A trade-off analysis of adaptive and non-adaptive future optimized rule curves based on simulation algorithm and hedging rules

2022 ◽  
Author(s):  
Mahnoosh Moghaddasi ◽  
Sedigheh Anvari ◽  
Najemeh Akhondi
Keyword(s):  
Simulation Algorithm ◽  
Trade Off ◽  
Rule Curves ◽  
Hedging Rules

scholarly journals Multiobjective water resources systems analysis using genetic algorithms - application to Chou-Shui River Basin, Taiwan

2003 ◽  
Vol 48 (10) ◽  
pp. 71-77 ◽  
Author(s):  
J.-T. Kuo ◽  
W.-C. Cheng ◽  
L. Chen
Keyword(s):  
Genetic Algorithms ◽  
Water Supply ◽  
River Basin ◽  
Research Work ◽  
Weighting Method ◽  
Trade Off ◽  
Water Resources Systems ◽  
Weighting Factors ◽  
Rule Curves ◽  
Central Taiwan

Multipurpose operation is adopted by most reservoirs in Taiwan in order to maximize the benefits of power generation, water supply, irrigation and recreational purposes. A multiobjective approach can be used to obtain trade-off curves among these multipurpose targets. The weighting method, in which different weighting factors are used for different purposes, was used in this research work. In Taiwan, most major reservoirs are operated by rule curves. Genetic algorithms with characteristics of artificial intelligence were applied to obtain the optimal rule curves of the multireservoir system under multipurpose operation in Chou-Shui River Basin in central Taiwan. The model results reveal that different shapes of rule curves under different weighting factors on targets can be efficiently obtained by genetic algorithms. Pareto optimal solutions for a trade-off between water supply and hydropower were obtained and analyzed.

Optimization of Conventional Rule Curves Coupled with Hedging Rules for Reservoir Operation

2014 ◽  
Vol 140 (5) ◽  
pp. 693-698 ◽  
Author(s):  
Mehrdad Taghian ◽  
Dan Rosbjerg ◽  
Ali Haghighi ◽  
Henrik Madsen
Keyword(s):  
Reservoir Operation ◽  
Rule Curves ◽  
Hedging Rules

scholarly journals Genetic algorithms optimization of hedging rules for operation of the multi-purpose Ubonratana Reservoir in Thailand

2014 ◽  
Vol 364 ◽  
pp. 507-512 ◽  
Author(s):  
C. Chiamsathit ◽  
A. J. Adeloye ◽  
B. Soudharajan
Keyword(s):  
Genetic Algorithm ◽  
Critical Level ◽  
Water Shortages ◽  
Reservoir Performance ◽  
Rule Curves ◽  
Decision Variables ◽  
Rule Curve ◽  
Hedging Policy ◽  
Hedging Rules ◽  
Northeastern Thailand

Abstract. This study has developed optimal hedging policies for the multi-purpose Ubonratana Reservoir in northeastern Thailand based on its existing rule curves. The hedging policy was applied whenever the reservoir storage falls below a critical level for each month of the year. The decision variables, i.e. the set of monthly storages defining the critical rule curve that triggers rationing and the rationing ratio, were optimized by genetic algorithm (GA). Both single stage (i.e. with one critical rule curve and one rationing ratio) and two-stage (with two critical rule curves and ratios) of the hedging policy were considered in the optimization. To test the effect of the optimized hedging policies on reservoir performance, simulations were carried out, forced alternatively with the existing rule curves (i.e. without hedging) and the two optimized hedging policies. Performance was summarized in terms of reliability (time- and volume-based) and vulnerability. The results showed that the vulnerability was significantly reduced by using the optimized hedging rules. However, the number of water shortages increased with the optimized rules, causing the time-based reliability to worsen significantly. This should not be of concern since, although the number of shortages increased, the associated shortage quantities on most of these additional occasions were small, leaving the volumetric reliability largely unchanged.

A Flow-Preserving Algorithm for the Time-Cost Trade-Off Problem

1982 ◽  
Vol 14 (2) ◽  
pp. 109-113 ◽  
Author(s):  
Suleyman Tufekci
Keyword(s):  
Time Cost ◽  
Trade Off

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

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