Stochastic optimal dispatching strategy of electricity-hydrogen-gas-heat integrated energy system based on improved spectral clustering method

The couplings and interactions among the multi-energy resources in the integrated energy system (IES) significantly improve the utilization of renewables and reduce carbon emissions. Hydrogen is considered to be one of the most potential energy carriers due to its excellent characteristics. Therefore, the use of hydrogen has become a hot spot in the energy field. Most researches on power to gas (P2G) technology do not use the potential advantages of hydrogen but only analyze the coupling relationship between electricity and natural gas, so the efficiency is low. Moreover, the uncertainties of renewable energy and load bring challenges to the power system dispatching. To solve these problems, an electricity-hydrogen-gas-heat integrated energy system (EHGHS) stochastic optimal dispatching strategy based on improved spectral clustering method is presented in this paper. First, the structure of EHGHS and the energy conversion unit in the EHGHS is modeled. A two-stage P2G technology is proposed which exploits the hydrogen utilization process and the combined heat and power generation process. Then a scenario reduction method based on improved spectral clustering is presented to describe the uncertain characteristics of renewable energy and load. The curve distance and cosine similarity are developed to represent the similarity between scenarios. Finally, the effectiveness, economics, and sensitivity of the stochastic optimal dispatching model are verified by case studies.

Automated summary

The coupling and interaction among multi-energy resources in an integrated energy system improves renewable energy utilization and reduces carbon emissions. Hydrogen is seen as a highly potential energy carrier due to its excellent characteristics, making it a hot topic in the field. However, most research on power to gas technology do not fully utilize the advantages of hydrogen, resulting in low efficiency.