Open AccessResearch on optimal self‐scheduling horizon for the wind power and large‐scale CAES combined system
Author(s) -
Li Yaowang,
Miao Shihong,
Yin Binxin,
Liu Junyao,
Yang Weichen,
Zhang Songyan
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.7081
Subject(s) - scheduling (production processes) , mathematical optimization , time horizon , profit (economics) , schedule , computer science , compressed air energy storage , fair share scheduling , dynamic priority scheduling , engineering , energy storage , mathematics , power (physics) , economics , physics , quantum mechanics , operating system , microeconomics
The self‐scheduling horizon is an important schedule parameter in the self‐scheduling problem. A more reasonable self‐scheduling horizon can lead to higher benefits of the wind farm (WF) and large‐scale compressed air energy storage (CAES) combined system. However, very few studies have been reported about the optimisation of self‐scheduling horizon for a WF paired with a CAES plant. In this study, a rolling day‐ahead self‐scheduling framework for a WF and CAES combined system is first proposed. After that, the self‐scheduling horizon optimisation model is developed in the formulation of a bilayer stochastic chance‐constrained optimisation problem. The proposed model is converted into its equivalent deterministic linear formulation and then is solved. Based on the developed model, the impacts of self‐scheduling horizon on the profit of the combined system are analysed. Numerical simulation results indicate that the profit of the combined system increases after using the optimal self‐scheduling horizon, and the profit increment is more obvious with the increase of the CAES's energy storage capacity.