DocumentCode :
1595935
Title :
Fuzzy milp unit commitment incorporating wind generators
Author :
Venkatesh, Bala ; Yu, Peng ; Choling, Dechen ; Gooi, H.B.
Author_Institution :
Ryerson Univ., Toronto, ON, Canada
fYear :
2009
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. Day-ahead unit commitment (UC) solution methods seek to determine the status and output of all available generators. In a world with an increasing integration of renewable energy sources such as wind electric generators (WEG), the UC solution process must model and include WEGs too in the decision making process. Power output of WEGs in a day-ahead decision making process are usually modeled using a short term probabilistic forecast. Inclusion of WEGs introduces uncertainty in the solution that may be quantified through an imbalance risk function. Thus a UC solution method should seek a solution to minimize cost and risk in schedule. Two strategies are proposed in this paper to minimize costs and handle risks introduced due to WEGs. These formulations are posed as fuzzy optimization models and are solved using the MILP (mixed integer linear programming) technique. The proposed strategies are tested on a 26 and a 100-generator systems with associated transmission networks that have 3 and 6 wind generators each. The results with two strategies of handling WEGs are discussed.
Keywords :
AC generators; decision making; fuzzy set theory; integer programming; linear programming; power generation economics; power generation scheduling; wind power plants; associated transmission networks; day-ahead unit commitment solution methods; decision making process; fuzzy MILP unit commitment; fuzzy optimization models; imbalance risk function; mixed integer linear programming technique; renewable energy sources; short term probabilistic forecasting; wind electric generators; Costs; Decision making; Generators; Mixed integer linear programming; Predictive models; Renewable energy resources; System testing; Uncertainty; Wind energy generation; Wind forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power & Energy Society General Meeting, 2009. PES '09. IEEE
Conference_Location :
Calgary, AB
ISSN :
1944-9925
Print_ISBN :
978-1-4244-4241-6
Type :
conf
DOI :
10.1109/PES.2009.5275948
Filename :
5275948
Link To Document :
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