scholarly journals Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm

2019 ◽  
Vol 651 ◽  
pp. 1877-1891 ◽  
Author(s):  
Jafar Y. Al-Jawad ◽  
Hassan M. Alsaffar ◽  
Douglas Bertram ◽  
Robert M. Kalin
Keyword(s):  
Optimization Algorithm ◽  
Reservoir Operation ◽  
Environmental Flows ◽  
Evolutionary Optimization ◽  
Operation Strategy

scholarly journals Assessment of the Multi-Objective Reservoir Operation for Maintaining the Turbidity Maximum Zone in the Yangtze River Estuary

2018 ◽  
Vol 15 (10) ◽  
pp. 2118 ◽  
Author(s):  
Yang Yu ◽  
Peifang Wang ◽  
Chao Wang ◽  
Xun Wang ◽  
Bin Hu
Keyword(s):  
Reservoir Operation ◽  
Yangtze River ◽  
Environmental Flows ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
The Yangtze River ◽  
Operation Model ◽  
Hydropower Generation ◽  
Quantitative Correlation ◽  
The Yangtze River Estuary

The construction of multifunction reservoirs is important for flood control, agriculture irrigation, navigation, and hydropower generation, but dam construction will inevitably affect the downstream flow and sediment regimes, which can cause some environmental and ecological consequences. Therefore, this paper aims to propose a framework for assessing the multiobjective reservoir operation model based on environmental flows for sustaining the suspended sediment concentration (SSC) requirements in the turbidity maximum zone (TMZ). The Yangtze River Estuary was used as a case study. Through using an analytical model, a quantitative correlation between SSC and water flow rate was established. Then, the quantitative correlation and the SSC requirements were applied to determine the environmental flows for the estuarine TMZ. Subsequently, a multiobjective reservoir operation model was developed for the Three Gorges Reservoir (TGR), and an improved nondominated sorting genetic algorithm III based on elimination operator was applied to the model. An uncertainty analysis and a comparative analysis were used to assess the model’s performance. The results showed that the proposed multiobjective reservoir operation model can reduce ecological deficiency under wet, normal, and dry years by 33.65%, 35.95%, and 20.98%, with the corresponding hydropower generation output lost by 3.37%, 3.88%, and 2.95%, respectively. Finally, we discussed ecological satiety rates under optimized and practical operation of the TGR in wet, normal, and dry years. It indicated that the multiobjective-optimized runoff performs better at maintaining the TMZ in the Yangtze River Estuary than practical runoff. More importantly, the results can offer guidance for the management of the TGR to improve the comprehensive development and protection of the estuarine ecological environment.

A New Approach to Compensate Oscillations of Path-Linked Presses Caused by Inertial Forces

2016 ◽  
Vol 1140 ◽  
pp. 361-368
Author(s):  
Stefan Hilscher ◽  
Richard Krimm ◽  
Bernd Arno Behrens
Keyword(s):  
Conceptual Design ◽  
Optimization Algorithm ◽  
Evolutionary Optimization ◽  
Inertial Forces ◽  
New Approach ◽  
Virtual Testing ◽  
Linear Motors ◽  
Control Signals ◽  
The Press ◽  
Mass Balancing

Presses with mechanical linkages based on levers between motor and ram (path-linked presses) tend to oscillate due to inertial forces as a consequence of the drive parts motion.In this publication a new approach for a mass-balancing system is presented. This system allows to generate the optimal compensation forces needed to counteract the inertial forces by means of four linear motors. The control signals for the linear motors are specified by an evolutionary optimization algorithm, which operates on the base of measured accelerations of the press frame. The control signals of the linear motors are created in a way that the machines oscillations are reduced to a minimum. This way the presented mass-balancing system adapts itself automatically to varying conditions during the operation of the machine, such as a tool change or a varying stroke rate.In particular, the present publication provides the results of the conceptual design and the virtual testing of this approach, which has been mainly carried out with the help of multiple-body simulations.

S.T. (Shafiabady-Teshnehlab) Evolutionary Optimization Algorithm

2011 ◽  
Vol 2 (3) ◽  
pp. 73-82
Author(s):  
Niusha Shafiabady ◽  
Mohammad Teshnehlab ◽  
Mohammad Ali Nekoui
Keyword(s):  
Optimization Algorithm ◽  
Evolutionary Optimization
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