Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm
Abstract In the construction of a new power system, the identification and evaluation of power consumption status of power customers will become an important basis for them to participate in the emerging businesses such as demand response and virtual power plants. In order to ensure the power safety...
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | The Journal of Engineering |
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| Online Access: | https://doi.org/10.1049/tje2.70018 |
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| author | Xixiang Zhang Qi Meng Jun Yang |
| author_facet | Xixiang Zhang Qi Meng Jun Yang |
| author_sort | Xixiang Zhang |
| collection | DOAJ |
| description | Abstract In the construction of a new power system, the identification and evaluation of power consumption status of power customers will become an important basis for them to participate in the emerging businesses such as demand response and virtual power plants. In order to ensure the power safety of important power customers, a new evaluation of power consumption status of important power customers based on the AHP (analytic hierarchy process)‐TOPSIS (technique for order preference by similarity to an ideal solution) algorithm is proposed by fully mining and applying the power big data. Firstly, a power consumption big data analysis platform based on the Hadoop architecture is built to provide a high‐performance platform support for big data analysis. Secondly, nine evaluation indexes are constructed from the three dimensions of voltage, load and synthesis, which objectively and scientifically describes the power consumption status of important power customers. Finally, the AHP‐TOPSIS algorithm is used to evaluate and analyse the voltage, load and comprehensive indicators respectively, thus, obtaining the evaluation values of three kinds of indicators. The power consumption status scores of important power customers are determined by the variable weight weighted summation. The rationality and feasibility of the method and algorithm are proved by example analysis and field verification. This method helps to promote the transformation from post fault emergency repair to warning beforehand. It has the multiple effects of ensuring safe power consumption, supporting accurate patrolling and active emergency repair serving. |
| format | Article |
| id | doaj-art-0d760e9a73cf4ad688aef7a43bbd5373 |
| institution | OA Journals |
| issn | 2051-3305 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Engineering |
| spelling | doaj-art-0d760e9a73cf4ad688aef7a43bbd53732025-08-20T02:23:34ZengWileyThe Journal of Engineering2051-33052024-11-01202411n/an/a10.1049/tje2.70018Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithmXixiang Zhang0Qi Meng1Jun Yang2China Southern Power Grid Guangxi Power Grid Co. Ltd. Nanning ChinaChina Southern Power Grid Guangxi Power Grid Co. Ltd. Nanning ChinaChina Southern Power Grid Guangxi Power Grid Co. Ltd. Nanning ChinaAbstract In the construction of a new power system, the identification and evaluation of power consumption status of power customers will become an important basis for them to participate in the emerging businesses such as demand response and virtual power plants. In order to ensure the power safety of important power customers, a new evaluation of power consumption status of important power customers based on the AHP (analytic hierarchy process)‐TOPSIS (technique for order preference by similarity to an ideal solution) algorithm is proposed by fully mining and applying the power big data. Firstly, a power consumption big data analysis platform based on the Hadoop architecture is built to provide a high‐performance platform support for big data analysis. Secondly, nine evaluation indexes are constructed from the three dimensions of voltage, load and synthesis, which objectively and scientifically describes the power consumption status of important power customers. Finally, the AHP‐TOPSIS algorithm is used to evaluate and analyse the voltage, load and comprehensive indicators respectively, thus, obtaining the evaluation values of three kinds of indicators. The power consumption status scores of important power customers are determined by the variable weight weighted summation. The rationality and feasibility of the method and algorithm are proved by example analysis and field verification. This method helps to promote the transformation from post fault emergency repair to warning beforehand. It has the multiple effects of ensuring safe power consumption, supporting accurate patrolling and active emergency repair serving.https://doi.org/10.1049/tje2.70018data analysisdata mining |
| spellingShingle | Xixiang Zhang Qi Meng Jun Yang Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm The Journal of Engineering data analysis data mining |
| title | Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm |
| title_full | Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm |
| title_fullStr | Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm |
| title_full_unstemmed | Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm |
| title_short | Power consumption state evaluation of important power customers based on AHP‐TOPSIS algorithm |
| title_sort | power consumption state evaluation of important power customers based on ahp topsis algorithm |
| topic | data analysis data mining |
| url | https://doi.org/10.1049/tje2.70018 |
| work_keys_str_mv | AT xixiangzhang powerconsumptionstateevaluationofimportantpowercustomersbasedonahptopsisalgorithm AT qimeng powerconsumptionstateevaluationofimportantpowercustomersbasedonahptopsisalgorithm AT junyang powerconsumptionstateevaluationofimportantpowercustomersbasedonahptopsisalgorithm |