Distribution Network Expansion Planning Method Based on Air-Conditioning Load Data Mining

doi:10.12204/j.issn.1000-7229.2021.11.011

Abstract

Abstract:

This paper focuses on load data mining in the field of distribution network planning, on the basis of actual data, the model of response evaluation based on air-conditioning load data mining is established, separating air-conditioning load from power consumption data, which can describe the demand response limits accurately, and the distribution system expansion planning model is also proposed and solved by aiming at minimizing the total cost of the distribution system. The validity of the model is verified by an IEEE 33-node example. The results show that the data mining methodology can be used to evaluate the demand response potential, which enables the distribution network planning scheme to be optimized, the total system cost to be reduced, the investment of distribution system expansion to be delayed, and the overall economic efficiency of distribution system to be improved. The proposed method has important practical significance and function for distribution network planning.

Key words: data mining, demand response, distribution network planning

CLC Number:

TM727

SU Ning, LI Xiaotong, LIANG Huishi, GONG Xiaoxu, LÜ Fengbo, XI Yanna, QI Buyang. Distribution Network Expansion Planning Method Based on Air-Conditioning Load Data Mining[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(11): 100-107.

Figures/Tables 10

Fig.1 Scatter point of load temperature response

Fig.2 Response slope of air-conditioning load corresponding to temperature

Fig.3 Collaborative planning framework

Fig.4 IEEE 33-node distribution network example

Table 1 Planning scheme of new load expansion

Fig.5 Probability distribution of response slope

Fig.6 The best planning scheme (case2)

Table 2 Planning scheme comparison

Table 3 Interruptible load factor of air-conditioning at each node

Fig.7 Relationship between total cost and demand response upper-limit

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