Page 402 - Decision Making Applications in Modern Power Systems
P. 402

364  Decision Making Applications in Modern Power Systems


            Acknowledgment
            The authors gratefully acknowledge the support of this research by FAPEAM, UFPA,
            ELETROBRAS, and ITEGAM.

            References
             [1] S.G. Silva, Sistema interligado nacional: An´ alise das penalizac¸o ˜es impostas a `s transmis-
                soras com foco na aplicac¸a ˜o da parcela vari´ avel. 2016.
             [2] M.A. Haiping, et al., Multi-objective biogeography-based optimization for dynamic eco-
                nomic emission load dispatch considering plug-in electric vehicles charging, Energy 135
                (2017) 101 111. ISSN 0360-5442.
             [3] J. Pless, H. Fell, Bribes, bureaucracies, and blackouts: towards understanding how corrup-
                tion at the firm level impacts electricity reliability, Res. Energy Econ. 47 (2017) 36 55.
                ISSN 0928-7655.
             [4] N. Kumar, A non convex cost function based optimal load dispatch using tlbo algorithm,
                J. Eng. Sci. Technol. Rev. 10 (1) (2017) 155 159. ISSN 1791-2377.
             [5] N. Alam, M.F. Karim, S.A. Islam, A.N. Ahsan, A 0/1 mixed integer linear programming
                approach to establish an effective preventive maintenance policy for power plant, Int. J.
                Ind. Syst. Eng. 25 (4) (2017) 478 498.
             [6] S. Alaswad, Y. Xiang, A review on condition-based maintenance optimization models for
                stochastically deteriorating system, Reliab. Eng. Syst. Saf. 157 (2017) 54 63.
             [7] R. Arya, Ranking of feeder sections of distribution systems for maintenance prioritization
                accounting distributed generations and loads using diagnostic importance factor (DIF), Int.
                J. Electr. Power Energy Syst. 74 (2016) 70 77.
             [8] A. Azadeh, S.M. Asadzadeh, N. Salehi, M. Firoozi, Condition-based maintenance effec-
                tiveness for series parallel power generation system—a combined Markovian simulation
                model, Reliab. Eng. Syst. Saf. 142 (2015) 357 368.
             [9] R. Baidya, S.K. Ghosh, Model for a predictive maintenance system effectiveness using
                the analytical hierarchy process as analytical tool, IFAC-PapersOnLine 48 (3) (2015)
                1463 1468.
            [10] M. Fonseca, et al., Pre-dispatch of Load in Thermoelectric Power Plants Considering
                Maintenance Management Using Fuzzy Logic, IEEE Access, 2018.
            [11] M. Fonseca Junior, et al., Maintenance tools applied to electric generators to improve
                energy efficiency and power quality of thermoelectric power plants, Energies 10 (8)
                (2017) 1091.
            [12] S. Larguech, et al., Fuzzy sliding mode control for turbocharged diesel engine, J. Dyn.
                Syst. Meas. Contr. 138 (1) (2016) 011009. ISSN 0022-0434.
                       ¸
            [13] B.P. Goncalves, et al., Avaliac¸a ˜o de impactos harmo ˆnicos na rede ele ´trica atrave ´s dos
                 indicadores THD e fator de pote ˆncia utilizando lo ´gica Fuzzy, Rev. Bras Energ. 19 (1)
                 (2013) 9 27.
            [14] E.L. Nogueira, M.H.R. Nascimento, Inventory control applying sales demand prevision
                based on fuzzy inference system, J. Eng. Technol. Ind. Appl. 3 (2017) 31 36. ,https://
                doi.org/10.5935/2447-0228.20170060..
            [15] D. Lopez-Perez, J. Antonino-Daviu, Application of infrared thermography to failure detec-
                tion in industrial induction motors: case stories, IEEE Trans. Ind. Appl. 53 (3) (2017)
                1901 1908. ISSN 0093-9994.
   397   398   399   400   401   402   403   404   405   406   407