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.
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Research Article|
June 02 2015
Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties
M. Sedghi;
M. Sedghi
a)
Faculty of Electrical Engineering,
K. N. Toosi University of Technology
, P.O. Box 16315-1355, Tehran, Iran
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A. Ahmadian;
A. Ahmadian
Faculty of Electrical Engineering,
K. N. Toosi University of Technology
, P.O. Box 16315-1355, Tehran, Iran
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E. Pashajavid;
E. Pashajavid
Faculty of Electrical Engineering,
K. N. Toosi University of Technology
, P.O. Box 16315-1355, Tehran, Iran
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M. Aliakbar-Golkar
M. Aliakbar-Golkar
Faculty of Electrical Engineering,
K. N. Toosi University of Technology
, P.O. Box 16315-1355, Tehran, Iran
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a)
Author to whom correspondence should be addressed. Fax: +98 21 88462066. Electronic mail: [email protected].
J. Renewable Sustainable Energy 7, 033120 (2015)
Article history
Received:
July 29 2014
Accepted:
May 21 2015
Citation
M. Sedghi, A. Ahmadian, E. Pashajavid, M. Aliakbar-Golkar; Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties. J. Renewable Sustainable Energy 1 May 2015; 7 (3): 033120. https://doi.org/10.1063/1.4922004
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