Load Characteristic Portrait Model of Power Users in Epidemic Stage Applying Data-Driven Method

doi:10.12204/j.issn.1000-7229.2021.02.012

Abstract

Abstract:

Load portrait modeling of power user is an important user-oriented method to create differentiated labels by mining the load characteristics in power consumption data. Most of the existing research focuses on the study of portrait methods, but lacks comprehensive load characteristic label system. This paper proposes a general method of load characteristic analysis based on data-driven. The load characteristic label system is constructed from power consumption regularity, smoothness, load control capability and epidemic impact, which are most concerned by dispatching department. Firstly, the typical load curve is extracted from massive actual load data by using fuzzy C-means clustering algorithm. Considering the power consumption characteristics of each industry from above four aspects, a comprehensive load characteristic label system and the load characteristic portrait models of different power users are established. Secondly, the load characteristic label is refined and every definition and calculation method of corresponding index is given. Furthermore, the index boundary is determined by fuzzy clustering algorithm, and the smoothness label is scored by entropy weight method. Finally, the data of typical users in different industries are analyzed from an example, and universal index boundaries are given, which provide a new idea for load modeling of users in various industries.

Key words: data-driven, load characteristic portrait model, load characteristic label, epidemic impact degree, load smoothness

CLC Number:

TM714

LU Xiao, XU Chunlei, LENG Zhaoying, WU Haiwei, CHEN Zhong. Load Characteristic Portrait Model of Power Users in Epidemic Stage Applying Data-Driven Method[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(2): 93-106.

Figures/Tables 36

Table 1 Load regularity label

Table 2 Load smoothness label

Table 3 Load control capability label

Table 4 The impact of COVID-19 label

Table 5 Criteria for intraday working-time characteristic

Table 6 Criteria for day-and-night electricity characteristic

Table 7 Criteria for morning-and-evening peak characteristic

Fig.1 Typical users'peak and valley period division

Table 8 The similarity of weekly load curve of transportation user 2

Table 9 Criteria for monthly electricity similarity

Table 10 Criteria for quarterly electricity similarity

Table 11 Criteria for seasonal electricity regularity

Fig.2 Cooling load curve in summer and heating load curve in winter for typical users

Table 12 Seasonal electricity regularity indexes of typical users

Table 13 Weight of each index in load smoothness label

Table 14 Comprehensive score and ranking of users'load smoothness (from bad to good)

Table 15 Criteria for load smoothness

Fig.3 Typical load curves of steel industry user 2 under incentive load control

Fig.4 Typical load curves of steel industry user 2 under price-based load control

Table 16 Indices of typical load curves of steel industry user 2 under incentive load control

Table 17 Indices of typical load curves of steel industry user 2 under price-based load control

Table 18 Criteria for load control

Table 19 Criteria for epidemic impact degree and epidemic recovery degree

Fig.5 Typical load curves and daily electricity consumption of commercial user1 in 2019 and 2020 epidemic period

Fig.6 Typical load curves and daily electricity consumption of electronic equipment manufacturing user 2 in 2019 and 2020 epidemic period

Fig.7 Daily electricity consumption of information transmission software and information technology service industry user 1 in 2019 and 2020

Fig.8 Load characteristic label for steel industry user 1

Table A1 Calculation results of intraday working-time characteristic

Table A2 Calculation results of day-and-night electricity characteristic

Table A3 Calculation results of morning-and-evening peak characteristic

Table A4 Calculation results of peak-valley visibility characteristic

Table A5 Calculation results of monthly electricity similarity

Table A6 Calculation results of quarterly electricity similarity

Table A7 Calculation results of seasonal electricity similarity

Table A8 Calculation results of load smoothness label

Table A9 Calculation results of epidemic impact degree

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