Hierarchical optimal scheduling of IES considering SOFC degradation, internal and external uncertainties

Existing research has not adequately accounted for the nonlinear characteristics and degradation of solid oxide fuel cell (SOFC) and lacks a systematic approach to handling internal uncertainties. To address this, this paper proposes a hierarchical economic dispatch method for integrated energy systems (IES) that incorporates the degradation costs of SOFC and uncertainties from both internal and external sources. Firstly, this paper employs a system-level electrochemical-thermodynamic coupled (ETC) modeling approach for SOFCs and exchange membrane electrolyzer (PEMEC). It characterizes the operational characteristics and thermodynamic processes of SOFCs at different operating temperatures and subsequently derives the degradation costs associated with SOFCs. Secondly, the concept of internal uncertainty is introduced, and a hierarchical scheduling framework is established to mitigate uncertainties at the day-ahead and intra-day time scales progressively. In the day-ahead layer, the ETC model is treated with piecewise linearization and an hourly dispatch plan is obtained based on short-term forecast data; in the intra-day layer, the ETC model is processed with local linearization, and rolling optimization is conducted based on ultra-short-term forecast data. Furthermore, a feedback correction link is utilized to maintain the power balance within the IES. Finally, the proposed approach is tested in an IES case study, and the results demonstrate the effectiveness and superiority of the scheme.