A real-time dispatch model of CAES with considering the part-load characteristics and the power regulation uncertainty. (February 2019) - Li, Yaowang; Miao, Shihong; Yin, Binxin; Yang, Weichen; Zhang, Shixu; Luo, Xing; Wang, Jihong
Highlights: The part-load characteristics of CAES are considered in the modelling process and the corresponding mathematical descriptions are derived in the developed real-time dispatch model. The compressing power, the generating power, the air pressure and the gas consumption all have correlations to the power regulation uncertainty in the developed dispatch model. The dynamic constraints of CAES under the real-time dispatch time scale are modelled, and the optimal real-time dispatch model for the power system with a CAES plant is developed. The CAES real-time dispatch model is converted into its equivalent deterministic linear formulation. The converted formulation can be solved by conventional solver. Abstract: Compressed Air Energy Storage (CAES) has its merits of large-scale, fast response, quick ramping and flexible operation, it can play an important role in power system real-time dispatch. However, there are very limited studies that focus on the real-time dispatch model of CAES. A specific model is developed in the paper for this purpose, which is based on a dispatch framework complied with the existing power control systems operated in China. The part-load characteristics of CAES and the power regulation uncertainty are considered in the developed model and thus it can mimic the practical situations. Then, an optimal real-time model for the power system with the CAES facility, the thermal unit and the wind farm is proposed. The concerned dispatch problem is converted into its equivalent deterministic linear formulation and then is solved. Numerical simulation results indicate that the CAES participation in the real-time dispatch can mitigate the wind curtailment and reduce the thermal unit's and the whole system's operation costs and the system Automatic Generation Control (AGC) cost. The results also show that the ignorance of the part-load characteristics and the power regulation uncertainty can result in the infeasibility of real-time scheduling decisions.