Open AccessResearch on optimal scheduling decision of multi‐microgrids based on cloud energy storage
Author(s) -
Wang Yujie,
Yang Junjie,
Jiang Wei,
Sui Zhicheng,
Chen Ting
Publication year - 2021
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12362
Subject(s) - microgrid , energy storage , cloud computing , computer science , renewable energy , scheduling (production processes) , smart grid , distributed computing , electricity , grid , wind power , intermittent energy source , distributed generation , engineering , power (physics) , electrical engineering , operations management , operating system , physics , geometry , mathematics , quantum mechanics
Abstract In microgrids, energy storage systems (ESS) can mitigate the intermittency and uncertainty associated with large amounts of renewable energy connected to the grid. Cloud energy storage (CES) is a solution proposed by scholars over the last two years. It provides energy storage and trading services that can alleviate high investment costs and small‐scale wind and light abandonment problems. However, large‐scale energy mutualisation and fine scheduling of energy become significant challenges for further development. This study proposes a CES scheduling architecture based on multi‐microgrids. CES extends the scope of power trading from a single microgrid to multi‐microgrids, with the microgrid capable of interacting with neighbouring microgrids for power and reducing the transmission pressure on the larger grid. In addition, this study defines the game strategy for power trading between cloud storage operators, considering the reduction in electricity costs due to dishonest behaviour by users. The simulation results indicate that the proposed dispatching architecture and strategy can effectively improve the consumption rate of new energy sources, mitigate grid fluctuations, and further reduce electricity costs for users while also being resilient to dishonest user behaviour.