Abstract
The Charged System Search (CSS) metaheuristic algorithm is introduced to the field of water resources management and applied to derive water-supply and hydro-power operating policies for a large-scale real-world reservoir system. The optimum algorithm parameters for each reservoir operation problems are also obtained via a tuning procedure. The CSS algorithm is a metaheuristic optimization method inspired by the governing laws of electrostatics in physics and motion from the Newtonian mechanics. In this study, the CSS algorithm’s performance has been tested with benchmark problems, consisting of highly non-linear constrained and/or unconstrained real-valued mathematical models, such as the Ackley’s function and Fletcher–Powell function. The CSS algorithm is then used to optimally solve the water-supply and hydropower operation of “Dez” reservoir in southern Iran over three different operation periods of 60, 240, and 480 months, and the results are presented and compared with those obtained by other available optimization approaches including Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Constrained Big Bang–Big Crunch (CBB–BC) algorithm, as well as those obtained by gradient-based Non-Linear Programming (NLP) approach. The results demonstrate the robustness and superiority of the CSS algorithm in solving long term reservoir operation problems, compared to alternative methods. The CSS algorithm is used for the first time in the field of water resources management, and proves to be a robust, accurate, and fast convergent method in handling complex problems in this filed. The application of this approach in other water management problems such as multi-reservoir operation and conjunctive surface/ground water resources management remains to be studied.
Highlights
Optimal utilization of available fresh-water resources requires development and application of robust and effective methods to plan and operate current reservoirs [1,2]
A robust metaheuristic optimization algorithm called the Charged System Search algorithm was introduced to the field of water resources management, and was applied to a large-scale real-world reservoir operation problem for the first time
The Charged System Search (CSS) was applied to the optimization of water-supply and hydropower operation of the “Dez” reservoir in Iran for operation periods of 60, 240, and 480 months, and the results compared with those derived by Genetic, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Constrained Big Bang-Big Crunch (CBB-BC) algorithms as well as those obtained by the Non-Linear Programming (NLP) approach
Summary
Optimal utilization of available fresh-water resources requires development and application of robust and effective methods to plan and operate current reservoirs [1,2]. Effective reservoir operation requires policies that optimize releases from the reservoir or storage volume, in order to achieve desired objectives such as maximizing power generation or minimizing water deficit, flood risk, and operation costs. Adoption of these policies are a must for the operators to make decisions based on the current and past conditions of the reservoir storage and river inflow, in order to manage the upcoming flood risks and water shortages [1,2,3]. Regional studies show future changes in reliability of reservoirs due to the changes in climate, projected by climate models [19,20,21,22]
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