CRSO approach for microgrid power dispatching. Issue 11 (16th April 2019)

• Record Type: Journal Article
• Authors: Qiu, Haifeng; Gu, Wei; Li, Peng; Zhang, Xuesong; Long, Huan; Wu, Zhi
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 11(2019)
• Page Start: 2208
• Page End: 2215
• Publication Date: 2019-04-16
• Subjects: renewable energy sources -- optimisation -- integer programming -- distributed power generation -- stochastic programming; CRSO approach -- microgrid power dispatching -- dynamic power fluctuations -- loads -- variations -- renewable energy sources -- traditional robust optimisation -- two‐stage -- mixed integer recourse -- islanded hybrid AC/DC microgrid -- CRSO model -- source–load power -- bidirectional converter overhauling -- stochastic source–load uncertainty sets -- developed dispatching model; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6889
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : The optimal dispatch of microgrids is greatly challenged by various uncertainties, introduced by dynamic power fluctuations in loads and variations in renewable energy sources. To depress the over‐conservativeness of traditional robust optimisation, this study puts forward a two‐stage coupled robust and stochastic optimal (CRSO) dispatching model with mixed integer recourse for the islanded hybrid AC/DC microgrid. The CRSO model comprehensively considers the uncertainties in source–load power and bidirectional converter overhauling, and the stochastic source–load uncertainty sets are constructed by interval partitioning methods. The CRSO model optimises the binary states of the diesel generator and the bidirectional converter in the first stage, and the second stage obtains the flexible operating states and power of each unit. The daily worst‐case operation cost is minimised by the nested column‐and‐constraint generation algorithm. Numerical simulations have validated the rationality and superiority of the developed dispatching model and its solution method.