DocumentCode :
1579176
Title :
Fuzzy mixed integer programming: Approach to security-constrained unit commitment
Author :
Daneshi, H. ; Jahromi, A. Naderian ; Li, Z. ; Shahidehpour, M.
Author_Institution :
Electr. Power & Power Electron. Center, Illinois Inst. of Technol., Chicago, IL, USA
fYear :
2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a formulation of fuzzy mixed integer programming (FMIP) solution for solving security-constrained unit commitment (SCUC) problem with emphasis on uncertainties in forecasted parameters in constraints. The proposed approach could be used by vertically integrated utilities as well as the ISOs in restructured power system. In this model, uncertainties in forecasted load demand, ancillary services and wind power are simulated in a fuzzy frame. Problem is finding a solution which satisfies the constraints and the objective with the maximum degree. The objective function will optimize while constraints have varying degree. The proposed model can be solved using a standard mixed integer-programming (MIP) solver. Case studies with the eight-bus system are presented in detail in this paper. We study the impact of uncertainty in forecasted parameters in SCUC solution and compare the results with those of crisp SCUC model.
Keywords :
demand forecasting; electricity supply industry; integer programming; load forecasting; power generation dispatch; power generation scheduling; power system security; FMIP approach; eight-bus system; fuzzy mixed integer programming; load demand forecasting; power system utility; security-constrained unit commitment; Demand forecasting; Linear programming; Load forecasting; Power system modeling; Power system security; Power system simulation; Predictive models; Uncertainty; Wind energy; Wind forecasting; Security-constrained unit commitment (SCUC); fuzzy sets theory; mixed integer programming (MIP); restructured power markets;
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.2009.5275364
Filename :
5275364
Link To Document :
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