Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPWRS.2012.2222939
Title: Evolutionary multi-objective day-ahead thermal generation scheduling in uncertain environment
Authors: Trivedi, A. 
Srinivasan, D. 
Sharma, D.
Singh, C.
Keywords: Evolutionary multi-objective optimization
Thermal generation scheduling
Uncertainty
Unit commitment
Issue Date: 2013
Source: Trivedi, A., Srinivasan, D., Sharma, D., Singh, C. (2013). Evolutionary multi-objective day-ahead thermal generation scheduling in uncertain environment. IEEE Transactions on Power Systems 28 (2) : 1345-1354. ScholarBank@NUS Repository. https://doi.org/10.1109/TPWRS.2012.2222939
Abstract: This paper addresses day-ahead thermal generation scheduling as a realistic multi-objective optimization problem in an uncertain environment considering system operation cost, emission cost and reliability as the multiple objectives. The uncertainties occurring due to unit outage and load forecast error are incorporated using loss of load probability (LOLP) and expected unserved energy (EUE) reliability indices. For solving the above-mentioned scheduling problem, a multi-objective generation scheduling algorithm (MOGSA) is proposed in this paper. Three case studies are performed on large scale test systems considering two different bi-objective optimization models and a three-objective optimization model that may be chosen by the system operator according to his/her own preference. The simulation results demonstrate the advantages of solving the thermal generation scheduling problem as a realistic multi-objective optimization problem in an uncertain environment. Finally the authors suggest a systematic procedure for the system operators to choose a single solution for the thermal generation scheduling problem. © 2012 IEEE.
Source Title: IEEE Transactions on Power Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/55931
ISSN: 08858950
DOI: 10.1109/TPWRS.2012.2222939
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