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Reliability constrained unit commitment with combined hydro and thermal generation embedded using self-learning group search optimizer

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  • Zheng, J.H.
  • Chen, J.J.
  • Wu, Q.H.
  • Jing, Z.X.

Abstract

This paper proposes a reliability constrained unit commitment problem with combined hydro and thermal generation embedded (RCHTUC), solved by a SLGSO (self-learning group search optimizer). The RCHTUC problem aims at minimizing the sum of fuel costs and start-up costs of thermal plants subject to various operation constraints. Furthermore, the problem takes into account the combination of hydro and thermal systems and the reliability constraints in hydrothermal power systems so as to respond to unforeseen outages and changes of load demands. In order to solve the RCHTUC problem, a SLGSO is developed from the GSO (group search optimizer), applying adaptive covariance matrix to design the optimum searching strategy and employing Lévy flights to increase the diversity of group. This paper reports on the simulation results obtained by the proposed method. The results are compared with those obtained by other methods on different hydrothermal systems over the scheduling horizon. The simulation results demonstrate the efficiency of the SLGSO for tackling the RCHTUC problem.

Suggested Citation

  • Zheng, J.H. & Chen, J.J. & Wu, Q.H. & Jing, Z.X., 2015. "Reliability constrained unit commitment with combined hydro and thermal generation embedded using self-learning group search optimizer," Energy, Elsevier, vol. 81(C), pages 245-254.
    • Handle: RePEc:eee:energy:v:81:y:2015:i:c:p:245-254
    DOI: 10.1016/j.energy.2014.12.036
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    3. Esmaeily, Ali & Ahmadi, Abdollah & Raeisi, Fatima & Ahmadi, Mohammad Reza & Esmaeel Nezhad, Ali & Janghorbani, Mohammadreza, 2017. "Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate," Energy, Elsevier, vol. 122(C), pages 182-193.
    4. Pérez-Díaz, Juan I. & Jiménez, Javier, 2016. "Contribution of a pumped-storage hydropower plant to reduce the scheduling costs of an isolated power system with high wind power penetration," Energy, Elsevier, vol. 109(C), pages 92-104.
    5. Zhang, Jingrui & Tang, Qinghui & Chen, Yalin & Lin, Shuang, 2016. "A hybrid particle swarm optimization with small population size to solve the optimal short-term hydro-thermal unit commitment problem," Energy, Elsevier, vol. 109(C), pages 765-780.
    6. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Quasi-oppositional turbulent water flow-based optimization for cascaded short term hydrothermal scheduling with valve-point effects and multiple fuels," Energy, Elsevier, vol. 251(C).
    7. Yin, Hao & Wu, Fei & Meng, Xin & Lin, Yicheng & Fan, Jingmin & Meng, Anbo, 2020. "Crisscross optimization based short-term hydrothermal generation scheduling with cascaded reservoirs," Energy, Elsevier, vol. 203(C).
    8. Tejada-Arango, Diego A. & Wogrin, Sonja & Siddiqui, Afzal S. & Centeno, Efraim, 2019. "Opportunity cost including short-term energy storage in hydrothermal dispatch models using a linked representative periods approach," Energy, Elsevier, vol. 188(C).
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