Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data
As we all know, the behavior of stealing electric energy governance is always the difficulty and key point in the management of electric power enterprises. In recent years, as bitcoin’s value continued to climb, the theft of electricity by bitcoin mining user began to appear. In order to solve the p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-07-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722003018 |
| _version_ | 1828422314390192128 |
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| author | LiYan Kang Ying Shang MuXin Zhang LiYing Liao |
| author_facet | LiYan Kang Ying Shang MuXin Zhang LiYing Liao |
| author_sort | LiYan Kang |
| collection | DOAJ |
| description | As we all know, the behavior of stealing electric energy governance is always the difficulty and key point in the management of electric power enterprises. In recent years, as bitcoin’s value continued to climb, the theft of electricity by bitcoin mining user began to appear. In order to solve the power theft problem of bitcoin mining users, we conducted an in-depth study on the power consumption behavior of such users based on the power data analysis technology. This paper analyzes the power consumption characteristics of bitcoin mining users and uses electric data acquire system to monitor power consumption behavior. The paper makes comparative analysis on the massive data such as voltage and power of the electric energy acquisition system, analyzes and calculates the Pearson correlation coefficient between the electricity consumption of each customer and the line loss statistics of the power station by using Pearson correlation algorithm combined with the power loss of the power station, and analyzes the suspected users of stealing electric energy by taking an actual example. Through our research, we found a total of 16 bitcoin miners suspected of stealing electricity. After on-site investigation and evidence collection, we found that 10 of the users did have abnormal power consumption, and the accuracy rate reached 62.50%. Therefore, the economic benefits of this research are very significant. |
| first_indexed | 2024-12-10T15:47:07Z |
| format | Article |
| id | doaj.art-99e2062c6a5b41aabc8fc43e2f0584e8 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-12-10T15:47:07Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-99e2062c6a5b41aabc8fc43e2f0584e82022-12-22T01:42:56ZengElsevierEnergy Reports2352-48472022-07-01811831189Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy dataLiYan Kang0Ying Shang1MuXin Zhang2LiYing Liao3Corresponding author.; State Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, 19A, Hunnan East Road, Hunnan District Shenyang, Liaoning, 110003, ChinaState Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, 19A, Hunnan East Road, Hunnan District Shenyang, Liaoning, 110003, ChinaState Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, 19A, Hunnan East Road, Hunnan District Shenyang, Liaoning, 110003, ChinaState Grid Liaoning Electric Power Co., Ltd. Marketing Service Center, 19A, Hunnan East Road, Hunnan District Shenyang, Liaoning, 110003, ChinaAs we all know, the behavior of stealing electric energy governance is always the difficulty and key point in the management of electric power enterprises. In recent years, as bitcoin’s value continued to climb, the theft of electricity by bitcoin mining user began to appear. In order to solve the power theft problem of bitcoin mining users, we conducted an in-depth study on the power consumption behavior of such users based on the power data analysis technology. This paper analyzes the power consumption characteristics of bitcoin mining users and uses electric data acquire system to monitor power consumption behavior. The paper makes comparative analysis on the massive data such as voltage and power of the electric energy acquisition system, analyzes and calculates the Pearson correlation coefficient between the electricity consumption of each customer and the line loss statistics of the power station by using Pearson correlation algorithm combined with the power loss of the power station, and analyzes the suspected users of stealing electric energy by taking an actual example. Through our research, we found a total of 16 bitcoin miners suspected of stealing electricity. After on-site investigation and evidence collection, we found that 10 of the users did have abnormal power consumption, and the accuracy rate reached 62.50%. Therefore, the economic benefits of this research are very significant.http://www.sciencedirect.com/science/article/pii/S2352484722003018Stealing electric energyBitcoin miningPearson correlation algorithmElectric energy acquisition system |
| spellingShingle | LiYan Kang Ying Shang MuXin Zhang LiYing Liao Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data Energy Reports Stealing electric energy Bitcoin mining Pearson correlation algorithm Electric energy acquisition system |
| title | Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| title_full | Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| title_fullStr | Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| title_full_unstemmed | Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| title_short | Research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| title_sort | research on monitoring technology of power stealing behavior in bitcoin mining based on analyzing electric energy data |
| topic | Stealing electric energy Bitcoin mining Pearson correlation algorithm Electric energy acquisition system |
| url | http://www.sciencedirect.com/science/article/pii/S2352484722003018 |
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