scholarly journals Optimal Operation of Flood Storage Areas in Huai River Using Coupled HEC-RAS River Model and NSGAII Global Optimization Algorithm

10.29007/q4v8 ◽  
2018 ◽  
Author(s):  
Andreja Jonoski ◽  
Ioana Popescu ◽  
Sun Zhe
Keyword(s):  
Optimization Algorithm ◽  
Local Population ◽  
Optimal Operation ◽  
Damage Potential ◽  
Main River ◽  
Decision Variables ◽  
Huai River ◽  
Storage Area ◽  
Opening And Closing ◽  
Initial Results

In this work we present an application of coupled HEC RAS river model with NSGAII multi-objective optimization algorithm, for optimal operations of flood protection storage areas in the downstream part of Huai River in China. During flood, these storage areas are used for decreasing the flood water level downstream in order to protect the important, densely populated city of Bengbu. However, the same storage areas have also been used by local population, as both residential and agricultural zones, with high damage potential in case of flooding. The application investigates optimal operations of opening and closing the gates that connect the storage areas to the main river, which minimize the damage in the storage areas without compromising the protection of Bengbu. Two objectives are formulated related to: 1) downstream risk of flooding in Bengbu, and 2) damages in the storage areas. Decision variables are stage differences between the river and a given storage area, used for controlling gates operations (opening and closing). The coupling is performed in MATLAB using recently available HEC RAS API, known as HEC-RAS Controller. Initial results, obtained using flood hydrograph from the summer of 2007, indicate possible optimal operations, with selective usage of the storage areas.

scholarly journals Analysis of Flood Storage Area Operations in Huai River Using 1D and 2D River Simulation Models Coupled with Global Optimization Algorithms

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 509 ◽  
Author(s):  
Andreja Jonoski ◽  
Ioana Popescu ◽  
Sun Zhe ◽  
Yuhan Mu ◽  
Yiqing He
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms ◽  
Local Population ◽  
Simulation Models ◽  
Flood Management ◽  
Nsga Ii ◽  
Operational Strategies ◽  
Huai River ◽  
Storage Area ◽  
Flood Storage

This article addresses the issue of flood management using four flood storage areas in the middle section of Huai River in China which protect the important downstream city of Bengbu. The same areas are also used by the local population as residential and agricultural zones. An optimization problem is therefore posed, with two objectives of simultaneously minimizing the downstream flood risk in Bengbu city and the storage areas’ economic damages. The methodology involved development of river flood models using HEC-RAS, with varying complexity, such as 1-dimensional (1D) model with storage areas represented as lumped conceptual reservoirs, and 2-dimensional (2D) models with detailed representation of the terrain, land-use and hydrodynamics in the storage areas. Experiments of coupling these models with global optimization algorithms (NSGA-II, PESA-II and SPEA-II) were performed (using the HEC-RAS Controller), in which the two objective functions were minimized, while using stage differences between the river and the storage areas as decision variables for controlling the opening/closing of the gates at the lateral structures that link the river with the storage areas. The comparative analysis of the results indicate that more refined optimal operational strategies that spread the damages across all storage areas can be obtained only with the detailed flood simulation models, regardless of the optimization algorithm used.

scholarly journals Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy

2021 ◽  
Vol 7 ◽  
pp. 3703-3725
Author(s):  
Mohammad Ehteram ◽  
Fatemeh Barzegari Banadkooki ◽  
Chow Ming Fai ◽  
Mohsen Moslemzadeh ◽  
Michelle Sapitang ◽  
...  
Keyword(s):  
Power Generation ◽  
Optimization Algorithm ◽  
Optimal Operation ◽  
Reservoir Systems

scholarly journals Water balance assessment of Sajnam watershed, Lalitpur (U.P.)

2019 ◽  
Vol 34 (02) ◽  
Author(s):  
R. K. Jaiswal ◽  
T. Thomas ◽  
Jyoti P Patil ◽  
Meeta Gupta ◽  
V. C. Goyal
Keyword(s):  
Water Balance ◽  
Artificial Recharge ◽  
Local Population ◽  
Water Harvesting ◽  
Balance Assessment ◽  
Irrigation Project ◽  
Main River ◽  
Balance Analysis ◽  
Demand Scenario ◽  
Water Harvesting Structures

It is a well-known fact that it is not all possible to avoid droughts, but droughts can be managed to minimise the hardships of the local population. For this purpose, understanding of the supply-demand scenario is of utmost importance to understand the overall hydrology and planning needs of any watershed. It is in this direction, the comprehensive water balance analysis has been performed for the Sajnam watershed in Lalitpur district of Bundelkhand which is susceptible to regular and continuous droughts. The detailed water balance has been carried out after identification of important components and their quantification using the advance tools of Remote Sensing and GIS alongwith standard estimation techniques of individual components. It was observed that the runoff at the outlet of Sajnam basin is influenced by the water storage in the irrigation project located on the main river. The higher surface runoff of 668.53 MCM, 406.17 MCM, 343.46 MCM and 214.00 MCM is generated only during 2013-14, 2008-09, 2012-13 and 2010-11 respectively. During the remaining years, the runoff varied between 89.35 MCM and 209.81 MCM. Efforts can be initiated towards exploring the possibility of more water harvesting structures onthe lower order tributaries as well as artificial recharge measures depending on the hydro-geology of the watershed..

A decision-making method based on Bayesian optimization algorithm for small modular reactor

Kerntechnik ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. 109-121 ◽  
Author(s):  
B. Zhang ◽  
M. Peng ◽  
S. Cheng ◽  
L. Sun
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Optimal Operation ◽  
Bayesian Optimization ◽  
Operating Personnel ◽  
Bayesian Optimization Algorithm ◽  
Autonomous Operation ◽  
Small Modular Reactor ◽  
The Cost

Abstract Small modular reactors (SMRs) are suitable for deployment in isolated underdeveloped areas to support highly localized microgrids. In order to achieve almost autonomous operation for reducing the cost of operating personnel, an autonomous control system with decision-making capability is needed. In this paper, a decision-making method based on Bayesian optimization algorithm (BOA) is proposed to explore the optimal operation scheme under fault conditions. BOA is used to adjust exploration strategy of operation scheme according to observations (operation schemes previously explored). To measure the feasibility of each operation scheme, an objective function that considers security and economy is established. BOA attempts to obtain the optimal operation scheme with maximum of the objective function in as few iterations as possible. To verify the proposed method, all main pump powered off fault is simulated by RELAP5 code. The optimal operation scheme of the fault is applied, the transient result shows that all key parameters are within safe limits and SMR is maintained at relatively high power, which means that BOA has the decision-making capability to get an optimal operation scheme on fault conditions.

scholarly journals Hybridized Symbiotic Organism Search Algorithm for the Optimal Operation of Directional Overcurrent Relays

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Sulaiman ◽  
Ashfaq Ahmad ◽  
Asfandyar Khan ◽  
Shakoor Muhammad
Keyword(s):  
Simulated Annealing ◽  
Objective Function ◽  
Search Algorithm ◽  
Optimal Operation ◽  
Decision Variables ◽  
Overcurrent Relays ◽  
Overcurrent Relay ◽  
Symbiotic Organism Search

This paper presents the solution of directional overcurrent relay (DOCR) problems using Simulated Annealing based Symbiotic Organism Search (SASOS). The objective function of the problem is to minimize the sum of the operating times of all primary relays. The DOCR problem is nonlinear and highly constrained with two types of decision variables, namely, the time dial settings (TDS) and plug setting (PS). In this paper, three models of the problem are considered, the IEEE 3-bus, 4-bus, and 6-bus, respectively. We have applied SASOS to solve the problem and the obtained results are compared with other algorithms available in the literature.

scholarly journals Introducing modified version of penguins search optimization algorithm (PeSOA) and its application in optimal operation of reservoir systems

2017 ◽  
Vol 18 (4) ◽  
pp. 1484-1496 ◽  
Author(s):  
Afshin Mansouri ◽  
Babak Aminnejad ◽  
Hassan Ahmadi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Real World ◽  
Global Optimum ◽  
Optimal Operation ◽  
The Other ◽  
Reservoir System ◽  
Search Optimization ◽  
Real World Problem ◽  
Reservoir Systems

Abstract In the current study, modified version of the penguins search optimization algorithm (PeSOA) was introduced, and its usage was assessed in the water resources field. In the modified version (MPeSOA), the Gaussian exploration was added to the algorithm. The MPeSOA performance was evaluated in optimal operation of a hypothetical four-reservoir system and Karun-4 reservoir as a real world problem. Also, genetic algorithm (GA) was used as a criterion for evaluating the performance of PeSOA and MPeSOA. The results revealed that in a four-reservoir system problem, the PeSOA performance was much weaker than the GA; but on the other hand, the MPeSOA had better performance than the GA. In the mentioned problem, PeSOA, GA, and MPeSOA reached 78.43, 97.46, and 98.30% of the global optimum, respectively. In the operation of Karun-4 reservoir, although PeSOA performance had less difference with the two other algorithms than four-reservoir problem, its performance was not acceptable. The average values of objective function in this case were equal to 26.49, 23.84, and 21.48 for PeSOA, GA, and MPeSOA, respectively. According to the results obtained in the operation of Karun-4 reservoir, the algorithms including MPeSOA, GA, and PeSOA were situated in ranks one to three in terms of efficiency, respectively.

scholarly journals Optimum manipulator path generation based on improved differential evolution constrained optimization algorithm

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141987206 ◽  
Author(s):  
Shimeng Fan ◽  
Xihua Xie ◽  
Xuanyi Zhou
Keyword(s):  
Differential Evolution ◽  
Constrained Optimization ◽  
Optimization Algorithm ◽  
Operation Time ◽  
Optimal Operation ◽  
Adaptive Mutation ◽  
Path Generation ◽  
End Effector ◽  
Joint Displacement ◽  
Self Adaptive

A new improved differential evolution constrained optimization algorithm is proposed to determine the optimum path generation of a rock-drilling manipulator with nine degrees of freedom. This algorithm is developed to minimize the total joint displacement without compromising the pose accuracy of the end-effector. Considering the rule for optimal operation time and smooth joint motion, total joint displacement and minimization of the end-effector pose error are respectively taken as the optimization objective and constraints. In the proposed algorithm, the inverse kinematics solution is computed by self-adaptive mutation differential evolution constrained optimization (SAMDECO) algorithm. Unlike conventional differential evolution (DE) algorithms, in the process of selection operation, the proposed algorithm takes full advantages of the information of excellent infeasible solutions in the contemporary population and scales the contribution of position constraint and orientation constraint. Consequently, the search process is guided to approach the optimal solution from both feasible and infeasible regions, which tremendously improves convergence accuracy and convergence rate. Some contrastive experiments are conducted with the basic self-adaptive mutation differential evoluton (SAMDE) algorithm. The results indicate that the proposed algorithm outperforms the basic SAMDE algorithm in terms of compliance of joints, which raises operation efficiency and plays an important role in engineering services value.

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