Optimal scheduling of hydrogen storage in integrated energy system including multi-source and load uncertainties
Laiqing Yan, Xiaoyu Zhang, Zia Ullah, Hany M. Hasanien
Abstract
Demand response (DR) is a crucial element in the optimization of integrated energy systems (IESs) that incorporate distributed generation (DG). However, its inherent uncertainty poses significant challenges to the economic viability of IESs. This research presents a novel economic dispatch model for IESs utilizing information gap decision theory (IGDT). The model integrates various components to improve IES performance and dispatch efficiency. With a focus on hydrogen energy, the model considers users' energy consumption patterns, thereby improving system flexibility. By applying IGDT, the model effectively addresses the uncertainty associated with DR and DG, overcoming the limitations of traditional methods. The research findings indicate that in relation to the baseline method, the proposed model has the potential to reduce operating costs by 6.3 % and carbon emissions by 4.2 %. The integration of a stepwise carbon trading mechanism helps boost both economic and environmental advantages, achieving a 100 % wind power consumption rate in the optimized plan. In addition, the daily operating costs are minimized to 23,758.99 ¥, while carbon emissions are significantly reduced to 34,192 kg. These findings provide quantitative decision support for IES dispatch planners to help them develop effective dispatch strategies that are consistent with low-carbon economic initiatives. • This paper presents a novel integrated energy systems economic dispatch model based on information gap decision theory. • The hydrogen energy is incorporated into the system modeling. • Demand response and distributed generation uncertainty are taken into account. • Practical measurements are implemented to verify the system model. • The effectiveness of the proposed method is compared with other methods.