Grid Enterprises Research Articles

Power Grid Enterprise Cost Rationality Evaluation Based on Meta-frontier and Super-efficient DEA

Evaluation of transmission and distribution cost rationality of power grid enterprises enables governments to scientifically approve power transmission and distribution prices. To depict the impact of environmental differences of power grid enterprises on the evaluation of operational efficiency, we measured and calculated meta-frontier efficiency and group-frontier efficiency of 25 provincial-level grid enterprises in China, from 2016 to 2019, by building a meta-frontier-based super-efficiency DEA model, and ranked them based on meta-frontier efficiency, in this paper. The measurement results show that there are pronounced differences in the operational efficiency levels of power grid enterprises, which are not only related to objective differences in economic development level, geographical environment, and historical burden, but also related to technology and management levels of individual enterprises. The cost rationality evaluation method proposed in this paper lays a foundation for introducing "cost benchmarking" in future power transmission and distribution pricing, providing reference for perfecting the transmission and distribution prices regulatory mechanism.

“碳达峰、碳中和”目标背景下电网企业绿色采购策略研究

“碳达峰、碳中和”目标背景下电网企业绿色采购策略研究

Digital information storage method of power grid enterprises based on random forest

Digital information storage method of power grid enterprises based on random forest

Grid investment capability prediction based on path analysis and BP neural network

With the more complex investment environment of China’s power grid, the accurate prediction of the investment ability of power grid enterprises has become an important prerequisite for managers to make precise investment decisions. This paper first selects the factors affecting the investment capacity of the power grid from the internal and external environment, and establishes the index system of the factors affecting the investment capacity. Secondly, the path analysis is used to deeply explore the interaction relationship and influence degree of each index and investment capacity. Finally, the maximum investment capacity of the power network can be predicted based on the BP neural network prediction model. The results show that the BP neural network prediction model can achieve higher prediction accuracy when predicting the power grid investment capability.

Power Grid Resource Integration of Enterprise Middle Station based on Analytic Hierarchy Process

With the transformation from smart grid to power Internet of Things, new power businesses such as power grid automation and power quality monitoring are constantly emerging. The load environment of power grid is changeable. In order to meet the needs of multi-service, the integrated access scheme for power grid resources in power enterprises is gradually diversified, which brings challenges to the unified management and control of power grid communication network. In this paper, SDN technology is used to improve the operation and maintenance management and control of power communication network, which aims at the integration scheme of power grid resources in power enterprises. Based on the controller cluster technology, combined with the new power business requirements, this paper designs a software-defined network centralized control architecture of the new business of power communication network. The architecture realizes the operation and maintenance management of network resources under the centralized control architecture of typical enterprise scenarios, such as power grid enterprises. The convergence speed is improved by 27%. The minimum value of iterative convergence is 31% better than that of other methods. The system requirement is reduced by 13.5%, which is helpful to improve the efficiency of node dynamic allocation and ensure the need of large-capacity data transmission of smart grid. The research in this paper can realize the two-way interaction, real-time expansion and unified deployment of power business in the future, and promote the intensive and lean development of power communication network.

A Hybrid Deep Learning Framework for Network Flow Forecasting of Power Grid Enterprise

With the expansion of the digital business line, the network flow behind the digital power grid is also exploding. To prevent network congestion, this article proposes a novel network flow forecasting model, which is composed of variational mode decomposition (VMD), GRU‐xgboost block, and a forecasting adjustment block, to grasp the changing patterns and trends of network flow in advance, and to formulate reasonable and effective flow management strategies and meet the requirements of users for network service quality. The network flow series in power grid enterprise always contain complex patterns and outliers, and VMD is applied to adaptively process complex net flow time series into several subseries with simpler patterns. A GRU‐xgboost block is designed to reconstruct the features of historical series. Then, xgboost model is applied to generate predictions for all decomposed subsignals. For the final predictions, we design a forecasting adjustment block to further remove the influence of random noise. Finally, the empirical results show the superior performance of the proposed model on network flow forecasting task.

Sustainable Investment Forecasting of Power Grids Based on the Deep Restricted Boltzmann Machine Optimized by the Lion Algorithm

This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model was used to predict the investment of a power grid enterprise, and the final prediction result was obtained by modifying the initial result with the modifying factors. The LA-DRBM model compensates for the deficiency of the single model, and greatly improves the investment prediction accuracy of the power grid. In this study, a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model, and a comparison with the RBM, support vector machine (SVM), back propagation neural network (BPNN), and regression model was conducted to verify the superiority of the model. The conclusion indicates that the proposed model has a strong generalization ability and good robustness, is able to abstract the combination of low-level features into high-level features, and can improve the efficiency of the model's calculations for investment prediction of power grid enterprises.

Digital information storage method of power grid enterprises based on random forest

Digital information storage method of power grid enterprises based on random forest

Analysis on the Importance of Electric Energy Substitution in Power Grid Enterprises

Analysis on the Importance of Electric Energy Substitution in Power Grid Enterprises

Non-intrusive identification and privacy-preserving of residential electric vehicle

Masses of user-side smart meter data provide a foundation for utilities to acquire users’ electricity consumption patterns and promote refined energy management. Therefore, the charging load of electric vehicles can be identified non-intrusively through the smart meter data of residential users, which provides flexible resources for the demand side response of power grid enterprises and is beneficial to the power dispatching decision making. Meanwhile, revealing residential energy consumption behavior from smart meter data is treated as energy privacy leakage. Extensive data collection from smart meters has raised privacy risk, which could lead to the reduction of trust in utilities from households. Aiming at this problem, the paper proposes a non-intrusive method to extract residential electric vehicles, and on this basis, discusses the privacy protection. In this paper, DWT method is used to decompose the total power of smart meter to extract the charging load of electric vehicle, and similar charging load patterns are added to smart meter data to preserve the residential EV charging behavior privacy. Practical households with EVs are used to test the proposed method and the result shows its feasibility for the performance of privacy-preserving.

Retraction Note: Groundwater pollution detection and power grid enterprise human resource management based on Markov chain

Retraction Note: Groundwater pollution detection and power grid enterprise human resource management based on Markov chain

Exploration and Practice of Digital Transformation of Power Grid Enterprises

Exploration and Practice of Digital Transformation of Power Grid Enterprises

Function orientation and typical application scenarios of the Internet of Things construction for power transmission and transformation equipment

In recent years, power grid enterprises have continuously promoted the construction of intelligent operation inspection system. Pilot applications of various equipment status sensors, online monitoring devices, intelligent wearable devices, mobile terminals and Beidou navigation satellite system have been gradually carried out. The configuration range of intelligent equipment such as UAV and robot has been continuously expanded, and big data analysis technology, artificial intelligence diagnosis technology have also been preliminarily applied. With the continuous development and breakthrough of key technologies such as edge computing and wireless transmission, it provides favorable conditions for the intelligent, diversified and ecological development of the construction and application of the IOT for power transmission and transformation equipment. This paper mainly introduces the overall architecture and functional positioning of the construction of power transmission and transformation IOT, and combined with the business needs of some typical application scenarios in the operation of power grid equipment, to promote the integrated application of IOT technology and power grid equipment operation and inspection business, and also establish an open, shared and symbiotic IOT ecosystem of power transmission and transformation equipment, so as to lay the foundation for intelligent equipment management.

AC/DC system construction and analysis of business model under multi-station fusion model

This paper focuses on a novel model named multi-station fusion (MSF). The proposed model integrates transformer substation, data center, energy storage system (ESS), photovoltaic (PV), electric vehicle charging station (EVCS), connection information base station and other systems. It aims at improving the utilization rate of the spare space in existing substation, reducing operation and maintenance cost, and increasing the revenue of power grid enterprises. This paper designs three types of AC/DC system based on reliability priority, economy priority and retrofit flexibility priority. Markov process Monte Carlo method is introduced to verify data center reliability in MSF. The business model of MSF is analyzed. Finally, the construction scheme of MSF model, the contents of the planning considerations and cost–benefit study demonstrate the economic efficiency of the proposed model.

Application of Digital Engineering Audit in Power Grid Enterprises

Application of Digital Engineering Audit in Power Grid Enterprises

Automated Analysis of Service Life of Air-Lines of the Electricity Transmission of Electric Power Systems

Basic EPS objects, which service life has exceeded normative value, increasingly affect – every year to a greater extent – the efficiency of overall performance. This manifests itself in increase of a number of automatic emergency shutdowns, an amount and complexities of accident-hazardous defects. After the expiration of the standard service life, there is a special need for a quantitative assessment of reliability and safety of an object. It is recommended to organize the operation, maintenance and repair of these objects according to their technical condition, and since it determines the reliability and safety of the object, these properties should be taken into account more fully. The relevant recommendations in electric power systems are implemented at a qualitative level, intuitively, according to the operating experience. There are neither quantitative evaluations nor methodology for their performance. Therefore, a method and algorithm of quantitative assessment of integral indicators of reliability and safety of operation of thermal power units of thermal power plants as concentrated objects of continuous operation were previously analyzed by the authors. The present paper examines distributed objects of continuous operation, viz. overhead power transmission lines with a voltage of 110 kV and higher, whose service life exceeds the standard value. Attention is paid to the issues of quantitative assessment of the degree of aging for a set of overhead power transmission lines, classification of these lines to identify the most significant classes and methodology for assessing the difference in the degree of aging when classifying them according to specified types of signs (for example, the difference in the degree of aging of overhead power transmission lines of grid enterprises of electric power systems). It is shown that it unacceptable to use the estimates of the relative number of overhead power transmission lines, the service life of which exceeds the calculated one, for comparison since it causes a great risk of an erroneous decision. The methodology and algorithm of methodological support of the management of electric power systems and grid enterprises in the organization of operation, maintenance and repair have been developed.

Место и роль некоторых массовых видов птиц в биоповреждениях в Ферганской долине Узбекистана

The article provides data on the place and role of some common bird species in the Fergana Valley in biological damage. The reasons for the occurrence of biological damage in birds are discussed, the nature and degree of biological damage caused by white storks, green bee-eaters, myna, Indian and field sparrows on fish farms, power grid enterprises, viticulture and grain crops (wheat and rice) are discussed. Building their huge nests on the poles of high-voltage power lines during the year, white storks make short circuits, which lead to an interruption in the power supply. In the post-nesting period, large flocks of white storks arrive at fish farms. One bird eats an average of 600–800 g of fish per day. During spring and autumn migrations, green bee-eaters gathering at beekeeping farms, one pair per day destroys about 350–400 worker bees. Mynas, after the chicks leave the nests, together with fledglings, flies into the vineyards and, on average, damage 18.5% of the grape harvest. Field and Indian sparrows consume an average of 16.95% of the crop during the milky-wax ripeness of wheat. In rice fields during autumn migrations, the harm from sparrows is 2.1–13.4%. The article also provides data on some of the repellents used in preventing and reducing bio-damage caused by birds, discusses their effectiveness.

Application of Blockchain technology in power material performance and settlement

The current management mode and technical means of electric power materials can not meet the increasing business volume of electric power materials. In order to solve the problem that the existing management mode can not meet the demand due to the growth of power material business volume and the improvement of power service level, this application is carried out. Through the application of blockchain, artificial intelligence, mobile Internet and other technologies, the online flow of electronic documents in power material business, the blocking points of settlement business and the 7*24 all-weather settlement business are realized. Finally, it shortens the order execution cycle, reduces the cost of manual window, improves the business efficiency, and saves expenses for power grid enterprises and suppliers, and improves the quality and efficiency of supply chain operation.

Research on Prediction Method of Distribution Network Activity in Green Electric Power through PSO-WNN

The convergence and prediction accuracy of the artificial neural network prediction model are affected by the initial parameter settings of the model, and the wavelet neural network (WNN) modeling algorithm can effectively overcome this defect and achieve better prediction results. In this paper, the particle swarm optimization (PSO) algorithm is used to optimize the initial weights, and the optimal value of the particle swarm algorithm is assigned to the WNN to replace the initial random assignment of the WNN. The WNN is trained according to the backpropagation (BP) algorithm until convergence. The particle swarm optimization wavelet neural network (PSO-WNN) model is used to predict the cost of a single grid activity based on the cost driver parameters of the power grid. The prediction error analysis shows that the model significantly improves the accuracy of the activity cost prediction, which is beneficial to the grid enterprise to effectively manage the cost drivers and track the specific effects of the grid activity cost which produced by the driver parameters.

The Exploratory Research on Reform and Innovation of Project Management in Grid Enterprises under the Changing Circumstances

At present, the management systems and enterprises demand have already changed because of the environments-changing, which puts new requirements and directions for grid enterprises. This research comprehensively analyzes the current situation and problems of the project management, and then explores the profound impact of the new situation to the project management system in power grid enterprises. After that, this research also summarizes the reforms and innovation experiences of the power grid enterprises in the project management, and extracts the project management characteristics of the grid enterprises under the new situation. At the same time, based on the project management practices, we provide a new method and implementation path for grid enterprises. This method and path provide theoretical and methodological support for relevant grid enterprises to improve their management efficiency and improve organizational performance.