Author:
Sun Jie,Qiu Degui,Xu Zhufa
Abstract
In the automation construction of marketing charge accounts in power supply enterprises, the key is the automation system of electric energy measurement. It covers all levels of measurement points and collection terminals in the whole network, and integrates measurement management, analysis, monitoring and information collection. The traditional electricity charge management of electric power enterprises is the process of manual meter reading, accounting and charging. Meter readers go to each customer every month to read the meter according to the meter reading time and meter reading card, record the number of electric energy meters on the meter reading card, and then copy the data of the meter reading card on the accounting card. Manual meter reading can't meet the current demand. Therefore, this paper will study the automatic management of electric power marketing charges based on RPA (Robot process automation), and build an automatic management system of electric power marketing charges. Through the comparative analysis of experimental data, the experimental results of the response accuracy of different systems show that this system is still more advantageous, and the accuracy of this system is the highest, with an average accuracy of 81.59%. However, the accuracy of reference method and reference method are 62.72% and 46.95% respectively. A perfect charging system based on RPA can not only improve the service level and corporate image of power supply companies, but also improve the management level of power supply companies, thus improving the economic benefits of enterprises.
Publisher
Darcy & Roy Press Co. Ltd.
Reference12 articles.
1. Peng Q. Research on the Risk Control of Electricity Charges in the Whole Process of Power Marketing. Management & Technology of SME, vol. 67, no. 30, pp. 25-56, 2018.
2. Jing S, Li-Li Z, Na X. Application of Hulan District Power Supply Enterprise Marketing Management Accounting System. Techniques of Automation and Applications, vol. 57, no. 20, pp. 28-56, 2017.
3. Zadorozhnyi Z M, Muravskyi V, Pochynok N, et al. Innovation Management and Automated Accounting in the Chaotic Storage Logistics. Marketing and Management of Innovations, vol. 66, no. 2, pp. 313-323, 2020.
4. Macko D. Contribution to Automated Generating of System Power-Management Specification. IEEE, vol. 48, no. 17, pp. 27-32, 2018.
5. Tahri A, El Fadil H, Belhaj F Z, et al. Management of fuel cell power and supercapacitor state-of-charge for electric vehicles. Electric Power Systems Research, vol. 160, no. 30, pp. 89-98, 2018.
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