A Method for Industrial Electricity Assignment and Abnormal Data Filtering

Abstract

This invention discloses a method for industrial electricity allocation and anomaly data filtering, relating to the field of energy management technology. This method achieves accurate and automatic collection of electricity data by constructing an allocation mapping model of generating units, high-voltage rooms, and transformers; and ensures data quality through an anomaly filtering mechanism. This invention solves the problems of chaotic data allocation, difficulty in tracing, and low data quality in existing technologies, and is applicable to industrial energy consumption management systems, significantly improving the accuracy and efficiency of energy consumption analysis. This invention has been practically implemented in state-owned steel plants for many years.

Description

Technical Field

[0001] This invention relates to the field of industrial energy management technology, specifically to a method for processing electricity data applicable to large-scale industrial scenarios such as metallurgy and steel, and particularly to a method for electricity allocation and abnormal data filtering based on the hierarchical relationship between generator units, high-voltage rooms, and transformers. Background Technology

[0002] In energy management systems for industrial production (such as metallurgical and steel enterprises), accurate attribution of electricity consumption data is fundamental for energy consumption analysis, cost accounting, and loss management. However, current technologies for processing electricity consumption data typically suffer from the following problems: The data is poorly classified due to a lack of unified planning and mapping across the entire data chain, from generating units to high-voltage rooms, transformers, and incoming lines. After data collection, it cannot be automatically and accurately attributed to the corresponding high-voltage rooms and production lines, leading to unclear data attribution and difficulties in tracing the data.

[0003] Inaccurate data allocation: Due to unclear attribution, electricity data can often only be simply accumulated, and cannot be precisely allocated and statistically analyzed according to production units (such as pickling and rolling production lines and cold galvanizing production lines), which affects the accuracy of energy consumption analysis.

[0004] Lack of anomaly filtering: There is a lack of effective outlier identification and filtering mechanisms for the collected raw data. Null values, zero values ​​and invalid data directly enter the analysis process, polluting the data environment and leading to large errors in subsequent statistical analysis results. Summary of the Invention

[0005] The purpose of this invention is to provide a method for industrial electricity allocation and abnormal data filtering to solve the problems of chaotic data allocation, inaccurate allocation, and unreliable data quality in the prior art.

[0006] This invention discloses a method for industrial electricity allocation and abnormal data filtering, comprising the following steps: Construct an attribution mapping model: Establish a unique attribution mapping relationship between "generator unit," "high-voltage room," "transformer," and "incoming line terminal" in the industrial production site beforehand. Clarify which high-voltage room each generator unit belongs to, which transformers supply power to each high-voltage room, and which incoming line terminals each transformer corresponds to.

[0007] Data collection and aggregation: Read the raw power data and automatically aggregate the power data of each unit to its respective high-voltage room according to the aforementioned attribution mapping relationship; at the same time, automatically aggregate the incoming power of each transformer to the corresponding incoming end.

[0008] Anomaly filtering: The system identifies and filters anomalies in the aggregated electricity data. It automatically marks or removes null, zero, and invalid data to ensure the accuracy and completeness of the generated standardized electricity detail dataset.

[0009] End-to-end traceability: Through a unified attribution identifier, the entire chain of electricity data traceability is achieved from raw collection and accurate allocation to final statistics, ensuring that the data is verifiable and verifiable.

Claims

1. A method for allocating and assigning industrial electricity data, characterized in that, Includes the following steps: (1) Establish a unique attribution mapping relationship configuration table between "generator unit", "high voltage room", "transformer" and "incoming end"; (2) Read the original power data and automatically summarize the power of each unit to the corresponding high-voltage room according to the affiliation mapping relationship, and summarize the power of each transformer incoming line to the corresponding incoming line end; (3) Automatically filter and process null values, zero values ​​and abnormal data in the summarized data to generate a standardized electricity consumption detail dataset.

2. The method according to claim 1, characterized in that, The attribution mapping relationship includes the automatic matching of unit number and high-voltage room name, and the automatic matching of transformer number and high-voltage room name.

3. The method according to claim 1, characterized in that, The abnormal data filtering step includes automatically converting NULL values ​​to 0 and filtering out meaningless zero-value data.