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Optimization of Hedging Rules for Reservoir Operation During Droughts Based on Particle Swarm Optimization

Author

Listed:
  • Mike Spiliotis

    (Democritus University of Thrace)

  • Luis Mediero

    (Technical University of Madrid)

  • Luis Garrote

    (Technical University of Madrid)

Abstract

This paper presents a methodology to achieve the identification of optimal hedging rules for operating reservoir systems, seeking to mitigate the drought impacts. The heuristic Particle Swarm Optimization (PSO) method is adopted as the optimization solver. This procedure establishes a two-phase method that combines PSO with the simulation of the water system, representing a system of reservoirs that are jointly operated to satisfy a set of demands with different priorities. The hedging rules are based on monthly storage levels that trigger restrictions on the demands. As model parameters, monthly rule activation thresholds and rationing factors were used for each type of demand. The optimization procedure minimizes an objective function that penalizes large deficits and assigns different weights to different demand types. Since the whole problem is quite complex, its dimensionality is reduced through: i) a set of candidate monthly activation thresholds are selected a priori associated to given risk conditions; and ii) the rationing factors are defined for every demand of each threshold throughout all months. In addition, an effort is made to avoid the trap in local optimums, whilst several other comments considering the application of the PSO method in the examined applications are provided. The procedure has been successfully applied to four water resource systems in Spain. From the application it can be seen that the deficits of the water supply demand are nearly removed, thanks to the larger weight given to the deficits of this demand type. The irrigation deficits are also reduced, since we lead to a sequence of smaller shortages than only one potential catastrophic shortage.

Suggested Citation

  • Mike Spiliotis & Luis Mediero & Luis Garrote, 2016. "Optimization of Hedging Rules for Reservoir Operation During Droughts Based on Particle Swarm Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5759-5778, December.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:15:d:10.1007_s11269-016-1285-y
    DOI: 10.1007/s11269-016-1285-y
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    References listed on IDEAS

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    2. Thibaut Cuvelier & Pierre Archambeau & Benjamin Dewals & Quentin Louveaux, 2018. "Comparison Between Robust and Stochastic Optimisation for Long-term Reservoir Management Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1599-1614, March.
    3. Beshavard, Mahdi & Adib, Arash & Ashrafi, Seyed Mohammad & Kisi, Ozgur, 2022. "Establishing effective warning storage to derive optimal reservoir operation policy based on the drought condition," Agricultural Water Management, Elsevier, vol. 274(C).
    4. Mike Spiliotis & Alvaro Sordo-Ward & Luis Garrote, 2021. "Estimation of Fuzzy Parameters in the Linear Muskingum Model with the Aid of Particle Swarm Optimization," Sustainability, MDPI, vol. 13(13), pages 1-26, June.
    5. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    6. Javad Jamshidi & Mojtaba Shourian, 2019. "Hedging Rules-Based Optimal Reservoir Operation Using Bat Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4525-4538, October.
    7. Mohammad Ehteram & Ali Najah Ahmed & Ming Fai Chow & Sarmad Dashti Latif & Kwok-wing Chau & Kai Lun Chong & Ahmed El-Shafie, 2023. "Optimal operation of hydropower reservoirs under climate change," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10627-10659, October.
    8. Luis Garrote, 2017. "Managing Water Resources to Adapt to Climate Change: Facing Uncertainty and Scarcity in a Changing Context," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2951-2963, August.
    9. Luis Garrote & Alfredo Granados & Mike Spiliotis & Francisco Martin-Carrasco, 2023. "Effectiveness of Adaptive Operating Rules for Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2527-2542, May.
    10. Inkyung Min & Nakyung Lee & Sanha Kim & Yelim Bang & Juyeon Jang & Kichul Jung & Daeryong Park, 2024. "An Improved Aggregation–Decomposition Optimization Approach for Ecological Flow Supply in Parallel Reservoir Systems," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
    11. Gokmen Tayfur & Bihrat Onoz & Antonino Cancelliere & Luis Garrote, 2016. "Editorial: Water Resources Management in a Changing World: Challenges and Opportunities," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5553-5557, December.

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