Abstract
Improving demand response capability of power load is an important way to build a new power system with high penetration of renewable energy. Based on the measured data of regenerative electric heating load in a province of China, this paper uses big data analytic method to reclassify the regenerative electric heating load. By using the hybrid decision trees method, the five types of demand response models have been built, and the demand response capability under different incentive conditions has been analyzed. The results show that different types of regenerative electric heating load have different demand response capability, and the same regenerative electric heating load has different demand response capability at different heating periods. The demand response capability of regenerative electric heating load could be effectively improved by reasonable market-oriented incentive, which can effectively improve the wind power consumption capability and reduce the peak valley difference of power load.
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