Application of gray wolf multi-objective algorithm in optimal operation of dam reservoirs in low water areas

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.

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

Abstract

In this research, the simulation-optimization method was used with the integration of the WEAP simulator model and the multi-objective gray wolf optimization algorithm (MOGWO) for the optimal exploitation of the Dez Dam water resource systems. The main goal in this structure is to provide a solution in which, based on the resources and costs of the region, in addition to reducing the penalty due to the violation of the authorized capacities of the reservoir, the percentage of meeting the needs of various uses in the entire period, especially in the dry months, will also increase. The results showed that in the reference scenario, in many dry years, the percentage of meeting the demand in critical and low water months was close to zero. This will create instability in the system and create irreparable economic losses and will have many social consequences. Optimizing the system based on the proposed structure in this research has improved the percentage of demand supply in critical months so that the minimum percentage of demand supply in these months reaches 30% and there is no month with zero demand supply percentage. The proposed model in this research can lead to better management of the reservoir in dry areas by taking into account the allowed capacities of the reservoir with optimal release of flow in high water seasons and storing part of the flow in the reservoir and releasing it in low water seasons.

Keywords

Main Subjects


EXTENDED ABSTRACT

Introduction

The most effective use of water resources has drawn the attention of many experts because of the scarcity of water resources and the alteration in consumption habits brought on by population increase. Owing to Iran's location in a dry and semi-arid climate, better management of water scarcity conditions and the optimal operation of water resource systems are required. In dry months, significant water shortages result from reservoir water being released with the intention of boosting reliability based on full demand supply in some months.

 

Materials and Methods

In this study, a method is proposed in which some rainy season water is retained in the reservoir to be released in dry months to alleviate the failure in such times, based on the reservoir zoning and a multi-objective optimization system. In order to achieve this, the WEAP simulator model and the multi-objective gray wolf optimizer (MOGWO) algorithm are linked. In the linked model, the MOGWO algorithm first generates the values for the decision variables based on the model's written constraints, which are then imported into the WEAP simulator model, where the model is then performed. The objective exchange curve is then generated after the results are reviewed using the goal functions specified by the optimizer model. If the intended objectives are not achieved, the optimizer model is run once again, a fresh population is created, and it is then inserted into the simulator model. This cycle is repeated until the result is closed  to the optimum value. The algorithm in such a system looks for a solution where, in terms of reservoir operation capacity, in addition to achieving adequate reliability of demand supply over the entire time, the proportion of supply of demands in dry months also increases.

 

Results and discussion

Finally, the role curve was assessed based on the outcomes of two scenarios, including the Reference System (RS) (based on existing conditions) and the Optimized System (OS). The RS results show that the proportion of demand supply in most uses for three to five consecutive months is equal to zero in many dry years, particularly the last years of planning, and that it is less than 5% in the remaining low-water years. The percentage of meeting the demands in such months rises to 28% to 60%, nevertheless, thanks to role curve optimization based on reservoir zoning. Also, the OS increases its percentage of meeting downstream environmental demands during months with low water levels. Based on the established objective functions in the low water and high water periods, the system enhances the withdrawal rate of the surface water and groundwater resources in comparison to the RS, given the ideal role curve performance in the OS. This study demonstrates how using this strategy improves reservoir management and lessens the severity of failure in meeting diverse demands during dry months.

 

Conclusion

The findings demonstrated that the optimizer model might lessen the degree of failure in the worst-case scenario and in years with three to six consecutive months without precipitation. This problem results from the optimizer model's use of the given goal functions. The findings demonstrated that some water was kept in the reservoir during the rainy seasons in order to be released as hedging during the dry months, in accordance with the application of the optimal role curve and the application of the hedging policy in the optimizer model. By meeting a portion of the demand in crucial months, this method decreased the frequency and severity of failure in dry and low-water months and guarded against significant system damage. In areas with dry climates where we ineluctably experience severe water shortages in several months of the year, this research demonstrated that planning water resources and allocating them to existing uses solely by relying on maximizing the reliability of supply over the entire period is not a suitable solution and results in irreparable financial losses and social consequences. Instead, putting the research's answer to use improves reservoir management and lessens the severity of failure to meet demand during dry months.

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