Optimal schedule of solid electric thermal storage considering consumer behavior characteristics in combined electricity and heat networks

Solid electric thermal storage (SETS) can convert electricity into heat energy, which is scheduled to alleviate wind power curtailment during the heating period. However, different consumer behavior characteristics of SETSs cause the scheduled results to be inconsistent with expectations by the existing methods, which is crucial to schedule distributed SETSs in combined electricity and heat networks (CEHN). To tack this challenge, we propose an optimal schedule framework based on consumer behavior characteristics of distributed SETSs and evaluation indices. Firstly, a SETS power prediction model combining the cyber-physical approach (CPA) with iterative dichotomiser3 (ID3) is proposed, and the prediction results are used to obtain the consumer behavior characteristics of various types of distributed SETSs. Secondly, an optimal schedule model of CEHN is developed considering different consumer behavior characteristics of SETSs. Thirdly, to evaluate the performance of the proposed schedule model, two evaluation indices are developed to enhance the consistency of scheduled results and expectations of electric and heat power. The proposed framework is verified by numerical simulations. Compared with the two traditional methods, the wind power curtailment by the proposed methods is reduced by 5.49% and 0.34%, and electric and heat power evaluation indices are enhanced by 24.52% and 20.08%, respectively.