Research on the Application of Bat Algorithm in the Medium and Long Term Optimization of Reservoir Operation

2018 ◽  
Author(s):  
Wang Jingyi ◽  
Zhang Zhi ◽  
Li Wenwu ◽  
Daniel Eliote Mbanze
Keyword(s):  
Reservoir Operation ◽  
Bat Algorithm

scholarly journals Performance analysis of a reservoir in arid region Case study: Babar reservoir, Aurès region, Algeria

2018 ◽  
Vol 39 (1) ◽  
pp. 141-146 ◽  
Author(s):  
Fatima Z. Tebbi ◽  
Hadda Dridi ◽  
Mahdi Kalla
Keyword(s):  
Reservoir Operation ◽  
Arid Region ◽  
R Package ◽  
Performance Criteria ◽  
Stochastic Dynamic ◽  
Operation Optimization ◽  
Rule Curves ◽  
Demand Scenario

AbstractLong term and mid-term reservoir operation involves derivation of rule curves for optimal management of the available resource. The present work deals with reservoir operation in the Aurès arid region. As an example, Babar reservoir is selected to apply the proposed approach which estimates all the water balance terms, especially those which are random as water inflows. For each demand scenario a reservoir operation optimization model using Explicit Stochastic Dynamic Programming (ESDP) is performed, to derive optimal rule curves based on historical operating records (Jan 2002–Dec 2013) and using “Reservoir” R package®. Subsequently, risk analysis is conducted for these different demand scenarios rules by the RRV (reliability, resilience, vulnerability) metrics. Results show the advantage of using the “Reservoir” R package for a rapid and an easy analysis of the performance criteria jointly with the optimization algorithm to Re-operate Reservoir operation.

Optimal Short-term Reservoir Operation with Integrated Long-term Goals

2012 ◽  
Vol 26 (10) ◽  
pp. 2833-2850 ◽  
Author(s):  
J. Sreekanth ◽  
Bithin Datta ◽  
Pranab K. Mohapatra
Keyword(s):  
Reservoir Operation ◽  
Short Term

scholarly journals Long-Term Impacts of Reservoir Operation on the Spatiotemporal Variation in Nitrogen Forms in the Post-Three Gorges Dam Period (2004–2016)

2021 ◽  
Author(s):  
Bei Nie ◽  
Yuhong Zeng ◽  
Lanhua Niu ◽  
Xiaofeng Zhang
Keyword(s):  
Water Quality ◽  
Reservoir Operation ◽  
Yangtze River ◽  
Ammonia Nitrogen ◽  
Three Gorges ◽  
The Yangtze River ◽  
Engineering Construction ◽  
Nitrogen Concentrations ◽  
Essential Nutrient

Abstract Nitrogen (N) is an essential nutrient limiting life, and its biochemical cycling and distribution in rivers have been markedly affected by river engineering construction and operation. Here, we comprehensively analyzed the spatiotemporal variations and driving environmental factors of N distributions based on the long-term observations (from 2004 to 2016) of seven stations in the Three Gorges Reservoir (TGR). In the study period, the overall water quality status of the river reach improved, whereas N pollution was severe and tended to be aggravated after the TGR impoundment. The anti-seasonal reservoir operation strongly affected the variations in N forms. The total nitrogen (TN) concentration in the mainstream of the Yangtze River continuously increased, although it was still lower than that in the incoming tributaries (Wu and Jialing rivers). Further analysis showed that this increase occurred probably because of external inputs, including the upstream (76%), non-point (22%), and point source pollution inputs (2%). Besides, different N forms showed significant seasonal variations; among them, the TN and nitrate nitrogen concentrations were the lowest in the impoundment season (October–February), and the ammonia nitrogen concentrations were the highest in the sluicing season (March–May). These parameters varied likely because of internal N transformation. Redundancy analysis revealed that the water level regulated by the anti-seasonal operation was the largest contributor. Our findings could provide a basis for managing and predicting the water quality in the Yangtze River.

Hedging Rules-Based Optimal Reservoir Operation Using Bat Algorithm

2019 ◽  
Vol 33 (13) ◽  
pp. 4525-4538 ◽  
Author(s):  
Javad Jamshidi ◽  
Mojtaba Shourian
Keyword(s):  
Reservoir Operation ◽  
Bat Algorithm ◽  
Hedging Rules

scholarly journals Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty

2018 ◽  
Vol 20 (2) ◽  
pp. 332-355 ◽  
Author(s):  
Mohammad Ehteram ◽  
Sayed Farhad Mousavi ◽  
Hojat Karami ◽  
Saeed Farzin ◽  
Vijay P. Singh ◽  
...  
Keyword(s):  
Climate Change ◽  
Evolutionary Algorithms ◽  
Reservoir Operation ◽  
High Reliability ◽  
Bat Algorithm ◽  
Particle Swarm Algorithm ◽  
Base Period ◽  
Future Period ◽  
Change Models ◽  
The Future

Abstract This study investigated reservoir operation under climate change for a base period (1981–2000) and future period (2011–2030). Different climate change models, based on A2 scenario, were used and the HAD-CM3 model, considering uncertainty, among other climate change models was found to be the best model. For the Dez basin in Iran, considered as a case study, the climate change models predicted increasing temperature from 1.16 to 2.5°C and decreasing precipitation for the future period. Also, runoff volume for the basin would decrease and irrigation demand for the downstream consumption would increase for the future period. A hybrid framework (optimization-climate change) was used for reservoir operation and the bat algorithm was used for minimization of irrigation deficit. A genetic algorithm and a particle swarm algorithm were selected for comparison with the bat algorithm. The reliability, resiliency, and vulnerability indices, based on a multi-criteria model, were used to select the base method for reservoir operation. Results showed the volume of water to be released for the future period, based on all evolutionary algorithms used, was less than for the base period, and the bat algorithm with high-reliability index and low vulnerability index performed better among other evolutionary algorithms.

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