DocumentCode :
2314225
Title :
Unit Commitment under Wind Power and Demand Uncertainties
Author :
Pappala, V.S. ; Erlich, I. ; Singh, S.N.
Author_Institution :
Inst. of Electr. Power Syst., Univ. Duisburg-Essen, Duisburg
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
1
Lastpage :
6
Abstract :
This paper addresses a multistage stochastic model for the optimal operation of wind farm, pumped storage and thermal power plants. The output of the wind farm and the electrical demand are considered as two independent stochastic processes. The evolution of these processes over time is modeled as a scenario tree. Considering all possible realizations of stochastic process, leads to a huge set of scenarios. These scenarios are reduced by a particle swarm optimization based scenario reduction algorithm. The scenario tree modeling transforms the cost model to a stochastic model. The stochastic model can be used to estimate the operation costs of the hybrid system under the influence of the uncertainties. The stochastic model is solved using adaptive particle swarm optimization.
Keywords :
particle swarm optimisation; power generation planning; wind power; electrical demand uncertainties; multistage stochastic model; particle swarm optimization; pumped storage; scenario reduction algorithm; thermal power plants; unit commitment; wind farm; wind power; Costs; Power generation; Power system modeling; Power system planning; Stochastic processes; Uncertainty; Wind energy; Wind energy generation; Wind farms; Wind power generation; Economic Model; Evolutionary Programming; Multi-stage Scenario tree; Particle Swarm Optimization; Random Process; Stochastic Programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4244-1763-6
Electronic_ISBN :
978-1-4244-1762-9
Type :
conf
DOI :
10.1109/ICPST.2008.4745274
Filename :
4745274
Link To Document :
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