An Optimal Scheduling Method for Demand-Side Resource Clustering in Distribution Networks Based on Customer Directrix Load Reconfiguration

doi:10.11930/j.issn.1004-9649.202412032

Abstract

Abstract:

Demand response is a key means of regulating the flexibility of the distribution network and optimizing the dispatch of demand-side resources. To fully utilize the adjustable of demand-side resources, a demand-side resource cluster optimization dispatch method based on load baseline reconstruction in the distribution network is proposed. A fuzzy set is used to construct an model for the output of new energy, and a load baseline model considering the prediction error of new energy is reconstructed. The adjustable power domain of the adjustable load resource cluster is quantified based the idea of time-period decoupling dimensionality reduction, and an intraday optimization model for the demand-side resource cluster participating in the baseline-type response is proposed. Through the example, it can be seen that the proposed method can not only improve the new energy consumption capacity, but also improve the economic benefits of the power grid.

Key words: uncertainty analysis, customer directrix load, robust optimization of distribution, demand response

YANG Xiong, LI Juan, JIANG Yunlong, LI Hongmei, XU Wanyun, LI Xiaolu, GUO Ruipeng. An Optimal Scheduling Method for Demand-Side Resource Clustering in Distribution Networks Based on Customer Directrix Load Reconfiguration[J]. Electric Power, 2025, 58(10): 163-170.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202412032

https://www.electricpower.com.cn/EN/Y2025/V58/I10/163

Figures/Tables 9

Fig.1 Adjustable power domain for aggregated resources

Fig.2 Improved IEEE 33 bus system

Fig.3 Air-conditioning cluster adjustable power

Fig.4 Adjustable total power boundary for electric vehicle clusters

Fig.5 Case1 optimal power usage trajectory

Fig.6 Case2 optimal power usage trajectory

Fig.7 Case3 optimal power usage trajectory

Table 1 Economic benefits of the grid under different cases

方案	与重构前准线相似度/%	与重构后准线相似度/%	激励成本/元	用电成本/元	净成本/ 元	新能源消纳率/%
1	28.1	35.8	0	22 981.5	23 022.6	76.2
2	21.3	89.1	6 724.6	46 392.9	39 718.4	83.4
3	23.6	84.3	5 038.8	21 075.1	16 101.5	87.6

Fig.8 Air conditioning, electric vehicle response capacity

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