DocumentCode :
735565
Title :
Hybrid stochastic/deterministic unit commitment with wind power generation
Author :
Wen-Shan Tan ; Shaaban, Mohamed
Author_Institution :
Centre of Electr. Energy Syst. (CEES), Univ. Teknol. Malaysia (UTM), Johor Bahru, Malaysia
fYear :
2015
fDate :
June 29 2015-July 2 2015
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a hybrid stochastic and deterministic unit commitment (SDUC) algorithm which takes into account the variability of wind generation. The proposed scheme is modeled as a chance constrained optimization, where the system ramping capability, required to meet changes in demand and variable generation, is also considered. The dayahead predicted net load probability density function (PDF) is modeled including wind curtailment effect. The PDF is then used to define the chance-constraint. The proposed UC is then linearized to maintain the mixed-integer linear structure of the problem such that, it can be solved by highly efficient commercially available solvers. Numerical simulations indicate the effectiveness of the developed hybrid SDUC formulation, including high penetration of wind power, and underline the competitive features of the proposed solution approaches.
Keywords :
demand side management; integer programming; linear programming; numerical analysis; power generation dispatch; power generation scheduling; stochastic processes; stochastic programming; wind power; chance constrained optimization; day-ahead predicted net load PDF; day-ahead predicted net load probability density function; demand and variable generation; hybrid SDUC algorithm; hybrid stochastic and deterministic unit commitment algorithm; mixed integer linear structure problem; numerical simulation; system ramping capability; wind curtailment effect; wind power generation; Computational modeling; Linear programming; Load modeling; Optimization; Probability density function; Stochastic processes; Wind power generation; Mixed-integer linear programming; chancedconstrained optimization; unit commitment; wind power generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2015 IEEE Eindhoven
Conference_Location :
Eindhoven
Type :
conf
DOI :
10.1109/PTC.2015.7232351
Filename :
7232351
Link To Document :
بازگشت