Multi-time scale scheduling optimization of integrated energy systems considering seasonal hydrogen utilization and multiple demand responses

Hydrogen energy is recognized as a crucial solution for addressing energy crises and advancing energy conservation and emissions reduction. It will play a significant role in the future integrated energy systems (IESs). However, the influence of seasonal variations in scheduling optimization of hydrogen-integrated energy system has rarely been investigated. A low-carbon scheduling model for IES, adopting multiple demand responses and a ladder-type carbon trading mechanism, has been established. Additionally, a multi-time scale dispatch optimization strategy considering seasonal hydrogen utilization is thus proposed in this paper. Specifically, day-ahead scheduling optimizes the system taking into account the seasonal variations of renewable energy and load. In the intraday stage, rolling optimization is adopted to address the forecasting errors introduced by wind and photovoltaic fluctuations. In the real-time stage, chance-constrained methods are employed to ensure short-term supply-demand balance. The efficacy of the proposed strategy is verified using real-world measurements, and the results show the multi-time scale scheduling strategy and multiple demand responses effectively enhanced the system's self-regulation capability, leading to a 12% increase in renewable energy absorption. In addition, seasonal hydrogen utilization is essential for system design, as it enhances the absorption of renewable energy, reducing the purchase cost by 4% and the total cost by 2.6%.