An optimized scheduling strategy combining robust optimization and rolling optimization to solve the uncertainty of RES-CCHP MG

A Novel Data-Driven Tighten-Constraint Method for Wind-Hydro Hybrid Power System to Improve Day-Ahead Plan Performance in Real-Time Operation

“…Ref. [30] proposes a multi-time scale optimal dispatch strategy combining robust optimization and rolling optimization for the combined cooling, heating and power microgrid containing renewable energy sources, and the effectiveness of the proposed model is showcased by comparing the operation cost in day-ahead plan and actual historical operation data. Even though the effectiveness of these proposed models is verified in actual operation level, these methods cannot be used to evaluate the day-ahead plan for the WHHPS that is going to be used in the coming real-time operation, in other words, these historical actual operation data comes from the plan made in advance and there is no way to gauge the performance of the day-ahead plan until it is executed in real-time operation.…”

Ultra-short-term PV power prediction based on Informer with multi-head probability sparse self-attentiveness mechanism

“…Although distributed photovoltaic power generation has many advantages, such as clean, green, low-carbon and flexible, it also has intermittent limitations that constrain its large-scale grid-connected power generation (Sabo et al, 2017;Xu et al, 2018). Therefore, accurate prediction of photovoltaic power generation is of great significance in alleviating the energy crisis, optimizing power dispatch and other aspects, which can improve the efficiency of photovoltaic power generation, maintain the stability of the power grid, alleviate the energy crisis and ensure the national energy security (Yang et al, 2023).…”