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DFHSMM-based non-intrusion type electric power load monitoring method and system

A non-intrusive technology for power loads, applied in forecasting, relational databases, electrical digital data processing, etc., can solve problems such as poor practicability

Active Publication Date: 2017-04-26
TIANJIN TRANSENERGY TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the reported NILM method based on HMM and its extended model either fails to consider the duration characteristics of the working state of the electrical equipment (such as literature [9], [10], [11]), or needs to analyze all Modeling of electrical equipment is not suitable for occasions where there are unmodeled electrical equipment, and the practicability is poor (such as literature [7] and [11])

Method used

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  • DFHSMM-based non-intrusion type electric power load monitoring method and system
  • DFHSMM-based non-intrusion type electric power load monitoring method and system
  • DFHSMM-based non-intrusion type electric power load monitoring method and system

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Effect test

Embodiment 1

[0175] Embodiment 1 verifies the effectiveness of the method of the present invention through simulation data. In this embodiment, the total monitoring time is 28 days, the total load power signal is active power, the standard deviation is 3W, and the sampling frequency is 1 / 3Hz. In this example, refrigerators, home theaters and monitors are selected as electrical equipment for modeling, and the unit of working state duration is minutes. The identification results are shown in Table 2.

[0176] Table 1 Example 1 Working state active power reference value and duration Gamma distribution parameters of electrical equipment [7]

[0177]

[0178] Table 2 Example 1 Identification Results

[0179] Electrical equipment Precision recall F-Measure refrigerator 100％ 99.04％ 99.52％ home theater 83.02％ 82.04％ 82.53％ monitor 87.71％ 93.46％ 90.49％ overall 89.83％ 92.27％ 91.03％

[0180] As can be seen from Table 2, the method of the pres...

Embodiment 2

[0181] Example 2 verifies the effectiveness of the method of the present invention through measured data. The embodiment adopts the phase A data of the public BLUED data set [16] , the electric load power signal uses active power and reactive power, and the sampling frequency is 1 / 3Hz. Refrigerators, air compressors, hair dryers, shredders, backyard lighting and toilet lighting are selected as electrical equipment for modeling, among which The machine is a multi-state device with two working modes. The identification results are shown in Table 3.

[0182] Table 3 Example 2 Identification Results

[0183] Electrical equipment Precision recall F-Measure refrigerator 99.64％ 94.79％ 97.15％ air compressor 100％ 100％ 100％ hair dryer 100％ 100％ 100％ Shredder (mode 1) 71.74％ 76.74％ 74.16％ Shredder (Mode 2) 100％ 100％ 100％ backyard lighting 100％ 76.71％ 86.82％ bathroom lighting 100％ 100％ 100％ overall 99.68％ 91....

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Abstract

The invention belongs to the field of electric power load monitoring and especially relates to a DFHSMM-based non-intrusion type electric power load monitoring method and system. A DFHMM model and an HSMM model are combined to form a DFHSMM model, an electric power load and electrical equipment included therein are modeled by use of the DFHSMM model, a novel method is provided for solving the DFHSMM model, and the work state of the electrical equipment is identified finally. The method and system have the following advantages: a stable-state power feature and a work state duration feature of the electrical equipment can be taken into consideration at the same time, the method and system are applied to occasions where non-modeled electrical equipment exists, and the practicality and the robustness are quite high; constraint conditions are increased by use of load events, the solution space of a load monitoring optimization model is substantially reduced, and the solving speed of the model is improved; and the electrical equipment is classified according to the power feature, the load monitoring optimization model is solved for each electrical equipment cluster, and the overall solving speed is improved.

Description

technical field [0001] The invention belongs to the field of electric load monitoring and utilization, and in particular relates to a non-invasive electric load monitoring method and system based on DFHSMM. Background technique [0002] The detailed monitoring of power consumption of power load can obtain the usage of each or every kind of electric equipment inside the power load. On the one hand, it helps power companies understand the load composition and power consumption of each component, so as to reasonably determine the system operation mode and system load model, and improve the security and economy of the power grid; on the other hand, it helps Users understand the use of each or each type of electrical equipment, and guide users to use electricity reasonably, thereby reducing power consumption and peak loads, reducing electricity expenses, and peak load reduction can further improve the economy of power grid operation. Studies have shown that feeding back power co...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06F17/30
CPCG06F16/285G06Q10/04G06Q10/067G06Q50/06Y02P90/82
Inventor 栾文鹏刘博余贻鑫陈鸿川刘浩冯丽杨静杜伟强马骁
Owner TIANJIN TRANSENERGY TECH
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