IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v81y2015icp245-254.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214014030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2014.12.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    2. G. M. Viswanathan & Sergey V. Buldyrev & Shlomo Havlin & M. G. E. da Luz & E. P. Raposo & H. Eugene Stanley, 1999. "Optimizing the success of random searches," Nature, Nature, vol. 401(6756), pages 911-914, October.
    3. Soroudi, Alireza, 2013. "Robust optimization based self scheduling of hydro-thermal Genco in smart grids," Energy, Elsevier, vol. 61(C), pages 262-271.
    4. Partovi, Farzad & Nikzad, Mehdi & Mozafari, Babak & Ranjbar, Ali Mohamad, 2011. "A stochastic security approach to energy and spinning reserve scheduling considering demand response program," Energy, Elsevier, vol. 36(5), pages 3130-3137.
    5. Wang, Yongqiang & Zhou, Jianzhong & Mo, Li & Zhang, Rui & Zhang, Yongchuan, 2012. "Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm," Energy, Elsevier, vol. 44(1), pages 657-671.
    6. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "Reserve constrained dynamic optimal power flow subject to valve-point effects, prohibited zones and multi-fuel constraints," Energy, Elsevier, vol. 47(1), pages 451-464.
    7. Catalão, J.P.S. & Pousinho, H.M.I. & Contreras, J., 2012. "Optimal hydro scheduling and offering strategies considering price uncertainty and risk management," Energy, Elsevier, vol. 37(1), pages 237-244.
    8. Pérez-Díaz, J.I. & Millán, R. & García, D. & Guisández, I. & Wilhelmi, J.R., 2012. "Contribution of re-regulation reservoirs considering pumping capability to environmentally friendly hydropower operation," Energy, Elsevier, vol. 48(1), pages 144-152.
    9. Modiri-Delshad, Mostafa & Rahim, Nasrudin Abd, 2014. "Solving non-convex economic dispatch problem via backtracking search algorithm," Energy, Elsevier, vol. 77(C), pages 372-381.
    10. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Seifi, Alireza, 2013. "A new algorithm for combined heat and power dynamic economic dispatch considering valve-point effects," Energy, Elsevier, vol. 52(C), pages 320-332.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    2. Howlader, Harun Or Rashid & Matayoshi, Hidehito & Senjyu, Tomonobu, 2016. "Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid," Renewable Energy, Elsevier, vol. 99(C), pages 107-117.
    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).
    9. Chen, Fang & Zhou, Jianzhong & Wang, Chao & Li, Chunlong & Lu, Peng, 2017. "A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching," Energy, Elsevier, vol. 121(C), pages 276-291.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "The impact of storage facility capacity and ramping capabilities on the supply side economic dispatch of the energy–water nexus," Energy, Elsevier, vol. 66(C), pages 363-377.
    2. Hickman, William & Muzhikyan, Aramazd & Farid, Amro M., 2017. "The synergistic role of renewable energy integration into the unit commitment of the energy water nexus," Renewable Energy, Elsevier, vol. 108(C), pages 220-229.
    3. Soroudi, Alireza, 2013. "Robust optimization based self scheduling of hydro-thermal Genco in smart grids," Energy, Elsevier, vol. 61(C), pages 262-271.
    4. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "Real-time economic dispatch for the supply side of the energy-water nexus," Applied Energy, Elsevier, vol. 122(C), pages 42-52.
    5. Glotić, Arnel & Glotić, Adnan & Kitak, Peter & Pihler, Jože & Tičar, Igor, 2014. "Optimization of hydro energy storage plants by using differential evolution algorithm," Energy, Elsevier, vol. 77(C), pages 97-107.
    6. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    7. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
    8. Shukla, Anup & Singh, S.N., 2016. "Advanced three-stage pseudo-inspired weight-improved crazy particle swarm optimization for unit commitment problem," Energy, Elsevier, vol. 96(C), pages 23-36.
    9. Younes, Mimoun & Khodja, Fouad & Kherfane, Riad Lakhdar, 2014. "Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration," Energy, Elsevier, vol. 67(C), pages 595-606.
    10. Arul, R. & Velusami, S. & Ravi, G., 2015. "A new algorithm for combined dynamic economic emission dispatch with security constraints," Energy, Elsevier, vol. 79(C), pages 496-511.
    11. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Haghrah, A., 2017. "Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation," Energy, Elsevier, vol. 128(C), pages 77-85.
    12. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Azizipanah-Abarghooee, Rasoul, 2013. "An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties," Energy, Elsevier, vol. 50(C), pages 232-244.
    13. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    14. Sichilalu, Sam & Wamalwa, Fhazhil & Akinlabi, Esther T., 2019. "Optimal control of wind-hydrokinetic pumpback hydropower plant constrained with ecological water flows," Renewable Energy, Elsevier, vol. 138(C), pages 54-69.
    15. Razavi, Seyed-Ehsan & Esmaeel Nezhad, Ali & Mavalizadeh, Hani & Raeisi, Fatima & Ahmadi, Abdollah, 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework," Energy, Elsevier, vol. 165(PB), pages 593-602.
    16. Lin, Shin-Yeu & Chen, Jyun-Fu, 2013. "Distributed optimal power flow for smart grid transmission system with renewable energy sources," Energy, Elsevier, vol. 56(C), pages 184-192.
    17. Dai, Canyun & Hu, Zhongbo & Su, Qinghua, 2022. "An adaptive hybrid backtracking search optimization algorithm for dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 239(PE).
    18. Xiong, Guojiang & Shi, Dongyuan, 2018. "Hybrid biogeography-based optimization with brain storm optimization for non-convex dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 157(C), pages 424-435.
    19. Cheng, Chuntian & Li, Shushan & Li, Gang, 2014. "A hybrid method of incorporating extended priority list into equal incremental principle for energy-saving generation dispatch of thermal power systems," Energy, Elsevier, vol. 64(C), pages 688-696.
    20. Lin, Shin-Yeu & Lin, Ai-Chih, 2014. "RLOPF (risk-limiting optimal power flow) for systems with high penetration of wind power," Energy, Elsevier, vol. 71(C), pages 49-61.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:81:y:2015:i:c:p:245-254. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.