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https://doi.org/10.17559/TV-20151021201400

A probabilistic demand side management approach by consumption admission control

Lorant Kovacs ; Kecskemet College, Faculty of Mechanical Engineering and Automation (GAMF), Izsaki ut 10, Kecskemet, H-6000, Hungary
Rajmund Drenyovszki ; Kecskemet College, Faculty of Mechanical Engineering and Automation (GAMF), Izsaki ut 10, Kecskemet, H-6000, Hungary
Andras Olah ; Pázmány Péter Catholic University, Faculty of Information Technology, Práter utca 50/a, H-1083 Budapest, Hungary
Janos Levendovszky ; Budapest University of Technology and Economics, Deptartment of Telecommunications, Egry József u. 18, H-1111 Budapest, Hungary
Kalman Tornai orcid id orcid.org/0000-0003-1852-0816 ; Pázmány Péter Catholic University, Faculty of Information Technology, Práter utca 50/a, H-1083 Budapest, Hungary
Istvan Pinter ; Kecskemet College, Faculty of Mechanical Engineering and Automation (GAMF), Izsaki ut 10, Kecskemet, H-6000, Hungary


Puni tekst: engleski pdf 686 Kb

str. 199-207

preuzimanja: 622

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Puni tekst: hrvatski pdf 686 Kb

str. 199-207

preuzimanja: 419

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Sažetak

New generation electricity network called Smart Grid is a recently conceived vision for a cleaner, more efficient and cheaper electricity system. One of the major challenges of electricity network is that generation and consumption should be balanced at every moment. This paper introduces a new concept for controlling the demand side by the means of automatically enabling/disabling electric appliances to make sure that the demand is in match with the available supplies, based on the statistical characterization of the need. In our new approach instead of using hard limits we estimate the tail probability of the demand distribution and control system by using the principles and the results of statistical resource management.

Ključne riječi

admission control; Demand Side Management; Smart Grid

Hrčak ID:

174717

URI

https://hrcak.srce.hr/174717

Datum izdavanja:

10.2.2017.

Podaci na drugim jezicima: hrvatski

Posjeta: 2.438 *