  With the rapid development of the energy internet, the proportion of flexible
loads in smart grid is getting much higher than before. It is highly important
to model flexible loads based on demand response. Therefore, a new demand
response method considering multiple flexible loads is proposed in this paper
to character the integrated demand response (IDR) resources. Firstly, a
physical process analytical deduction (PPAD) model is proposed to improve the
classification of flexible loads in industrial parks. Scenario generation, data
point augmentation, and smooth curves under various operating conditions are
considered to enhance the applicability of the model. Secondly, in view of the
strong volatility and poor modeling effect of Wasserstein-generative
adversarial networks (WGAN), an improved WGAN-gradient penalty (IWGAN-GP) model
is developed to get a faster convergence speed than traditional WGAN and
generate a higher quality samples. Finally, the PPAD and IWGAN-GP models are
jointly implemented to reveal the degree of correlation between flexible loads.
Meanwhile, an intelligent offline database is built to deal with the impact of
nonlinear factors in different response scenarios. Numerical examples have been
performed with the results proving that the proposed method is significantly
better than the existing technologies in reducing load modeling deviation and
improving the responsiveness of park loads.
