Power Grid Company Research Articles

Impact of new energy supporting delivery repurchase on transmission and distribution price and investment and operation of power grid companies under the new situation

The new round of power system reform is profoundly affecting the functional positioning and profit model of power grid companies, and puts forward higher requirements for the investment decision-making management of power grid companies. Based on the cost accounting and pricing mechanism of power transmission and distribution prices for grid enterprises, and the linkage mechanism of grid investment-transmission and distribution prices based on system dynamics, this paper briefly analyzes and summarizes the impact of new energy repurchase work on power transmission and distribution prices and investment.

Time structure of the distortion source identification of the electric power quality indicators and hardware and software system for its reduction

THE PURPOSE. Investigation of the time structure forthedistortion source identification of the electric power quality and a method for its reduction using of a mobile software and hardware instrumentation system.METHODS. The analysis of the number of complaints regarding low-quality electric power, the structure and values of the time spent on the identification of the distortion sources of the electric power quality indicators (PQI) for the standard values, taking into account all its components, was carried out.RESULTS. It is determined that the number of complaints received by the power grid company regarding lowquality electric powerremains high. At the same time, it takes a long time to identify the distortionsource before putting in place the necessary remedial measures. According to the analyzed data, it can take up to 21 days. The number of cases when the distortion source of the PQI couldn’t be detected within two days was 117 cases of 419 analyzed. The solutions to reduce this time are proposed.CONCLUSIONS. The solutions presented in the article make it possible to reduce the time spent on the source distortion identificationofthe PQI due to the use of a mobile hardware and software instrumentation system (HSIS). A variant of the HSIS structure is proposed, which includes sensors and the HSIS central unit. The proposed HSIS can be used in the absence of external communication channels through the use of data transmitted from the sensors of the system to the central unit using Long Range (LORA) or Wireless Fidelity (Wi-Fi) technologies. In addition, the HSIS provides time synchronization of all the sensors.

Distributed dispatching method of active distribution network considering multiple regulation resources

In view of the low capacity of distribution network to accept renewable energy such as wind power and photovoltaic, which leads to the failure of active distribution network to achieve the expected economic benefits, a distributed scheduling method of active distribution network considering multiple regulation resources is proposed in this paper. In the case of multiple coupled energy access, the resource collaborative scheduling principle is designed, the business process of adjustable resources participating in the emergency coordination control of auxiliary distribution network is proposed, and the supply side resources and demand side resources are planned. The installation location and initial capacity of distributed generation are determined by network sensitivity factor method. After optimizing the capacity, the location and scale of distributed generation are obtained. Considering the load response and distribution of distributed generation, the distributed dispatching model of active distribution network is established with the goal of minimizing output cost and dispatching cost. The net annual value method is used to calculate the operation benefit increment of distribution network, so as to evaluate the effect of control. Taking the pilot project in Zhejiang as an example, the maximum operating benefit increment of this method is 367600 yuan, which is 32800 yuan and 45300 yuan higher than the scheduling method based on power load temporal and spatial correlation and risk distribution respectively, which can improve the operating benefit for the power grid company.

Recovery Algorithm of Power Metering Data Based on Collaborative Fitting

Electric energy metering plays a crucial role in ensuring fair and equitable transactions between grid companies and power users. With the implementation of the State Grid Corporation’s energy Internet strategy, higher requirements have been put forward for power grid companies to reduce costs and increase efficiency and user service capabilities. Meanwhile, the accuracy and real-time requirements for electric energy measurements have also increased. Electricity information collection systems are mainly used to collect the user-side energy metering data for the power users. Attributed to communication errors, communication delays, equipment failures and other reasons, some of the collected data is missed or confused, which seriously affects the refined management and service quality of power grid companies. How to deal with such data has been one of the important issues in the fields of machine learning and data mining. This paper proposes a collaborative fitting algorithm to solve the problem of missing collected data based on latent semantics. Firstly, a tree structure of user history data is established, and then the user groups adjacent to the user with missing data are obtained from this. Finally, the missing data are recovered using the alternating least-squares matrix factorization algorithm. Through numerical verification, this method has high reliability and accuracy in recoverying the missing data.

Potential application of Six Sigma method in operation and maintenance management of UHVDC converter station

Abstract The ultra high voltage direct current (UHVDC) technology plays an important role in the long-distance and large-capability transmission of renewable energy. Power grid company has to improve the reliability and efficiency of UHVDC transmission systems to support renewable energy utilization. In this paper, Six Sigma method is considered for improving the operation and maintenance (O&M) performance of UHVDC converter stations. The working tasks for the operation team and the maintenance team are introduced at first, respectively. The limitation of current O&M management is analyzed. A five-stage implementation of Six Sigma method is discussed in detail. The formed negative feedback ensures the sustainability of implementation and realizes closed-loop management. A representative equipment disposal case is used to demonstrate the adaptability and operability of the potential application of Six Sigma method.

Dilemmas of R&D investment risks and sustainability in the clean-tech economy: Evidence from Nasdaq clean edge index components

ABSTRACT Clean energy companies often require more costly investment in technology innovation than traditional energy companies, which poses higher technological risks. Therefore, many inconclusive debates have arisen concerning whether the R&D investment can generate sustained returns for such companies. This paper adopts progressive modeling steps to address the problem by using a modified Cobb-Douglas production function, System Generalized Method of Moments (SYS-GMM) approach, and fixed-effect panel threshold model. The role of R&D investment; the non-linear relationship between revenue, innovation, efficiency, and risk; as well as the corresponding threshold effects in clean and traditional energy companies are analyzed. 840 firm-year observations of clean energy companies from the NASDAQ Clean Edge Index are collected and screened, and compared with 280 firm-year observations of listed traditional energy companies in the U.S. Moreover, four types of clean energy companies, comprising green energy, wind power, water, and smart grid companies, are calculated and summarized separately. The results show that, for clean energy companies, long-term R&D intensity is beneficial to returns, shortening the cash conversion cycle (CCC) value, and reducing the financial leverage can produce a positive effect on return on assets (ROA), while different types of clean energy companies are advised with tailor-made portfolio strategies. For traditional energy companies, controlling the financial leverage while properly increasing CCC can help improve their ROAs. In this context, policy recommendations are provided for stakeholders to optimize their investment strategies in various clean and traditional energy enterprises according to the time-lag effect and threshold effect.

Method for assessing the state and residual life of the insulation based on analysis of the time of discharge of the capacity of electric cables

As of today, the problem of the lack of non-destructive methods for assessing the state and determining the residual life of the insulation of electrical cables is relevant for cable lines in operation, and especially for lines that have exhausted their service life. The research presented in the framework of this article is aimed at creating a non-destructive technique for assessing the state and residual life of electrical cables insulation. The study was carried out using computer simulation methods and using the basic theoretical laws of physics and electrical engineering. A method for assessing the condition and residual life of electrical cable insulation has been developed, which is based on the analysis of the discharge time of the cable capacity. The applicability of the method is determined, instructions are given on its applicability and the analysis of the output data. The obtained results can be used by power grid companies and industrial enterprises to analyze the state of the insulation of electrical cables.

Research on Comprehensive Evaluation Method of Competitiveness of Energy-saving Low-carbon Value-added Service

Traditional electricity sales services present a development trend of diversification and integration, and will gradually evolve into comprehensive energy services in the future. Energy-saving, low-carbon value-added services are an important part of it, which is important for grid companies to cultivate core competitiveness in the electricity sales market. effect. In this regard, this article conducts a comprehensive evaluation of the competitiveness of energy-saving low-carbon value-added services based on the perspective of power grid companies. First, this article constructs an energy-saving low-carbon value-added service competitiveness evaluation system from the aspects of energy-saving, intelligent, personalized, and comprehensive levels; secondly, constructs a comprehensive evaluation model for the competitiveness of energy-saving and low-carbon value-added services, using AHP weighting method Empower the supervisor, and then conduct a comprehensive evaluation based on the fuzzy comprehensive evaluation; finally, select the Y city power company to conduct an empirical analysis of the comprehensive evaluation model, and provide a favorable reference for other companies to carry out energy-saving low-carbon value-added services in the future.

Hierarchical Distribution Network Topology Formulation and Dimensionality Reduction Using Homeomorphism Transformation

The scales of the power distribution networks in real-world power grids expand quickly while the network structures are becoming more and more complex. The power grid companies analyze the power distribution networks in different business scenarios with different topology models. In this work, we propose a hierarchical graph model to describe the medium-voltage distribution network (which is a typical power distribution network in power grids) based on homeomorphic transformation. The hierarchical graph model preserves the basic network topology described by the traditional Common Information Model (CIM). Firstly, the nodes in the distribution network topology are classified according to graph theory. Secondly, three typical business scenarios of distribution network topology analysis are summarized, and the original model is simplified by progressive dimensionality reduction method to meet the analysis requirements of different scenarios, the simplified method consists of three abstract levels: critical path, core path and minimal path, and can effectively reduce the space complexity of the model while maintaining the topological properties. Thirdly, a multi-level distribution network topology construction and mapping method based on the graph database is proposed. It is used to realize the rapid conversion and traceability between different levels of topology. Finally, a practical distribution network in a county is used as an example to verify the effectiveness of the proposed method in the aspects such as topology rendering and path searching. The evaluation indicates that the proposed model can visualize the distribution network intuitively. The model can also speed up the visualization and path searching significantly.

Multitarget Detection of Transmission Lines Based on DANet and YOLOv4

In order to accurately identify targets such as insulators, shock hammers, bird nests, and spacers on high-voltage transmission lines, this paper proposes a multitarget detection model for transmission lines based on DANet and YOLOv4. First, the DANet and YOLOv4 are fused to solve the difficulty in understanding the scene and the discrimination of pixels caused by the complex and diverse scenes of UAV’ (unmanned aerial vehicle) aerial images (lighting, viewing angle, scale, occlusion, and so on) so as to improve the significance of the detection target. Gaussian function and KL (Kullback–Leibler) divergence are used to improve the nonmaximum suppression in YOLOv4 so as to improve the recognition rate of occluded targets; the focal loss function and the balanced cross entropy function are used to improve the loss function of YOLOv4 in order to reduce the impact of not only the imbalance between the background and the detection target but also the imbalance among the samples, which is aimed at improving the accuracy of the detection. Then, a data set is made for the experiment by using the UAV inspection image provided by a power grid company in Eastern Inner Mongolia. Finally, the algorithm proposed in this paper is compared with other target detection algorithms. Experimental results show that the average detection accuracy of the proposed algorithm can reach 94.7%, and the detection time of each image is 0.05 seconds. The method has good accuracy, real-time, and robustness.

Simulation application of three-dimensional GIS based on full-scenario intelligence in power grid company transmission line planning

Traditional data collection and review methods in power grid planning have always had the problems of time-consuming, poor real-time performance, and cumbersome processes. The application of mobile GIS solves the problems of data collection and review methods and makes more efficient use of mobile GIS terminal collection. The data of the mobile GIS solve the urgent problems that need to be solved since the popularization and application of mobile GIS. This system implements functions such as storage, transmission, and review based on mobile GIS data, which will greatly improve the efficiency of data collection by mobile terminals and reduce the cost of data collection. Realize the planning simulation of the power grid under the intelligent cycle of the whole scene.

Development of a device for control of electric energy parameters in the distribution network

Background: As of today, the actual problem in the power sector is to create a device for the collection and transmission of information in networks of different voltage levels.
 Aim: The research presented in the framework of this article is aimed at creating a universal device intended for use in electrical networks of low and medium voltage in order to collect and transmit information about the parameters of electrical energy at the place of installation of the device.
 Methods: The study was performed with the use of computer modeling techniques developed electronic devices.
 Results: A functional diagram of the developed device is given, options for its connection to the network for various conditions and requirements are indicated, and recommendations for use are given.
 Conclusion: The obtained results can be used by power grid companies and industrial enterprises to analyze the condition and efficiency of power grids.

Study on Strategic Equilibria of Tobacco Industry Power Energy Markets in Post-epidemic Era

This paper aims to solve the strategic balance issues in tobacco industry energy markets in the post-epidemic era, based on the game theory, a strategic equilibrium model for power networks is proposed after evaluating users, power grid company in tobacco industry, and new power entities. By analyzing the claims and interests of relevant transaction subjects, an optimization computation model for tobacco industry power energy markets is constructed, meanwhile the flowchart of finding the Nash optimized solutions is also presented on basis of the genetic algorithm (GA), and the physical meaning of the Nash solutions are explained. The research results can provide some fundamental support and practical suggestions for the related aspects of the power energy markets, along with the economists who study the market design and prediction.

Customer engagement in innovative smart grid deployment projects: evidence from Russia.

In recent years, Russian power grid companies have significantly intensified their planning and implementing innovative projects to introduce various elements of smart grid technology. The global experience shows that the best potential outcome from smart grid technologies largely relies on the customers' readiness and adoption. To this end, we assess the Russian consumers' awareness and readiness regarding smart grid technologies by conducting a comprehensive survey. Our empirical study showed that, in general, Russian consumers are unaware of the various aspects of smart grid technologies. On the contrary, a significant share of respondents believes that smart grid technologies can reduce their energy consumption burden through gaining efficiency. The low level of awareness would be detrimental to accrue smart grid innovative projects' potential socio-economic and environmental benefits. We propose several recommendations for policymakers and managers of grid companies for the elimination of the identified risks.

Research on the Benefit-Sharing Model of Collaborative Innovation Mechanism in Power Innovation Park

Currently, innovation is no longer limited to a single enterprise. The joint realization of collaborative innovation by multiple parties has become the main driving force for innovation and development. The Power Innovation Park is an emerging innovation and entrepreneurship model. It is guided by power grid companies, and the school, government, and enterprise are combined in the park. The Power Innovation Park urgently needs theoretical guidance in terms of the resource allocation mechanism, support incentive mode, and benefit-sharing mode, so this paper takes the park as an example to study the benefit-sharing mode of collaborative innovation. In this paper, the transformation methods of the Power Innovation Park are divided into two types: cooperation between members within the park and dominated by external enterprises in the park. This paper applies cooperative game theory and HJB equation to study the benefit-sharing model of each member in the Power Innovation Park under two different result transformation modes. Research has shown that an appropriate method of transformation of results can maximize the overall and individual interests of the park and that individual interests are affected by many factors. Finally, this paper puts forward policy recommendations to promote the collaborative innovation development of the innovation park through the research results.

Research on Transformer Life Forecast Based on Random Forest Algorithm

Accurately assessing the life and operating status of transformers has important guiding significance for the formulation of maintenance strategies for power grid companies, and at the same time plays a key role in the risk management of power grid companies. However, the traditional methods for predicting the remaining life of the equipment have the problems of insufficient accuracy or long data training time. In order to achieve a more accurate assessment of the life and status of the transformer, a random forest-based transformer life prediction method is constructed in this paper. Relying on the theory of big data analysis, by mining and analyzing the accumulated data of massive transformers, the life prediction model of the transformer is established and the characteristic parameters affecting the life of the transformer are extracted to predict the life of the transformer. The experimental data research demonstrates that the model can be accurate and effective Predicting the life of transformers has higher prediction accuracy than traditional methods, providing method references for asset management and risk management of power grid companies.

Research on pricing model of uninterrupted maintenance for distribution network project of power grid enterprise

Uninterrupted operation of distribution network engineering is an important means to ensure the safe and reliable operation of power supply equipment and improve the level of power supply reliability and quality service. In recent years, with the vigorous promotion of the power grid company, the uninterrupted operation of distribution network has a more rapid and standardized development. At present, the pricing basis of distribution network engineering has not included the content of uninterrupted power operation, which leads to the problems of unable to find the corresponding quota and unclear charging standard in the actual construction charging process. Therefore, it is urgent to study the pricing method of uninterrupted power operation, guide the uninterrupted power operation, standardize the charging, and promote the healthy development of power construction.

A Prediction Method Based on Extreme Gradient Boosting Tree Model and its Application

Improving the accuracy of financing risk prediction is of great significance to the healthy development of grid enterprises. Taking a provincial-level power grid company as the research object, the financing risk index system is constructed by considering multiple dimensions, and the monthly financing risk index RI of power grid enterprises from 2015-2018 is determined based on entropy weight and comprehensive index method, while the financing risk prediction model is constructed with the help of extreme gradient boosting tree model. The empirical results show that compared with support vector regression and BP neural network models, the financing risk prediction model constructed based on the extreme gradient boosting model has an excellent performance in terms of prediction accuracy and stability.

Research on Application Scheme of Power Internet of Things in Power Grid

Introduction Power Internet of things is an important means for power grid companies to make digital transformation and improve the level of power grid intelligence. Method This paper introduced the general situation and architecture of power Internet of things， focused on the functional requirements and development goals of each level， and put forward the technical direction of developing power Internet of things according to the differences among comprehensive power companies， distribution network companies and power sales companies. Results Application solutions were put forward in the fields of transmission network， distribution network， marketing and power consumption， and enterprise management. Conclusion The scheme has been well applied in various power grid companies.

Increasing Renewable Energy Consumption Coordination With the Monthly Interprovincial Transaction Market

The limited regulation capacity of the power grid, coupled with the imperfect market mechanism, has squeezed the space for renewable energy consumption in China. This article proposes a renewable energy consumption mechanism through the monthly interprovincial transaction market, to balance the revenue of each market participant and improve the consumption of renewable energy. A new player named “interprovincial traders” is introduced to serve as the middleman for the renewable generation, users, and the power grid company. The main function of “interprovincial traders” is to coordinate and match the user load with the output of renewable energy. In such a market mechanism, the social factors, influenced by the revenue of each trading cycle, are considered in the user responding model from the perspective of consumer psychology. Finally, a two-phase optimization model is proposed to promote renewable energy consumption coordination with the monthly interprovincial market. The optimization model is simulated in a provincial power grid example. The results show that the model can effectively increase the consumption of renewable energy as well as improve the profit of power grid companies and users.