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A hybrid particle swarm optimization with small population size to solve the optimal short-term hydro-thermal unit commitment problem

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  • Zhang, Jingrui
  • Tang, Qinghui
  • Chen, Yalin
  • Lin, Shuang

Abstract

Hydro-thermal unit commitment (HTUC) is an extension of unit commitment (UC) problems. The hydro-thermal unit commitment problem considered in this study aims at minimizing the total fuel cost of thermal units while satisfying the constraints of spinning reserve, minimum online/offline, ramp rate, hydraulic networks, etc. A hybrid particle swarm optimization approach with small population size (HPSO-SP) is presented for solving the optimal short-term HTUC problem. In the proposed approach, three extra handling operations, i.e. mutation, DE-acceleration, and migration have been proposed for both binary and continuous variables to ensure the effects of small population. A repair strategy to the main equality and inequality constraints has also been employed to improve the searching efficiency of the algorithm. Several well-known UC test systems in literature are considered to test the proposed HPSO-SP approach first. After verification on UC problems, this approach is applied to solve several HTUC test systems and a practical hydro-thermal system in China. The final results show the feasibility and effectiveness of the HPSO-SP approach.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:109:y:2016:i:c:p:765-780
    DOI: 10.1016/j.energy.2016.05.057
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    1. Rajesh, K. & Bhuvanesh, A. & Kannan, S. & Thangaraj, C., 2016. "Least cost generation expansion planning with solar power plant using Differential Evolution algorithm," Renewable Energy, Elsevier, vol. 85(C), pages 677-686.
    2. Yanık, Seda & Sürer, Özge & Öztayşi, Başar, 2016. "Designing sustainable energy regions using genetic algorithms and location-allocation approach," Energy, Elsevier, vol. 97(C), pages 161-172.
    3. Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
    4. 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.
    5. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    6. 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.
    7. 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.
    8. Madzharov, D. & Delarue, E. & D'haeseleer, W., 2014. "Integrating electric vehicles as flexible load in unit commitment modeling," Energy, Elsevier, vol. 65(C), pages 285-294.
    9. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    10. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    11. Neves, Diana & Silva, Carlos A., 2015. "Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms," Energy, Elsevier, vol. 82(C), pages 436-445.
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    11. Baghaee, H.R. & Mirsalim, M. & Gharehpetian, G.B. & Talebi, H.A., 2016. "Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system," Energy, Elsevier, vol. 115(P1), pages 1022-1041.
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    14. Feng, Zhong-kai & Niu, Wen-jing & Wang, Sen & Cheng, Chun-tian & Jiang, Zhi-qiang & Qin, Hui & Liu, Yi, 2018. "Developing a successive linear programming model for head-sensitive hydropower system operation considering power shortage aspect," Energy, Elsevier, vol. 155(C), pages 252-261.
    15. Zhang, Jingrui & Lin, Shuang & Liu, Houde & Chen, Yalin & Zhu, Mingcheng & Xu, Yinliang, 2017. "A small-population based parallel differential evolution algorithm for short-term hydrothermal scheduling problem considering power flow constraints," Energy, Elsevier, vol. 123(C), pages 538-554.
    16. Liu Yang & Kan Yang & Lei Chen, 2018. "Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2437-2456, May.
    17. Md. Arif Hossain & Ashik Ahmed & Shafiqur Rahman Tito & Razzaqul Ahshan & Taiyeb Hasan Sakib & Sarvar Hussain Nengroo, 2022. "Multi-Objective Hybrid Optimization for Optimal Sizing of a Hybrid Renewable Power System for Home Applications," Energies, MDPI, vol. 16(1), pages 1-19, December.
    18. 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.
    19. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Wu, Xin-yu, 2017. "Optimization of hydropower system operation by uniform dynamic programming for dimensionality reduction," Energy, Elsevier, vol. 134(C), pages 718-730.

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