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In the context of deepening electric power system reform, the refined assessment of user-side adjustable potential is an important foundation to support demand response implementation. In this paper, a demand response potential assessment model based on the Iterative Self-Organising Data Analysis Technique Algorithm (ISODATA) and Gaussian Mixture Model (GMM) is constructed. Firstly, based on the characteristic indicators of electricity load, ISODATA is used to cluster residential customers and daily characteristics, and then typical data are selected and introduced into the GMM to achieve a refined assessment of demand response potential. Finally, the feasibility and effectiveness of the method are demonstrated through example simulations. The proposed method mines the distribution characteristics and response potential of electric loads through historical electricity consumption data, thus realizing the quantification of hourly response potential.
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Long et al. (2024) studied this question.
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