Multi-Reservoir Flood Control Operation Using Improved Bald Eagle Search Algorithm with ε Constraint Method (original) (raw)
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Flood Management in Hirakud Reservoir using Particle Swarm Optimization
Disaster Advances, 2018
This work proposed particle swarm optimization (PSO) a meta-heuristic technique to develop operating policies for flood control in Hirakud multipurpose reservoir, Sambalpur, Odisha, India. The flood control reservoir is designed to moderate flood and not to conserve water. Real time reservoir operation is a challenging task. The reservoir releases are influenced by the inflows and the reservoir storage levels. The present research develops effective reservoir operation policies by using optimization technique and demonstrates the utility for practical applications. The inflows into the Hirakud reservoir are highly uncertain, which often induce lot of uncertainty in release policies. Therefore, it requires developing operation policies at different exceedance probabilities of inflows to assess the associated risks and developing real time reservoir operation models to facilitate easiness in reservoir operation system. Mostly such problems involve non-linear optimization to find a feasible solution as it involves good quantities of equality and inequality constraints. In this study, it is intended to test the usefulness of PSO in solving such type of problems. To formulate the PSO model for reservoir operation, the problem is approached by considering a finite time series of inflows, classifying the reservoir volume into several class intervals and determining the reservoir release for each period with respect to a predefined optimality criterion. The multiple objectives comprise of minimizing flood risks, minimizing irrigation deficits and maximizing hydropower production in that order of priority. The developed model is applied for monthly operation. The results of the models indicate that PSO model performs better in flood control restrictions.
This paper presents a multi-objective optimisation model for multipurpose reservoir operation model. Two conflicting objectives are to minimize downstream damage by reducing flood peaks at selected downstream control points and to maximize hydropower generation. The obtained Pareto optimal solution is a compromise between optimal alternatives of downstream and hydropower damages. The proposed model is applied to the reservoirs system of Karkheh river basin in southwest of Iran. The proposed model includes VENSIM simulation model based on system dynamics approach coupled with multi-objective particle swarm optimization (MOPSO) algorithm. The MOPSO-VENSIM model is employed to optimize the operation of cascaded reservoirs during flood through allocating an optimal initial flood control capacity to each reservoir in the river basin. The results indicate that an improved reservoir operation as flood peak reduction, distribution of initial flood control capacity among the cascaded reservo...
Due to global water scarcity and also reduced surface water runoff due to increasing water consumption and climate change effect, the optimal operation of reservoirs has become an interested topic for water resources management specialists. In the present study, since more than three objectives are considered for the Azad Dam operation in Iran, the many-objective particle swarm optimization (MaOPSO) algorithm is used for the optimal operation of the reservoir. Four objectives are defined as maximizing water supply, water supply reliability and mean annual energy generation while minimizing the violation of the downstream river flow over a pre-defined safe flow rate. Running MaOPSO and comparing a sample solution with the objective functions values obtained by simulating the present situation over a 7-year operation period indicates 42.8% increase in water supply, 7.9% increase in water supply reliability, 4.39% decrease in hydropower generation and 57.2% decrease in over flowing cas...
Flood Control Operation of Reservoir Group Using Yin-Yang Firefly Algorithm
Water Resources Management , 2021
Flood control operation (FCO) of a reservoir is a complex optimization problem with a large number of constraints. With the rapid development of optimization techniques in recent years, more and more research efforts have been devoted to optimizing FCO problems. However, for solving large-scale reservoir group optimization problem, this is still a challenging task. In this work, a reservoir group FCO model is established with minimum flood volume stored in each reservoir and minimum peak flow of downstream control point during the dispatch process. At the same time, a flood forecast model for FCO of a reservoir group is developed by coupling Yin-Yang firefly algorithm (YYFA) with ε constrained method. As a case study, the proposed model is applied to a three-reservoir flood control system in Luanhe River Basin consisting of reservoirs, river channels, and downstream control points. Results show that optimal operation of three reservoirs systems can efficiently reduce the occupied storage capacity for flood control and flood peaks at downstream control point of the basin. The proposed method can be extended to FCO of other reservoir groups with similar conditions.
Application of PSO algorithm in short-term optimization of reservoir operation
The optimization of the operation of existing water systems such as dams is very important for water resource planning and management especially in arid and semi-arid lands. Due to budget and operational water resource limitations and environmental problems, the operation optimization is gradually replaced by new systems. The operation optimization of water systems is a complex, nonlinear, multi-constraint, and multidimen-sional problem that needs robust techniques. In this article, the practical swarm optimization (PSO) was adopted for solving the operation problem of multipurpose Mahabad reservoir dam in the northwest of Iran. The desired result or target function is to minimize the difference between downstream monthly demand and release. The method was applied with considering the reduction probabilities of inflow for the four scenarios of normal and drought conditions. The results showed that in most of the scenarios for normal and drought conditions, released water obtained by the PSO model was equal to downstream demand and also, the reservoir volume was reducing for the probabilities of inflow. The PSO model revealed a good performance to minimize the reservoir water loss, and this operation policy can be an appropriate policy in the drought condition for the reservoir.
Application of Harmony Search Algorithm to Reservoir Operation Optimization
In this study, a meta-heuristic technique called harmony search (HS) algorithm is developed for reservoir operation optimization with respect to flood control. The HS algorithm is used to minimize the water supply deficit and flood damages downstream of a reservoir. The GIS database is used to determine the flood damage functions. The efficacy of HS algorithm is evaluated in comparison with other techniques by using a benchmark problem for a single reservoir operation optimization problem. HS showed promising results in terms of speed of convergence to an optimal objective function value compared with other techniques such as honey-bee mating optimization (HBMO) and a global optimization model (LINGO 8.0 NLP solver). The HS algorithm is then applied to the Narmab reservoir, north of Iran, as a case study. Narmab reservoir serves multiple purposes including irrigation, flood control, and drinking water requirements. The developed model is applied for monthly operation. The results show that the HS algorithm can be effectively used for operation of reservoir for flood management.