DocumentCode :
3600632
Title :
Load Modeling For Power System Requirement and Capability Assessment
Author :
Orji, Uzoma ; Sievenpiper, Bartholomew ; Gerhard, Katherine ; Leeb, Steven B. ; Doerry, Norbert ; Kirtley, James L. ; McCoy, Timothy
Author_Institution :
Electr. Eng. & Comput. Sci. Dept., Massachusetts Inst. of Technol., Cambridge, MA, USA
Volume :
30
Issue :
3
fYear :
2015
fDate :
5/1/2015 12:00:00 AM
Firstpage :
1415
Lastpage :
1423
Abstract :
Load modeling is essential for designing and operating power systems. This paper presents an approach for load modeling on smaller power systems that could be “islanded,” an approach that preserves the detail of a full differential equation simulation of relevant loads while requiring far less computation by employing behavioral models of important loads. Mixed domain models, e.g., stochastic, finite-state machine, and differential equation models, are employed to provide accuracy in a computationally tractable framework. Where simple load models may not be adequate, particularly for generation-constrained systems (in a paper by Sotiropoulos et al.), and full models are computationally unfavorable, this approach provides excellent results that enable “what-if” studies and flexible re-evaluation during power system design and operational assessment. Naval vessels, particularly warships with relatively large and increasing load power requirements, offer a unique laboratory for understanding isolated power grids. This paper examines the DDG-51 power distribution system as an example.
Keywords :
differential equations; distribution networks; finite state machines; stochastic processes; DDG-51 power distribution system; capability assessment; differential equation model; finite-state machine model; full differential equation simulation; generation-constrained system; isolated power grids; load modeling; mixed domain model; operational assessment; power system design; power system requirement; stochastic model; Computational modeling; Load modeling; Marine vehicles; Mathematical model; Object oriented modeling; Power systems; Stochastic processes; Microgrids; power system dynamics; power systems analysis and computing; power systems planning; simulation;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2348531
Filename :
6884866
Link To Document :
بازگشت