UM
Sto2Auc: A Stochastic Optimal Bidding Strategy for Microgrids
An, Dou; Yang, Qingyu; Yu, Wei; Yang, Xinyu; Fu, Xinwen; Zhao, Wei
2017-12
Source PublicationIEEE INTERNET OF THINGS JOURNAL
ISSN2327-4662
Volume4Issue:6Pages:2260-2274
AbstractMicrogrids (MGs) have attracted growing attention due to self-sufficiency and self-healing properties. Nonetheless, the intermittent nature and uncertainty of distributed energy resources and load demands remain challenging issues in balancing demands and managing energy resources in MGs. Existing research efforts mainly focus on developing techniques to enable interactions between local MGs and the utility grid, which leads to high line power losses and operation costs. In this paper, we present the Sto2Auc framework to address the issue of stochastic optimal bidding problem for a system with MGs. First, the optimal bidding problem is formulated as a two-stage stochastic programming process, which aims to minimize the system operation cost and obtain optimal energy capacity of MGs by the MG center controller (MGCC). Uncertainties arise from both energy supply and demand, which are considered in the stochastic model, and random parameters representing those uncertainties are captured by using the Monte Carlo method. Second, to enable optimal electricity trading between the insufficient and surplus MGs, we propose a distributed double auction (DDA)-based scheme, which is proven to converge to the optimal social welfare of the system with MGs, and achieves the economical properties of being strategy-proof, individually rational, and (weak) budget balanced. Extensive experiments on an MG system composed of IEEE-33 buses demonstrate the effectiveness of proposed scheme. The experimental results show that Sto2Auc framework is capable of reducing the operational cost of MG systems, while the implemented DDA scheme achieves good performance with respect to social welfare, demand insufficiency, and MGCC profit.
KeywordDouble auction Internet of Things (IoT) applications microgrids (MGs) optimal biding stochastic programming uncertainties
DOI10.1109/JIOT.2017.2764879
URLView the original
Indexed BySCI ; SSCI
Language英语
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000418174100041
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:15   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
An, Dou,Yang, Qingyu,Yu, Wei,et al. Sto2Auc: A Stochastic Optimal Bidding Strategy for Microgrids[J]. IEEE INTERNET OF THINGS JOURNAL,2017,4(6):2260-2274.
APA An, Dou,Yang, Qingyu,Yu, Wei,Yang, Xinyu,Fu, Xinwen,&Zhao, Wei.(2017).Sto2Auc: A Stochastic Optimal Bidding Strategy for Microgrids.IEEE INTERNET OF THINGS JOURNAL,4(6),2260-2274.
MLA An, Dou,et al."Sto2Auc: A Stochastic Optimal Bidding Strategy for Microgrids".IEEE INTERNET OF THINGS JOURNAL 4.6(2017):2260-2274.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[An, Dou]'s Articles
[Yang, Qingyu]'s Articles
[Yu, Wei]'s Articles
Baidu academic
Similar articles in Baidu academic
[An, Dou]'s Articles
[Yang, Qingyu]'s Articles
[Yu, Wei]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[An, Dou]'s Articles
[Yang, Qingyu]'s Articles
[Yu, Wei]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.