Customer Baseline Load (CBL) Estimation Method Based on Privacy Protection Scheme Using Blockchain

In demand response (DR), customer baseline load plays an important role in determining economic compensation. Traditionally, it is believed that private data cannot be used when estimating baseline loads. This paper proposes a privacy protection scheme based on blockchain to make the use of private data possible. Based on this scheme, the baseline load can be estimated by combining customers private data and non-private data, in which the convolutional neural network (CNN) is employed to capture the relationships of these data and estimate baseline load. This method can be applied to accurately determine the authenticity of customers demand response and solve the problem of baseline load estimation for continuously participating in demand response. Finally, a comparison between our method and other estimation method demonstrates that our study can improve the rationality and reliability of baseline load estimation.