Non-overlapping moving compressive measurement algorithm for electrical energy estimation of distorted m-sequence dynamic test signal
•Typical intrinsic characteristics analysis of large power electrical loads.•Distorted m-sequence dynamic test signal model to reflect the characteristics.•Non-overlapping moving compressive measurement algorithm to estimate electric energy. The complex random characteristics in smart grid lead to i...
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| Published in | Applied energy Vol. 251; p. 113234 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.10.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0306-2619 1872-9118 |
| DOI | 10.1016/j.apenergy.2019.05.037 |
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| Abstract | •Typical intrinsic characteristics analysis of large power electrical loads.•Distorted m-sequence dynamic test signal model to reflect the characteristics.•Non-overlapping moving compressive measurement algorithm to estimate electric energy.
The complex random characteristics in smart grid lead to inaccuracy of smart electricity metering. This is caused by the power filter and energy accumulation algorithm under dynamic signal conditions. By analyzing the typical intrinsic characteristics of large power electrical loads, this paper proposes a distorted m-sequence dynamic test (DmDT) signal model to reflect the characteristics and summarizes the parameter set that relates to the characteristics. In addition, based on the compressive measurement (CM) theory, a novel non-overlapping moving compressive measurement (NOLM-CM) algorithm is proposed to accurately estimate electrical energy. The performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm is tested under representative distorted dynamic random conditions. Simulation and experimental results indicate that the non-overlapping moving compressive measurement (NOLM-CM) algorithm achieves accurate estimation of electrical energy. Furthermore, the comparisons with five popular window-based estimation algorithms by simulations verify the higher performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm. |
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| AbstractList | •Typical intrinsic characteristics analysis of large power electrical loads.•Distorted m-sequence dynamic test signal model to reflect the characteristics.•Non-overlapping moving compressive measurement algorithm to estimate electric energy.
The complex random characteristics in smart grid lead to inaccuracy of smart electricity metering. This is caused by the power filter and energy accumulation algorithm under dynamic signal conditions. By analyzing the typical intrinsic characteristics of large power electrical loads, this paper proposes a distorted m-sequence dynamic test (DmDT) signal model to reflect the characteristics and summarizes the parameter set that relates to the characteristics. In addition, based on the compressive measurement (CM) theory, a novel non-overlapping moving compressive measurement (NOLM-CM) algorithm is proposed to accurately estimate electrical energy. The performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm is tested under representative distorted dynamic random conditions. Simulation and experimental results indicate that the non-overlapping moving compressive measurement (NOLM-CM) algorithm achieves accurate estimation of electrical energy. Furthermore, the comparisons with five popular window-based estimation algorithms by simulations verify the higher performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm. The complex random characteristics in smart grid lead to inaccuracy of smart electricity metering. This is caused by the power filter and energy accumulation algorithm under dynamic signal conditions. By analyzing the typical intrinsic characteristics of large power electrical loads, this paper proposes a distorted m-sequence dynamic test (DmDT) signal model to reflect the characteristics and summarizes the parameter set that relates to the characteristics. In addition, based on the compressive measurement (CM) theory, a novel non-overlapping moving compressive measurement (NOLM-CM) algorithm is proposed to accurately estimate electrical energy. The performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm is tested under representative distorted dynamic random conditions. Simulation and experimental results indicate that the non-overlapping moving compressive measurement (NOLM-CM) algorithm achieves accurate estimation of electrical energy. Furthermore, the comparisons with five popular window-based estimation algorithms by simulations verify the higher performance of the non-overlapping moving compressive measurement (NOLM-CM) algorithm. |
| ArticleNumber | 113234 |
| Author | Wang, Lin Yuan, Ruiming Wang, Jing Wang, Xuewei |
| Author_xml | – sequence: 1 givenname: Xuewei orcidid: 0000-0002-7099-8641 surname: Wang fullname: Wang, Xuewei email: wangxw@mail.buct.edu.cn organization: College of Information Science and Technology, Beijing University of Chemical Technology, 100029 Beijing, China – sequence: 2 givenname: Jing surname: Wang fullname: Wang, Jing organization: College of Information Science and Technology, Beijing University of Chemical Technology, 100029 Beijing, China – sequence: 3 givenname: Lin surname: Wang fullname: Wang, Lin organization: College of Information Science and Technology, Beijing University of Chemical Technology, 100029 Beijing, China – sequence: 4 givenname: Ruiming surname: Yuan fullname: Yuan, Ruiming organization: Institute of Power Research, State Grid Jibei Electric Power Company Limited, 100045 Beijing, China |
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| Keywords | Test signal Compressive measurement Electrical energy Smart electricity meter Dynamic load |
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| Title | Non-overlapping moving compressive measurement algorithm for electrical energy estimation of distorted m-sequence dynamic test signal |
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