industry

With China's economy entering the stage of rapid development, the competition of listed companies in the electric power industry belonging to the national economy is also very fierce, and it is easy to appear many problems related to financial risks. Through the research on the current situation of financial risk of listed companies in the power industry, this paper has an in-depth understanding of the types of corporate financial risk and the ways of evaluation, and discusses the ways of preventing financial risk combined with the concrete practice, so as to provide some feasible suggestions for promoting the further development of listed companies in the power industry. The types of financial risks are very complex, and enterprise managers need to make accurate decisions on the long-term development of the company according to the actual situation, so as to help the normal operation of the financial market and promote the progress of society.

Synthesis Load Model With Renewable Energy Sources for Transient Stability Studies

Increased penetration of renewable energy sources (RES) has brought challenges to load modelling techniques. This paper proposes a synthesis load model with RES (SLMR), and elaborates related industrial practice conducted by China Electric Power Research Institute. Several practical issues are addressed in designing and implementing SLMR, such as load survey and representation of different types of RESs. Besides, three new modelling concerns brought by RESs are novelly addressed in the paper, i.e., aggregation of various RES parameters, consideration of various RES terminal voltage, and additional line loss due to RES response. Parameterization of the SLMR calibrates widely varied node voltage in distribution grid, and aggregates them to one equivalent node. The proposed SLMR is practically applied in industrial works, which is demonstrated in the paper.

Towards a Greener Future: Analyzing the Trends and Influences in Sustainable Energy Literature

The growth in sustainable energy relies significantly on the utilization of clean energy sources, attracting increasing attention in the literature with substantial growth in research outputs. This study employs bibliometric analysis via Scopus to depict the current cleaner energy research landscape and future directions. It amalgamates trends and influential research at the sustainability-renewable energy intersection. By mapping notable authors, institutions, and research clusters, it highlights interdisciplinary aspects across engineering, environmental science, economics, and policy studies. The journal Renewable and Sustainable Energy Reviews is pivotal in publishing articles on sustainable development and renewable energy. China leads in related research, with North China Electric Power University as a major contributor. The most cited article in Nature (2012) underscores the importance of sustainable energy for global prosperity, exploring solar, water-based, and biofuel energy, and outlining pathways for a sustainable future. This research not only reviews the current state-of-the-art literature but also informs researchers regarding the critical pathways and emerging trends in the sustainable development goals.

Research on Control Strategy of Power Engineering Quality Management Based on Safety Management

Especially after the 18th National Congress of the Communist Party of China, with the rapid development of social economy, the development of electric power engineering in China has made significant improvements. In the quality control process of electric power engineering, we must pay attention to the importance of safety management. Only the quality control strategy of electric power engineering based on safety management can ensure the sustainable development of China's electric power engineering construction industry.

Digital Finance & Green Innovation Review Paper with special reference to Oman and Bibliometric Analysis for the Duration of 2017-2023

This bibliometric analysis highlighted the transformative role of blockchain technology in reshaping the banking sector and amplifying its value for stakeholders. Using data extracted from the Dimension AI database, the study centers on English-language articles from 2017 to 2023, which were processed and visualized using Excel and Vos-viewer. The annual publication growth rate in Digital Finance and Green Innovation stood at 33.74%. A peak of 1,197 citations in 2022 marks heightened scholarly engagement. Diverse citation counts across articles underscore the varied academic impact. Journals like 'Technological Forecasting and Social Change' are pivotal, with "Energy Policy" distinguishing itself in volume and impact. The Beijing Institute of Technology and North China Electric Power University emerge as influential contributors, with China, the US, and the UK leading globally in publications. Thematically, the synthesis of fintech, sustainability, innovation policy, and green finance signals the domain's depth and interdisciplinarity. Exploring economic, environmental, societal, and policy facets of Digital Finance and Green Innovation is imperative.

Study on the spatial correlation effects and influencing factors of carbon emissions from the electricity industry: a fresh evidence from China.

Carbon emissions from the electricity industry (CEEI) account for a large proportion of China's total carbon emissions, and it is important to study the spatial correlation between CEEI and the influencing factors to promote cross-regional synergistic emission reduction and low-carbon development of the power system. In this paper, the quasi-input-output (QIO) model is applied to assess the transfer of carbon emissions generated by electricity trading based on the consideration of electricity carbon transfer, and the exploratory spatial data analysis (ESDA) method is applied to analyze the spatial correlation effect of carbon emissions from China's electric power sector from 2001 to 2020, analyzes its distribution pattern in both spatial and temporal dimensions, and applies the improved logarithmic mean Divisia index (LMDI) two-stage decomposition model to decompose the changes in CEEI into 11 influencing factors from the perspective of the whole industrial chain of power production, transmission, trade, and consumption. The research results show that (1) the spatial distribution of CEEI has obvious unevenness and aggregation characteristics, with high-high aggregation areas and hot spot aggregation areas generally concentrated in the North China Power Grid and the East China Power Grid, but the aggregation trend is gradually decreasing, while low-low aggregation areas and cold spot aggregation areas are concentrated in the Northwest China Power Grid and the Central China Power Grid, but the area is very limited. (2) The direction of carbon emission diffusion in China's electricity industry is gradually transitioning from southwest-northeast to northwest-southeast, and the east-west diffusion trend is stronger than the north-south diffusion trend and carbon emissions are gradually shifting to the northwest grid. (3) The total amount of electricity production is the most influential factor in the change of CEEI, driving the cumulative growth of CEEI by 4495.34 Mt, followed by GDP per capita and electricity consumption intensity. Coal consumption for power generation, the share of thermal power, and net electricity exports were the main factors inhibiting the increase in carbon emissions from the power sector, with cumulative contributions of -797.74 Mt, -619.99 Mt, and -47.76 Mt, respectively.

Research on EPC Construction Mode of China Informatization Project

EPC(Engineering, Procurement, Construction) has a history of decades in global development, has been introduced to China for more than 40 years, and is widely used in China's chemical, electric power, construction, energy, and other construction projects. With the development of informatization in China, the construction mode of informatization projects continues to evolve, and the EPC construction mode has also been applied and promoted in the informatization industry and has promoted the construction efficiency of informatization projects. The author analyzes and studies the development of EPC in China and the application and practice of EPC mode in informatization projects, and makes a case analysis through the EPC construction mode practice of informatization projects. Through the analysis and case study, the author provides reference and reference for the construction of informatization projects using EPC mode in the development of the digital economy in China.

Sensitivity analysis in multi-criteria decision making: A state-of-the-art research perspective using bibliometric analysis

In the present era, the implementation of scientifically grounded Multi-Criteria Decision Making (MCDM) has emerged as a pivotal solution to diverse decision-making challenges across various domains. Although a substantial body of exploratory, conceptual, and experimental studies exists, only 9.457% studies have incorporated sensitivity analyses to assess the robustness of MCDM methods. An exhaustive scientific exploration of sensitivity analysis within the scope of MCDM is thus lacking. This research aims to address this gap through Bibliometric Analysis while examining 1374 articles published between January 2000 and March 2023 from the Scopus database. Using RStudio (Biblioshiny), CiteSpace, and VOSviewer software, the study constructs a visual representation of the most prolific countries, institutions, and authors. Impressively, China takes the lead in article publications, while India excels in international collaboration. “An extended TODIM multi-criteria group decision-making method for green supplier selection in an interval type-2 fuzzy environment,” featured in the Journal of Environmental Management, emerges as the most cited paper with a total citation of 455. The study also identifies the top three most cited journals, namely “Journal of Cleaner Production,” “Expert Systems With Applications,” and “Computers and Industrial Engineering.” “North China Electric Power University” is the leading institute with the highest research outputs. “Pamučar D” is the most cited author, with 2594 citations and 39 articles, followed by “Kahraman C” and “Zavadskas EK. This study sheds light on trends in scientific developments and collaborations, providing a model for the application of sensitivity analysis in MCDM research and highlighting global trends. An understanding of the current state of sensitivity analysis research can assist researchers working in the entire domain of MCDM. Additionally, the visualization provides prescriptive data for future work and applications related to sensitivity analysis.

The Application and Research of Translation Studios in the Development of MTI at Polytechnic University

As exchanges with the global community continue to increase, the translation field presents significant challenges that capture the attention of researchers. The new era demands a reform in the traditional approach to cultivating translation talents. Particularly, the form and quality of practical teaching need improvement to adapt to the changing demands of the market. University translation studios can to some extent compensate for the shortcomings of traditional classroom teaching and workshop-style practical training at Polytechnic University. Taking the author's own university as an example, this paper explores the significance, feasibility, and operational model of the university translation studio. The paper concludes that the purpose of the university translation studio is to enhance students' translation skills, application of translation techniques, project management, professional demeanor, task handling, and teamwork capabilities. This kind of studio elevates the ability of both faculty and students to serve the local community and society, thereby making a positive contribution to the comprehensive development of the North China Electric Power University's Master of Translation and Interpreting program.