DocumentCode :
1388123
Title :
Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems
Author :
Atwa, Yasser M. ; El-Saadany, Ehab F.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Volume :
5
Issue :
1
fYear :
2011
fDate :
1/1/2011 12:00:00 AM
Firstpage :
79
Lastpage :
88
Abstract :
Recent development in small renewable/clean generation technologies such as wind turbines, photovoltaic, fuel cells, microturbines and so on has drawn distribution utilities´ attention to possible changes in the distribution system infrastructure and policy by deploying distributed generation (DG) in distribution systems. In this study, a methodology has been proposed for optimally allocating wind-based DG units in the distribution system so as to minimise annual energy loss. The methodology is based on generating a probabilistic generation´load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer non-linear programming (MINLP), with an objective function for the system´s annual energy losses minimise. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units. This proposed technique is applied to a typical rural distribution system and compared to the traditional planning technique (constant output power of DG units and constant peak load profile).
Keywords :
distributed power generation; integer programming; nonlinear programming; power generation planning; probability; wind power plants; MINLP; deterministic planning problem; distribution systems; mixed integer non-linear programming; optimal allocation; probabilistic generation-load model; wind turbines; wind-based distributed generation;
fLanguage :
English
Journal_Title :
Renewable Power Generation, IET
Publisher :
iet
ISSN :
1752-1416
Type :
jour
DOI :
10.1049/iet-rpg.2009.0011
Filename :
5644824
Link To Document :
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