Comprehensive energy system user portrait method and system

Abstract

The invention provides a comprehensive energy system user portrait method and system, and belongs to the field of data statistics and analysis, and the method specifically comprises the following steps: obtaining the power consumption, heat consumption and gas consumption of each user at each moment from a meter, and storing the power consumption, heat consumption and gas consumption; classifyingand preprocessing the data, and processing missing data and noise data; further subdividing the classified data, and forming a typical user energy consumption data set by utilizing a clustering method; and predicting each group of data by utilizing a prediction method according to the subdivided data after the portrait, and finally obtaining a refined user energy consumption behavior and total quantity prediction result. The total prediction result can help the comprehensive energy system to arrange a production scheduling plan, and the subdivided prediction result can help market personnel toanalyze user energy consumption habits, formulate reasonable market prices and implement reasonable demand side management, improve user energy consumption behaviors and improve system operation economy.

Description

technical field [0001] The invention relates to the field of data statistics and analysis, in particular to a user portrait method and system for an integrated energy system. Background technique [0002] With the increasingly severe energy crisis and environmental problems, improving energy utilization and the proportion of clean energy has become a key measure in the energy plans of countries around the world. The integrated energy system uses natural gas to realize the coordinated optimization and mutual conversion of electric energy and thermal energy through gas turbines, heat collector pumps and other equipment, breaking the barriers to diversified energy utilization and improving energy utilization efficiency. The integrated energy system is the main development direction of future urban energy transformation. [0003] However, compared with the traditional power system, thermal pipeline system, gas supply system, etc., the integrated energy system is more important ...

AI Technical Summary

Problems solved by technology

[0004] Existing load forecasting technologies can only predict the total amount at a certain time, but the deep-seated reasons for this total load cannot be known. Associated, there is a coupling relationship, and the total amount of each energy is forecasted separately. It is difficult to mine the correlation relationship between the utilization of various energy sources, and it is impossible to explain the relationship between the energy consumption habits of different users and the prediction results.

The prediction results can only serve the formulation of production plans, but cannot serve the energy sales market, and cannot formulate targeted demand-side management measures such as tiered prices to guide users' energy consumption behavior, reasonably avoid peaks and flat valleys, and improve the operational efficiency of the integrated energy system

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