Application of a New Gorilla Troops Optimization Algorithm for Reservoir Operation Management

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

2 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

Abstract

In this paper, the artificial gorilla troops (GTO) optimizer algorithm with the gray wolf optimizer (GWO) and particle swarm optimization (PSO) algorithms was compared for optimal operation of dam reservoir. The results of the GTO were evaluated with GWO and PSO results which are successful in complex engineering issues and reservoir operation. The objective function of minimizing the total squares of the downstream demand deficit was defined during the operation period. The constraints of the operating equation include the reservoir continuity equation, the reservoir volume, and the release volume. A case study of Jamishan reservoir dam located in Kermanshah province was considered. In this regard, runoff values related to the statistical years 1991-2011 were introduced as input to the reservoir for optimal operation management. The obtained results from optimization algorithms using error estimation indices including mean square root of error (RMSE), mean absolute value of error (MAE), Nash-Sutcliffe criterion (NSE), ratio of root mean square error to standard deviation of observational data (RSR), Reliability, Resiliency, Vulnerability And the minimization values of the objective function were evaluated. The values of these indicators for GTO were 2.86, 1.85, 0.73, 0.52, 69%, 36%, 23% and 4.7, respectively. The results showed that the GTO algorithm had very good accuracy in minimizing the objective function and based on the values of proposed indicators performed better than the GWO and PSO algorithms. Based on this algorithm, the amount of water release volume was brought to the reservoir as a function of the reservoir volume and the amount of water demand volume for the months of the year was determined.

Keywords

References

Abdollahzadeh, B., Soleimanian Gharehchopogh, F., & Mirjalili, S. (2021). Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems. International Journal of Intelligent Systems, 36(10), 5887-5958.
Afshar, M. (2012). Large scale reservoir operation by constrained particle swarm optimization algorithms. Journal of Hydro-Environment Research, 6(1), 75-87.
Ahmadi, A., Han, D., Kakaei Lafdani, E., & Moridi, A. (2015). Input selection for long-lead precipitation prediction using large-scale climate variables: a case study. Journal of Hydroinformatics, 17(1), 114-129.
Ahmadianfar, I., Kheyrandish, A., Jamei, M., & Gharabaghi, B. (2021). Optimizing operating rules for multi-reservoir hydropower generation systems: An adaptive hybrid differential evolution algorithm. Renewable Energy, 167, 774-790.
Bolouri-Yazdeli, Y., Haddad, O. B., Fallah-Mehdipour, E., & Mariño, M. (2014). Evaluation of real-time operation rules in reservoir systems operation. Water resources management, 28(3), 715-729.
Bozorg-Haddad, O., Azarnivand, A., Hosseini-Moghari, S.-M., & Loáiciga, H. A. (2017). Optimal operation of reservoir systems with the symbiotic organisms search (SOS) algorithm. Journal of Hydroinformatics, 19(4), 507-52.
Bozorg-Haddad, O., Karimirad, I., Seifollahi-Aghmiuni, S., & Loáiciga, H. A. (2015). Development and application of the bat algorithm for optimizing the operation of reservoir systems. Journal of water resources planning and management, 141(8), 0404097
Chang, F. J., Chen, L., & Chang, L. C. (2005). Optimizing the reservoir operating rule curves by genetic algorithms. Hydrological Processes: An International Journal, 19(11), 2277-2289.
Che, G., Liu, L., & Yu, Z. (2020). An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle. Journal of Ambient Intelligence and Humanized Computing, 11(8), 3349-3354.
Chong, K. L., Lai, S. H., Ahmed, A. N., Jaafar, W. Z. W., & El-Shafie, A. (2021). Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm. Applied Soft Computing, 106, 107325.
Choopan, Y., & Emami, S. (2019). Optimal Operation of Dam Reservoir Using Gray Wolf Optimizer Algorithm (Case Study: Urmia Shaharchay Dam in Iran). Journal of Soft Computing in Civil Engineering, 3(3), 47-61.
Dahmani, S., & Yebdri, D. (2020). Hybrid algorithm of particle swarm optimization and Grey Wolf optimizer for reservoir operation management. Water resources management, 34(15), 4545-4560.
Davani Motlagh, A., Sadeghian, M., Javid, A., & Asgari, M. (2021). Optimization of Dam Reservoir Operation Using Grey Wolf Optimization and Genetic Algorithms (A Case Study of Taleghan Dam). International Journal of Engineering, 34(7), 1644-1652.(In Farsi)
Donyaii, A., Sarraf, A., & Ahmadi, H. (2020a). Application of a new approach in optimizing the operation of the multi-objective reservoir. Journal of Hydraulic Structures, 6(3), 1-20. (In Farsi)
Donyaii, A., Sarraf, A., & Ahmadi, H. (2020b). Evaluation of Whale, Fruit Fly and Cuckoo Search Algorithms in Optimizing Multi-Objective Operation of Golestan Dam Reservoir Based on Multi-Criteria Decision-Making Method.
Donyaii, A., Sarraf, A., & Ahmadi, H. (2020c). Water reservoir multiobjective optimal operation using Grey Wolf optimizer. Shock and Vibration, 2020 (In Farsi).
Emami, S., Choopan, Y., & Salmasi, F. (2020). Presentation of a Method Based on Gray Wolf Optimizer and Imperialist Competitive Algorithms in Optimal Operation of Dam Reservoir. Amirkabir Journal of Civil Engineering, 52(5), 1027-1046.  (In Farsi)
Fallah-Mehdipour, E., Haddad, O. B., & Mariño, M. (2011). MOPSO algorithm and its application in multipurpose multireservoir operations. Journal of Hydroinformatics, 13(4), 794-811.
Feng, Z.-k., Niu, W.-j., Liu, S., Luo, B., Miao, S.-m., & Liu, K. (2020). Multiple hydropower reservoirs operation optimization by adaptive mutation sine cosine algorithm based on neighborhood search and simplex search strategies. Journal of hydrology, 590, 125223.
Garousi-Nejad, I., Bozorg-Haddad, O., Loáiciga, H. A., & Mariño, M. A. (2016). Application of the firefly algorithm to optimal operation of reservoirs with the purpose of irrigation supply and hydropower production. Journal of Irrigation and Drainage Engineering, 142(10), 04016041.
Jahandideh-Tehrani, M., Bozorg-Haddad, O., & Loáiciga, H. A. (2019). Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview. Environmental Monitoring and Assessment, 191(7), 1-21.
Jahandideh-Tehrani, M., Bozorg-Haddad, O., & Loáiciga, H. A. (2020). Application of particle swarm optimization to water management: an introduction and overview. Environmental Monitoring and Assessment, 192(5), 1-18.
Karami, H., Ehteram, M., Mousavi, S.-F., Farzin, S., Kisi, O., & El-Shafie, A. (2019). Optimization of energy management and conversion in the water systems based on evolutionary algorithms. Neural computing and applications, 31(10), 5951-5964.
Labadie, J. W. (2004). Optimal operation of multireservoir systems: State-of-the-art review. Journal of water resources planning and management, 130(2), 93-111.
Masoumi, F., Salimi, N., & Zafari, N. (2020). Evaluation of Grasshopper Optimization Algorithm for Optimal Operation of Surface Water Reservoirs with Reliability Constraints. Iranian Journal of Irrigation & Drainage, 14(2), 579-592. (In Farsi)
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46-61.
Moeini, R., & Babaei, M. (2017). Constrained improved particle swarm optimization algorithm for optimal operation of large scale reservoir: proposing three approaches. Evolving Systems, 8(4), 287-301. (In Farsi)
Mohammadi, M., Mousavi, S. F., Farzin, S., & Karami, H. (2019). Optimal operation of dam reservoir using whale optimization algorithm and its hybrid with genetic algorithm based on multi-criteria decision making. Iranian journal of Ecohydrology, 6(2), 281-293(In Farsi).
Mohammadrezapour, O., & Zeynali, M. (2018). Comparison of meta-heuristic algorithms in the optimal operation of multi-reservoir (a case study: Golestan and Voshmgir dams). Journal of Water and Soil Science, 22(1).
Montalvo, I., Izquierdo, J., Pérez, R., & Tung, M. M. (2008). Particle swarm optimization applied to the design of water supply systems. Computers & Mathematics with Applications, 56(3), 769-776.
Noori, M., Emadi, A., & Fazloula, R. (2020). Agent Based Model Development for Optimal Water Allocation from Dam Reservoir Case Study: Shahid Rajaee Dam. Iranian Journal of Soil and Water Research, 51(4), 937-948. (In Farsi)
Ostadrahimi, L., Mariño, M. A., & Afshar, A. (2012). Multi-reservoir operation rules: multi-swarm PSO-based optimization approach. Water resources management, 26(2), 407-427.
Rani, D., Pant, M., & Jain, S. (2020). Dynamic programming integrated particle swarm optimization algorithm for reservoir operation. International Journal of System Assurance Engineering and Management, 11(2), 515-529.
Reddy, M. J., & Kumar, D. N. (2007). Optimal reservoir operation for irrigation of multiple crops using elitist-mutated particle swarm optimization. Hydrological Sciences Journal, 52(4), 686-701.
SaberChenari, K., Abghari, H., & Tabari, H. (2016). Application of PSO algorithm in short-term optimization of reservoir operation. Environmental Monitoring and Assessment, 188(12), 1-11.
Sharifi, M. R., Akbarifard, S., Qaderi, K., & Madadi, M. R. (2021). Developing MSA algorithm by new fitness-distance-balance selection method to optimize cascade hydropower reservoirs operation. Water resources management, 35(1), 385-406.
Wurbs, R. A. (1993). Reservoir-system simulation and optimization models. Journal of water resources planning and management, 119(4), 455-472.
Yaghoubi, B., Hosseini, S. A., Nazif, S., & Daghighi, A. (2020). Development of reservoir’s optimum operation rules considering water quality issues and climatic change data analysis. Sustainable Cities and Society, 63, 102467.
Yan, D., Zhuang, K., Xu, B., Chen, D., Mei, R., Wu, C., & Wang, X. (2017). Excitation current analysis of a hydropower station model considering complex water diversion pipes. Journal of Energy Engineering, 143(5), 04017012.
Zhang, R., Zhou, J., Ouyang, S., Wang, X., & Zhang, H. (2013). Optimal operation of multi-reservoir system by multi-elite guide particle swarm optimization. International Journal of Electrical Power & Energy Systems, 48, 58-68.
Iranian Journal of Soil and Water Research
Volume 52, Issue 11
March 2022
Pages 2829-2842

Files

Share

How to cite

Statistics