An Integrated Predictive Maintenance and Operations Scheduling Framework for Power Systems Under Failure Uncertainty

Published Online:https://doi.org/10.1287/ijoc.2022.0154

References

  • Abbasi E, Fotuhi-Firuzabad M, Abiri-Jahromi A (2009) Risk based maintenance optimization of overhead distribution networks utilizing priority based dynamic programming. Proc. IEEE Power Energy Soc. General Meeting (IEEE, Piscataway, NJ), 1–11.Google Scholar
  • Abiri-Jahromi A, Fotuhi-Firuzabad M, Abbasi E (2009) An efficient mixed-integer linear formulation for long-term overhead lines maintenance scheduling in power distribution systems. IEEE Trans. Power Delivery 24(4):2043–2053.CrossrefGoogle Scholar
  • Basciftci B, Ahmed S, Gebraeel NZ (2020) Data-driven maintenance and operations scheduling in power systems under decision-dependent uncertainty. IISE Trans. 52(6):589–602.CrossrefGoogle Scholar
  • Basciftci B, Ahmed S, Gebraeel NZ, Yildirim M (2018) Stochastic optimization of maintenance and operations schedules under unexpected failures. IEEE Trans. Power Systems 33(6):6755–6765.CrossrefGoogle Scholar
  • Bienstock D, Chertkov M, Harnett S (2014) Chance-constrained optimal power flow: Risk-aware network control under uncertainty. SIAM Rev. 56(3):461–495.CrossrefGoogle Scholar
  • Canto SP (2008) Application of benders’ decomposition to power plant preventive maintenance scheduling. Eur. J. Oper. Res. 184(2):759–777.CrossrefGoogle Scholar
  • Conejo A, Garcia-Bertrand R, Diaz-Salazar M (2005) Generation maintenance scheduling in restructured power systems. IEEE Trans. Power Systems 20(2):984–992.CrossrefGoogle Scholar
  • EIA (2020) Weekly electricity consumption from the U.S. Energy Information Administration. Accessed January 1, 2021. www.eia.gov/electricity/data/browser/.Google Scholar
  • Fisher EB, O’Neill RP, Ferris MC (2008) Optimal transmission switching. IEEE Trans. Power Systems 23(3):1346–1355.CrossrefGoogle Scholar
  • FRCC (2008) Florida Reliability Coordinating Council Inc system disturbance and underfrequency load shedding event. Report, FRCC Operating Committee, Tampa, FL.Google Scholar
  • Froger A, Gendreau M, Mendoza JE, Pinson E, Rousseau LM (2016) Maintenance scheduling in the electricity industry: A literature review. Eur. J. Oper. Res. 251(3):695–706.CrossrefGoogle Scholar
  • Fu Y, Shahidehpour M, Li Z (2007) Security-constrained optimal coordination of generation and transmission maintenance outage scheduling. IEEE Trans. Power Systems 22(3):1302–1313.CrossrefGoogle Scholar
  • Fu Y, Li Z, Shahidehpour M, Zheng T, Litvinov E (2009) Coordination of midterm outage scheduling with short-term security-constrained unit commitment. IEEE Trans. Power Systems 24(4):1818–1830.CrossrefGoogle Scholar
  • Gebraeel NZ, Lawley MA, Li R, Ryan JK (2005) Residual-life distributions from component degradation signals: A Bayesian approach. IIE Trans. 37(6):543–557.CrossrefGoogle Scholar
  • Geetha T, Swarup KS (2009) Coordinated preventive maintenance scheduling of genco and transco in restructured power systems. Internat. J. Electrical Power Energy Systems 31(10):626–638.CrossrefGoogle Scholar
  • Geng X, Xie L (2019) Data-driven decision making in power systems with probabilistic guarantees: Theory and applications of chance-constrained optimization. Annual Rev. Control 47:341–363.CrossrefGoogle Scholar
  • Hong Y (2013) On computing the distribution function for the Poisson binomial distribution. Comput. Statist. Data Anal. 59:41–51.CrossrefGoogle Scholar
  • IEA (2017) Digitalisation and Energy (International Energy Agency, Paris).Google Scholar
  • Laporte G, Louveaux FV (1993) The integer l-shaped method for stochastic integer programs with complete recourse. Oper. Res. Lett. 13(3):133–142.CrossrefGoogle Scholar
  • Lv C, Wang J, Sun P (2012) Short-term transmission maintenance scheduling based on the Benders decomposition. Proc. Asia-Pacific Power and Energy Engrg. Conf. (IEEE, Piscataway, NJ), 1–5.Google Scholar
  • Mak W, Morton D, Wood R (1999) Monte Carlo bounding techniques for determining solution quality in stochastic programs. Oper. Res. Lett. 24(1–2):47–56.CrossrefGoogle Scholar
  • Marwali M, Shahidehpour S (1998) Integrated generation and transmission maintenance scheduling with network constraints. IEEE Trans. Power Systems 13(3):1063–1068.CrossrefGoogle Scholar
  • Marwali M, Shahidehpour S (2000) Short-term transmission line maintenance scheduling in a deregulated system. IEEE Trans. Power Systems 15(3):1117–1124.CrossrefGoogle Scholar
  • O’Neill RP, Hedman KW, Krall EA, Papavasiliou A, Oren SS (2010) Economic analysis of the N-1 reliable unit commitment and transmission switching problem using duality concepts. Energy Systems 1(2):165–195.CrossrefGoogle Scholar
  • Ozturk U, Mazumdar M, Norman B (2004) A solution to the stochastic unit commitment problem using chance constrained programming. IEEE Trans. Power Systems 19(3):1589–1598.CrossrefGoogle Scholar
  • Pandzic H, Conejo AJ, Kuzle I, Caro E (2012) Yearly maintenance scheduling of transmission lines within a market environment. IEEE Trans. Power Systems 27(1):407–415.CrossrefGoogle Scholar
  • Papavasiliou A, Oren SS (2013) Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network. Oper. Res. 61(3):578–592.LinkGoogle Scholar
  • Papavasiliou A, Oren SS, Rountree B (2015) Applying high performance computing to transmission-constrained stochastic unit commitment for renewable energy integration. IEEE Trans. Power Systems 30(3):1109–1120.CrossrefGoogle Scholar
  • PyPI (2020) Poisson binomial package. Accessed January 1, 2021, https://pypi.org/project/poisson-binomial/.Google Scholar
  • Shahidehpour M, Yamin H, Li Z (2002) Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management (Institute of Electrical and Electronics Engineers, Wiley-Interscience, New York).CrossrefGoogle Scholar
  • Stott B, Alsac O, Monticelli A (1987) Security analysis and optimization. Proc. IEEE 75(12):1623–1644.CrossrefGoogle Scholar
  • Wang Y, Zhong H, Xia Q, Kirschen DS, Kang C (2016b) An approach for integrated generation and transmission maintenance scheduling considering N-1 contingencies. IEEE Trans. Power Systems 31(3):2225–2233.CrossrefGoogle Scholar
  • Wang Y, Li Z, Shahidehpour M, Wu L, Guo CX, Zhu B (2016a) Stochastic co-optimization of midterm and short-term maintenance outage scheduling considering covariates in power systems. IEEE Trans. Power Systems 31(6):4795–4805.CrossrefGoogle Scholar
  • Wu HH, Küçükyavuz S (2019) Probabilistic partial set covering with an oracle for chance constraints. SIAM J. Optim. 29(1):690–718.CrossrefGoogle Scholar
  • Wu L, Shahidehpour M, Fu Y (2010) Security-constrained generation and transmission outage scheduling with uncertainties. IEEE Trans. Power Systems 25(3):1674–1685.CrossrefGoogle Scholar
  • Wu L, Shahidehpour M, Li T (2008) Genco’s risk-based maintenance outage scheduling. IEEE Trans. Power Systems 23(1):127–136.CrossrefGoogle Scholar
  • Xiong P, Jirutitijaroen P (2013) A stochastic optimization formulation of unit commitment with reliability constraints. IEEE Trans. Smart Grid 4(4):2200–2208.CrossrefGoogle Scholar
  • Yildirim M, Sun XA, Gebraeel NZ (2016a) Sensor-driven condition-based generator maintenance scheduling—Part I: Maintenance problem. IEEE Trans. Power Systems 31(6):4253–4262.CrossrefGoogle Scholar
  • Yildirim M, Sun XA, Gebraeel NZ (2016b) Sensor-driven condition-based generator maintenance scheduling—Part II: Incorporating operations. IEEE Trans. Power Systems 31(6):4263–4271.CrossrefGoogle Scholar
  • Zimmerman RD, Murillo-Sánchez CE, Thomas RJ (2011) Matpower: Steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Systems 26(1):12–19.CrossrefGoogle Scholar
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