Power Enterprises Research Articles

Research on the Innovative Ideological and Political Work of Young Employees in Electric Power Enterprises

As the backbone of the development of electric power enterprises, young employees’ working attitude determines the vitality of an enterprise to a large extent. Therefore, enterprises need to carry out scientific and reasonable ideological and political work for young employees for the current development needs and to promote the rapid growth of young employees. Based on this, the study carries out detailed research and discussion on the current ideological and political work of young employees in electric power enterprises with personal practical research experience, to innovate and provide a steady stream of ideological and political momentum for their high-quality development.

Analysis and Value Evaluation of Carbon Emission Reduction Strategies in the Power Industry Based on Real Options Theory and XGboost Algorithm

China, as the world’s largest energy consumer, has made significant commitments regarding carbon peaking and carbon neutrality. In order to realize the goal of “dual carbon,” this paper proposes a method for analyzing and evaluating carbon emission reduction strategies in the electric power industry based on physical options theory and the XGBoost algorithm. Starting from the study of carbon emission reduction strategies for power enterprises, the model is oriented towards investment in energy-saving and emission reduction technologies for thermal power, aiming to construct the least-cost carbon emission reduction strategy. Additionally, it comprehensively considers changes in carbon trading mechanisms and the uncertainty of investment budgets for emission reduction, integrating machine learning algorithms to assess the emission reduction value of enterprises during the research period. The aim is to provide theoretical guidance and strategic suggestions for existing thermal power enterprises to cope with the implementation of carbon trading mechanisms. Finally, through case analysis, the effectiveness of this method is validated.

Research on Non-Standard Business Optimization of Insurance Companies Under Computer Big Data

This article mainly describes a lightweight framework based on J2EE (Struts+ Spring+ Hibernate). Then the paper puts forward the design and implementation scheme of the electric power enterprise insurance system based on J2EE. The technical architecture, function model, data model, information security mechanism and test specification of the system are emphatically described. The goal is to use this architecture to increase program reusability and reduce engineering complexity. The NP method is used to screen the customers in the insurance system, so as to improve the effectiveness of customer relationship management. Finally, the feasibility of the proposed algorithm is verified by computer simulation. This method can not only ensure that probability 1 converges to the optimal solution, but also improve the efficiency of customer feature selection.

Research on the relationship between carbon performance and financial performance of electric power enterprises under the background of “dual carbon”

Under the background of “dual carbon,” the power industry, as a pillar industry of the national economy, is ushering in changes. Based on the data of listed companies in the electric power production and supply industry from 2010 to 2020, this paper takes the operating income corresponding to each unit of carbon emission as the substitute variable of carbon performance (CP). After dimensionality reduction of 12 financial indicators through factor analysis, this paper establishes a comprehensive indicator of financial performance (FP), and establishes panel data to explore the relationship between CP and FP of electric power enterprises. To mitigate the endogeneity problem, 2SLS regression was performed using instrumental variables. The results show that CP has a positive and sustainable impact on the FP, which indicates that power enterprises need to pay attention to the long-term management of carbon emission reduction, so that the improvement of FP of enterprises can achieve sustainable development, which is in line with the expectations of Porter’s hypothesis and stakeholder theory. In addition, firm size plays a negative moderating role in the relationship between CP and FP. The research results provide a path and basis for encouraging power enterprises to improve CP and help China achieve the goal of “dual carbon” as soon as possible.

The impact of environmental regulation on green investment efficiency of thermal power enterprises in China-based on a three-stage exogenous variable model

Due to the increased frequency of extreme weather events and the implementation of the China’s dual-carbon target, thermal power companies have been under pressure to construct green infrastructure and to actively pursue low-carbon transformation in response to stricter environmental regulations. This research thus selects 30 listed thermal power enterprises in China as study objects and assesses their green investment efficiency in the low-carbon transition process using three-stage DEA evaluation model with environmental regulation as an exogenous variable. Based on this, a benchmark regression model is used to corroborate the relationship between environmental regulation and green investment. Simultaneously, we carry out analysis to compare the correlation between thermal power firms’ green investment efficiency and their focus on green investments. The results show in terms of total efficiency that environmental regulation significantly improves the total efficiency of 80% of thermal power enterprises compared to the absence of this exogenous variable. With the addition of environmental regulation, firms’ total efficiency declines gradually in general from 2018 to 2022, with the mean value of efficiency falling by 0.068. In terms of stage-specific efficiency, the efficiency of the green investment stage of the majority of firms is between 0.3 and 0.6, which is much lower than that of the operational stage and the market performance stage. In terms of sub-indicator efficiency, both green investment efficiency and social donation efficiency among thermal power enterprises show obvious polarization, with 30% of them having an efficiency of 1 and 30% less than 0.1. In terms of green investment focus, thermal power unit renovation has a more obvious role in boosting the green investment efficiency of thermal power enterprises than do wind power and photovoltaic projects. Therefore, both governmental departments and thermal power enterprises need to take active measures in order to achieve green transformation from the perspective of green investment efficiency. Through the segmentation of important projects of green investment, this paper provides a reasonable investment direction reference for the sustainable transformation of China’s thermal power industry. It also provides a rich and novel theoretical basis for the Chinese government to further improve the relevant environmental protection laws and regulations of thermal power industry.

The Impact of Carbon Emissions Trading on the Total Factor Productivity of China’s Electric Power Enterprises—An Empirical Analysis Based on the Differences-in-Differences Model

Based on the panel data of China’s listed electric power enterprises, this paper adopts the differences-in-differences model to empirically analyze the pilot policy of carbon emissions trading’s impact on the total factor productivity of power enterprises in 2013. The study finds that the carbon trading pilot policy has a significant positive effect on the total factor productivity of power companies, and the two possible impact mechanisms are external cost compensation and additional income, and internal low-carbon technology innovation and resource allocation optimization. The conclusions above have been further confirmed by the parallel trend test and robustness test. The heterogeneity analysis demonstrates that there are differences in the regression results between state-owned enterprises and nonstate-owned enterprises. The possible reason is that state-owned enterprises are more likely to be affected by the carbon emissions trading system, and their asset-heavy model puts greater pressure on carbon emission reduction. Therefore, their demand for low-carbon technology innovation is more urgent; areas with stricter carbon emission verification are more sensitive to the implementation of carbon trading, and a reasonable increase in carbon verification can make the carbon trading market more effective. Based on the research results, this paper proposes to speed up the improvement of the national carbon trading market system, enhance the diversity and richness of the main market, improve the liquidity of the carbon trading market, broaden financing channels for electric power enterprises, and improve the carbon market supervision mechanism.

Medical service reform and government regulation in electric power enterprises from the perspective of health economics

Drawing from the field of health economics, this study investigates the government's role in reforming health care delivery within the electric utilities sector. It identifies key systemic and institutional shortcomings in these utilities that have led to escalating health care costs. Utilizing statistical analysis and model simulations, the research further explores the impact of policy interventions on the pricing of healthcare delivery technologies and the expenses of public hospitals. Ultimately, this paper leverages insights from both institutional and regulatory economics to recommend an enhanced governmental regulatory framework designed to foster sustainable, socially productive growth and enhance the quality of life.

Research on digital transformation and application of key business of power grid planning

As the basis for the construction and development of the power grid industry, power grid planning not only affects the development direction of power grid enterprises, but also determines the economic level, social stability and quality of life of urban residents. In the construction and development of the new era, the digital transformation of power grid planning business is an important part of the construction and improvement of the digital power grid system, which will guide the power grid planning business to develop stably in the direction of intelligence, automation and information, actively create a safe and reliable smart grid, and lay a solid foundation for improving the development level of power grid enterprises. Therefore, after understanding the current digital transformation goals and development status of power grid planning business, this paper mainly explores the specific plan for the transformation of power grid planning business of a regional power enterprise according to the structure and transformation requirements of the new power system, and finally explores the practical significance of digital transformation according to the construction effect and development goals, providing a reference for the reform and development of the power industry.

Standardization as Way of Raising Efficiency of Power Enterprises in Conditions of Digital Transformation

Automation and digitalization in all types of activity is a growing trend of economy development today. It causes evolution of technological processes, where man still takes part. A necessary condition of the efficient functioning of enterprises is standardization, which provides a way of storing, transfer and accumulation of knowledge and continuous improvement of processes. Work in program complexes maintaining technology requires a new method of standard visualization. The article reviews methods of standardization at power enterprises and provides recommendations aimed at their introduction and use in managing the production system in conditions of digitalization. The authors studied problems of effective visualization, put forward a new type of standards in the form of video, identified benefits and drawbacks of video-standards. Apart from that, a model of digital architecture for storing and safe-keeping documents at enterprises was presented and the effect of using standards at power enterprises was demonstrated.

Production decision analysis of China's fossil fuel power enterprises in dual market conditions

At present, China and some other countries and regions are adopting both electricity and carbon trading markets to optimize the resource allocation of the power industry. The aim of this research is to explain the production behaviors of fossil fuel power enterprises in these complex dual market conditions and then evaluate the market effects. On the basis of the real market rules of China and the production characteristics of these enterprises, we describe the production decision process of enterprises with different market positions (leader, follower, and taker), obtain their optimal yield, and then offer market equilibrium results (total electricity supply, clearing price, total CO2 emissions, and carbon intensity level). Besides, we evaluate the impacts of government interventions (market condition changes) on regional market equilibrium situations by numerical simulation. Our results indicate that the direction (positive or negative) of the above impacts is determined by the level of the allocation coefficients of the carbon emission quota, and the degree of these impacts is determined by the level of fine for unit excess carbon emissions. Moreover, our research also proves that enterprise collusion behaviors aggravate market failure but lower the carbon intensity level.

Processing method for multi-source data fabric system based on intelligent system architecture

Currently, the data management of power enterprises faces the need to analyze data sources from multiple places. However, traditional multi-source data fabric systems have problems such as low analysis efficiency and high error rates, which brings great inconvenience to the data analysis of power enterprises. In order to improve the accuracy and efficiency of data analysis in data structure systems, the intelligent system architecture is applied to the construction of source data structure systems. The main modules are data collection, data matching, data integration, and data analysis. This article uses simulated annealing genetic algorithm to perform high-performance calculations on system timing data, thus achieving data matching. This article conducted data level data integration, feature level data integration, and decision level data integration. The access survey method was used to analyze the current data management problems faced by power companies. The evaluation and analysis of general multi-source data fabric systems and multi-source data fabric systems based on intelligent system architecture were conducted using the evaluation panel evaluation method. The analysis results showed that the operational convenience of the multi-source data fabric system based on intelligent system architecture could reach 60%–80%, which greatly improved compared to general multi-source data fabric systems; the information sharing of multi-source data fabric systems based on intelligent system architecture was greatly improved; the data processing efficiency of general multi-source data fabric systems was much lower than that of multi-source data fabric systems based on intelligent system architecture; however, the symmetry of data collection and matching in the multi-source data fabric system based on intelligent system architecture was slightly insufficient, and further improvement was still needed. In order to benefit more power companies through the intelligent system architecture based multi-source data fabric system, it was necessary to strengthen the management of data collection and matching symmetry.

Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms

With the continuous occurrence of power crisis events worldwide, meeting society's demand for electricity has kept coal-fired power generation high, which leads to a large amount of carbon dioxide emissions and environmental pollution problems. Therefore, improving the environmental performance of thermal power plants under the background of a power crisis has become particularly important. This research provides a new path for production optimization and environmental performance improvement of electric power enterprises from the perspective of combining prediction algorithms and DEA methods. We apply the modified non-radial directional distance function (MNDDF) method to a set of panel data containing 16 different cogeneration units and 27 different periods in eastern China and construct the grey prediction model to predict the future environmental performance of these units. Empirical analysis shows that our model has high prediction accuracy and offers a reasonable basis for future production decision-making adjustments for electric power enterprises. Based on the results herein, we present valuable suggestions for thermal power plants to improve their environmental performance during a power market crisis, including optimizing resource utilization, improving management level and operating conditions, strengthening technological innovation, and enhancing production factor allocation.

Research on the Root Cause Analysis and Governance Measures of Frequent Power Outages in Electric Power Enterprises

Abstract Accompanied by the rapid development of the economy and the great strides of reform, the whole society puts forward higher and higher requirements for the safety and stability of the power grid, and the frequent power outage events will bring great losses to the power enterprises. In this paper, we employ the linear encoding function in the MAGNN method to linearly process the risk factors associated with frequent power outages in electric power enterprises. We then assign weights to these linearly processed risk factor vectors using a graph attention mechanism. Finally, we apply the correction matrix of outage risk factors to identify the risk of power outages in electric power enterprises and design an intelligent power outage control system. The study discovered that 10 kV system failure is the primary cause of frequent outages in Power Enterprise-A. The number of failures occurred 129 times due to 10kV feeder system failures in rural distribution networks. The study also reveals that the implementation of an intelligent outage control system resulted in a 73.60% year-over-year decrease in the reliability loss of fault outages in power enterprise A, thereby effectively addressing the issue of frequent outages and reducing the economic losses incurred by power enterprises. This paper provides an effective method for resolving frequent power outages in electric power enterprises and provides a guiding direction for improving power supply reliability in electric power enterprises.

Evaluation of Emission Reduction Performance of Power Enterprises Based on Least Squares Support Vector Machine

In response to the increasingly severe environmental pollution problem at present, many traditional power companies are facing the promotion of environmental protection work. The promotion of Energy Conservation and Emission Reduction (ECER) work needs sufficient theory and data support. Therefore, this study proposes a performance evaluation model for ECER in power enterprises based on the improved lion swarm algorithm optimized Least Squares Support Vector Machine (LSSVM). The evaluation index system has been reconstructed according to the current environment and era characteristics. The LSSVM has been used to evaluate the ECER work of power enterprises, and the training efficiency of Lion Swarm Optimization (LSO) algorithm has been solved using chaos theory. An improved LSO algorithm is utilized to improve the parameter selection problem of the LSSVM model, to achieve a scientific and objective evaluation of the ECER performance of power enterprises. The research findings denote that the algorithm put forward in this study has better training efficiency, higher accuracy and stability, as well as better response time. It also exhibits minimal errors in simulation experiments. In summary, the ECER performance evaluation model proposed by this research institute can effectively output correct scoring results, providing data support for the promotion of environmental protection work.

Utilization of technogenic waste from energy enterprises

The paper shows that the use of nano-additives can reduce the content of harmful impurities in flue gases. It is demonstrated that the waste of the water treatment process of thermal power plants can be used as a cheap and environmentally friendly nanostructured additive to improve the properties of hydrocarbon fuel. If necessary, the effect of carbonate sludge can be enhanced by adding other nanoparticles. The composition and properties of carbonate sludge are presented. The prospectivity of extraction of valuable, rare-earth metals from technogenic wastes generated during combustion of fuel oil at power enterprises is proved.The results of the obtained experimental powder diffractogram of fuel oil ash are discussed.

Research on power communication data security based on ETL

The use of modern data application technology in information security management programs within power enterprises is a major trend in industry development. Integrate scattered, messy, and non-standard data in electronic communication, extract, clean, and transform business system data, and load it into a data warehouse. ETL mainly relies on cloud computing logic to protect the transfer, storage, confidentiality, and other aspects of data, effectively avoiding the loss, omission, and leakage of information in enterprise data transmission. This study discusses the necessity of ETL based data transmission security protection technology for power enterprises to achieve security, in order to provide theoretical support for subsequent research and practice.

A refined decision-making method for orderly power consumption in virtual power plants considering load characteristics

Abstract In recent years, electricity consumption has been increasing, while the supply of electricity is relatively lagging, and power shortages often occur. Therefore, the management of organized power consumption is an urgent task for the current power industry. Based on the characteristics of power load, this paper constructs a decision-making management framework for orderly power consumption by considering four aspects: generation, grid side, demand side, and social benefit. Through the various types of flexible load resources aggregated within the virtual power plant, it participates in regulating its power, effectively reduces the peak-valley difference, and realizes refined, orderly power consumption management. Finally, based on the multi-objective optimization model, refined decision-making for orderly power consumption with the participation of virtual power plants is constructed and compared to traditional decision-making for orderly power consumption. The results show that compared with conventional decision-making, the peak-to-valley difference is reduced by 8.7789 WM, the economic benefit of the power enterprise is improved by 228,300 yuan, and customer satisfaction is enhanced by 0.1613, which verifies the effectiveness of the decision-making method of the sequential power consumption in this paper.

Research on the application of large language model in electric power enterprise audit

Research on the application of large language model in electric power enterprise audit

On the state of the environment and natural environment of the East Kazakhstan region

The article analyzes the state of the environment in the East Kazakhstan region. The authors, having analyzed official sources, showed that as a result of the restoration of production volumes at non-ferrous metallurgy and thermal power enterprises, there is an increase in emissions of hazardous waste by individual enterprises in this industry into the environment. In the atmospheric air of large industrial cities and towns in the region, maximum permissible concentrations of lead, sulfur dioxide, nitrogen oxides, phenol, formaldehyde and other components are observed to be exceeded. The authors emphasize that mining enterprises have a negative impact on the state of water resources and the unsatisfactory technical condition of sewer networks and treatment facilities, which leads to bacterial contamination of water sources, including sources of drinking water supply. The authors also discuss the state of forest resources and wildlife in the region. The conclusion that was done by the authors – there is a real threat of environmental pollution from waste from non-ferrous metallurgy and mining enterprises in the region and at the present moment.

Optimal scheduling of deep peaking compensation for electric utilities considering multiple types of adjustable resources

Abstract This paper first analyzes the peak compensation process of electric power units in electric power enterprises, studies the carbon emission model of unit operation and the cost calculation method, then constructs an optimized dispatch model of deep peak compensation in electric power enterprises based on the factors of peaking subject and object and multiple types of adjustable resources, determines the critical peaking rate, and calculates the coefficient of the unit’s peaking capacity and the coefficient of the system’s peaking demand. Finally, based on the model, single-day and multi-day data from the regional power grid were analyzed, and the energy losses of the system units in summer and spring were compared before and after optimization. The results show that the average load factor of coal power units after the optimal dispatch of regional grid peak compensation is increased from 62%-68% before optimization to more than 91%, and the overall energy consumption of the system is reduced by 30.95% in the summer and 39.93% in the spring, which is of theoretical and practical significance for alleviating the scheduling pressure on the grid and the control problems of the power units.