Artificial intelligence-based distribution transformer anomaly analysis and early warning method

Abstract

The invention discloses an artificial intelligence-based distribution transformer anomaly analysis and early warning method, which comprises the following steps: performing sensitivity analysis on associated factors such as air temperature, capacity and operation age limit, constructing a TOPSIS-based evaluation algorithm by using a multi-dimensional data analysis and mining technology, constructing an evaluation model, evaluating and scoring each distribution transformer by using the TOPSIS evaluation algorithm, estimating the distribution transformer overload occurrence probability, issuingan advanced early warning notification to a professional department, providing differentiated operation and maintenance suggestions for abnormal distribution transformers according to the severity reflected by scoring, providing big data support for lean operation and maintenance of the distribution transformers, thus realizing post-event governance to pre-event pre-control, improving the advancedmonitoring, early warning and operation and maintenance level of the distribution transformers, and reducing the distribution transformer overload rate.

Description

Technical field:

[0001] The invention relates to the field of power supply and transformation maintenance, in particular to an artificial intelligence-based analysis and early warning method for distribution transformer abnormality. Background technique:

[0002] With the continuous development of social economy and the rapid improvement of people's lives, the demand for electricity in the whole society continues to increase, especially during the summer and winter peak load periods, distribution transformers (low voltage, three-phase imbalance) lead to heavy overload of transformers Frequently, the resulting complaints from residents are also high. How to solve the abnormal operation of distribution transformers, avoid equipment accidents, improve power supply quality, power supply reliability and high-quality service levels is particularly important.

[0003] In the prior art, the distribution transformers are regularly inspected to find out the problems and repair them. T...

Examples

Embodiment

[0028] Example: see figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 and Figure 8 .

[0029] The specific steps of the distribution transformer abnormality analysis and early warning method based on artificial intelligence are as follows: 1. Collect the distribution transformer overload record data through corresponding sensors and perform preprocessing; 2. Based on the correlation analysis method of mutual information coefficient Select the key factors affecting the abnormality of the public variable from the data information; 3. Through multi-dimensional analysis methods, analyze the change of overload under different factors, and obtain the weight of each factor affecting the overload of the public variable; 4. Use the K-Means algorithm to analyze the overload Common change clustering analysis, get overload common change clustering results, select the best overload common change characteristics and types; 5. Based on the TOPSIS evaluat...

Technical field:

[0001] The invention relates to the field of power supply and transformation maintenance, in particular to an artificial intelligence-based analysis and early warning method for distribution transformer abnormality. Background technique:

[0002] With the continuous development of social economy and the rapid improvement of people's lives, the demand for electricity in the whole society continues to increase, especially during the summer and winter peak load periods, distribution transformers (low voltage, three-phase imbalance) lead to heavy overload of transformers Frequently, the resulting complaints from residents are also high. How to solve the abnormal operation of distribution transformers, avoid equipment accidents, improve power supply quality, power supply reliability and high-quality service levels is particularly important.

[0003] In the prior art, the distribution transformers are regularly inspected to find out the problems and repair them. T...

Examples

Embodiment

[0028] Example: see figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 and Figure 8 .

[0029] The specific steps of the distribution transformer abnormality analysis and early warning method based on artificial intelligence are as follows: 1. Collect the distribution transformer overload record data through corresponding sensors and perform preprocessing; 2. Based on the correlation analysis method of mutual information coefficient Select the key factors affecting the abnormality of the public variable from the data information; 3. Through multi-dimensional analysis methods, analyze the change of overload under different factors, and obtain the weight of each factor affecting the overload of the public variable; 4. Use the K-Means algorithm to analyze the overload Common change clustering analysis, get overload common change clustering results, select the best overload common change characteristics and types; 5. Based on the TOPSIS evaluat...

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