Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties
dc.contributor.author | Sedghi, M. | |
dc.contributor.author | Ahmadian, A. | |
dc.contributor.author | Pashajavid, Ehsan | |
dc.contributor.author | Aliakbar-Golkar, M. | |
dc.date.accessioned | 2018-12-13T09:13:51Z | |
dc.date.available | 2018-12-13T09:13:51Z | |
dc.date.created | 2018-12-12T02:46:58Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Sedghi, M. and Ahmadian, A. and Pashajavid, E. and Aliakbar-Golkar, M. 2015. Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties. Journal of Renewable and Sustainable Energy. 7 (3). | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/72569 | |
dc.identifier.doi | 10.1063/1.4922004 | |
dc.description.abstract |
© 2015 AIP Publishing LLC. The storage units decrease the operation cost of active distribution network considerably if they are managed optimally. In this paper, the short-term optimal scheduling of stationary batteries is presented. The point estimate method is used for considering uncertainty of load, wind-based distributed generation and plug-in electric vehicles as well as their influence on optimal scheduling. The optimal scheduling consists of minimizing cost objective function under technical constraints. In this paper, the cost objective function is composed of operation and reliability costs which are minimized using Tabu search algorithm. The storage units are used for several objectives, i.e., peak shaving, voltage regulation, and reliability enhancement. The numerical studies show the advantages of batteries for energy management in active distribution network, and the impact of uncertainties on optimal scheduling. | |
dc.publisher | American Institute of Physics | |
dc.title | Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties | |
dc.type | Journal Article | |
dcterms.source.volume | 7 | |
dcterms.source.number | 3 | |
dcterms.source.issn | 1941-7012 | |
dcterms.source.title | Journal of Renewable and Sustainable Energy | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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