Extraction of optimal flow release pattern from dam reservoirs based on multi-objective particle swarm optimization algorithm

Introduction

Due to the location of Iran in an arid and semi-arid climate, the optimal use of water resources systems and better management in water shortage conditions are necessary. One of the appropriate tools in the field of water resources management is the use of simulation, optimization techniques and the combination of simulation and optimization methods. The main goal of this research is to provide a solution in which, according to the capacity of the reservoir, in addition to achieving the acceptable reliability of supplying demands in the whole period, the percentage of meeting the needs in dry months also increases.


Materials and Methods
To achieve the optimal operation of the water resources in the Marun and Jareh dams located in the south of Iran, the multi-objective particle swarm optimization (MOPSO) algorithm is linked to the WEAP model to provide a new structure for the water resources management, especially in periods of low water by obtaining the optimal values of water release from the reservoir.In this structure, the WEAP simulator is called directly in the MATLAB environment and executed by the optimization algorithm. In this research, for optimal operation of the system, the amount of water released from the reservoir every month is considered as a decision variable. However, due to the large number of available variables and the high volume of calculations, in the body of the MOPSO optimization model, the flow release coefficients that are considered on a monthly basis are used. Based on these coefficients, every month, a percentage of the water volume in the Marun and Jareeh reservoirs is released to supply the needs of the downstream uses, and the rest is stored for the better management of the reservoir, especially in water shortage conditions. Therefore, according to the application of these coefficients on a monthly basis, 12 variables are considered for each dam and 24 decision variables in the whole multi-dam system in the entire next 30-year operation period.

Results and discussion
The optimization process is carried out using the MOPSO multi-objective algorithm. The number of iterations of the algorithm to reach convergence is considered to be around 1000. Finally, after the optimization, according to the population size of 48 and the implementation of the MOPSO model for 1000 iterations, the solutions close to to optimal are obtained, and the optimal exchange curve (Pareto-optimal front) between the optimization objectives (the function of maximizing the supplying percentage and the function of minimizing the violation of the minimum operation level) is achieved (Figure (1)). In Pareto curve the solution with the least amount of penalty due to the violation of the reservoir operation capacity and the highest supplying percentage is chosen as the best answer. Then, these optimal variables are entered in the WEAP surface water model.


The average percentage of supplying the needs and the level of reliability of meeting the needs according to Table (1) for different uses in optimization scenario. According to this table, in this scenario, the drinking and industrial demands are fully provided in all months. Also, the average percentage of meeting the agricultural demands of the Marun and Jarrahi basins for August, September, October and November was improved by about 15 to 16%, which is significant and shows a decrease in the severity of failure in these low water months. The supplying percentage in July also increases by about 7%.

Conclusion

The results obtained from the implementation of the optimizer model showed that the percentage of demand supply in the months that was 0% in the reference scenario reached 30-60% and in most of the dry months, it was calculated around 45%. This showed that the optimizer model was able to reduce the failure severity in the worst case and in years with three to eight consecutive dry months. The results showed that according to the application of hedging in the model, some of the need is stored in the high water months to be consumed in the low water months. This research showed that planning water resources and allocating them to existing uses only by relying on maximizing the reliability of supplying needs in the entire period, especially in areas with dry climates where we inevitably face severe water shortages in several months of the year, is not a suitable solution and leads to irreparable financial losses and social consequences. Instead, using the solution of this research will lead to better management of the reservoir and reduce the severity of the failure to supply the needs in the dry months of low water.