Dynamic programming with the principle of progressive optimality for searching rule curves

2007 ◽  
Vol 34 (2) ◽  
pp. 170-176 ◽  
Author(s):  
C Chaleeraktrakoon ◽  
A Kangrang

Rule curves are monthly reservoir-operation guidelines for meeting the minimum of water shortage over the long run. This paper proposes a dynamic programming (DP) approach for finding the optimal rule curves of single- and multi-reservoir systems. The proposed DP approach uses a traditional DP technique conditionally and applies the principle of progressive optimality (PPO) to search its optimal solutions. The proposed DP–PPO approach is suitable because of the multi-stage, nonlinear, and continuous-type characteristics of the rule curve search. Its dimensionality is relatively small, as compared with that of the traditional one. Results of an illustrative application to a multi-reservoir system under two different initial feasible solutions (i.e., new or existing reservoirs) have demonstrated that the DP–PPO approach is generally fast and robust. Its convergence varies only slightly, according to the initial conditions.Key words: rule curves, principle of progressive optimality, dynamic programming (DP), monthly reservoir operation.

2012 ◽  
Vol 15 (1) ◽  
pp. 155-173 ◽  
Author(s):  
R. Moeini ◽  
M. H. Afshar

This paper extends the application of Constrained Ant Colony Optimization Algorithms (CACOAs) to optimal operation of multi-reservoir systems. Three different formulations of the constrained Ant Colony Optimization (ACO) are outlined here using Max-Min Ant System for the solution of multi-reservoir operation problems. In the first two versions, called Partially Constrained ACO algorithms, the constraints of the multi-reservoir operation problems are satisfied partially. In the third formulation, all the constraints of the underlying problem are implicitly satisfied by the provision of tabu lists to the ants which contain only feasible options. The ants are, therefore, forced to construct feasible solutions and hence the method is referred to as a Fully Constrained ACO algorithm. The proposed constrained ACO algorithms are formulated for both possible cases of taking storage/release volumes as the decision variables of the problem. The proposed methods are used to optimally solve the well-known problems of four- and ten-reservoir operations and the results are presented and compared with those of the conventional unconstrained ACO algorithm and existing methods in the literature. The results indicate the superiority of the proposed methods over conventional ACOs and existing methods to optimally solve large scale multi-reservoir operation problems.


2014 ◽  
Vol 915-916 ◽  
pp. 1452-1455 ◽  
Author(s):  
Yi Fan Ding ◽  
De Shan Tang ◽  
Zhen Zhu Meng

Rule curves are guidelines for long term reservoir operation. An efficient optimization technique is required to find the optimal rule curves that can mitigate water shortage in long-term operation. A new functional approach was proposed to search the optimal rule curves of reservoir. The results indicated that the situations of water shortage and excess release water of using the new approach are smaller than the situations of using the existing rule curves.


2010 ◽  
Vol 13 (1) ◽  
pp. 121-139 ◽  
Author(s):  
Abbas Afshar ◽  
Mahyar Shafii ◽  
Omid Bozorg Haddad

We present an improved version of Honey Bees Mating Optimization (HBMO) algorithm to develop operating rules for multi-reservoir systems. The performance of the proposed model is tested through sensitivity analysis and comparing the result with those of a real-coded Genetic Algorithm (GA) for a 60-month period single-reservoir operation problem. The improved model is subsequently employed to derive release rule and storage balancing functions which form operating policy for a multi-reservoir system along two case examples: (i) water supply and (ii) hydropower generation. The obtained operating rule curves can be used to guide the system operators in decision-making. These rule curves provide the operator with the opportunity to systematically look at the system and to make proper decisions. The obtained results showed that the optimization technique proposed in this study is capable of solving complex multi-reservoir systems operation problems. Moreover, the proposed structure properly handled the tight constraints defining the parallel reservoirs operation in such a way that all the generated solutions were feasible after a particular set of iterations. The proposed optimization algorithm of this study can be developed more in future to solve multi-modal optimization problems, and also to define operation policies for highly complex multi-reservoir systems.


2006 ◽  
Vol 53 (10) ◽  
pp. 317-325 ◽  
Author(s):  
J.-T. Kuo ◽  
N.-S. Hsu ◽  
S.-K. Chiu

Tien-Hua-Hu Reservoir is currently under planning by the Water Resources Agency, Taiwan to meet the increasing water demands of central Taiwan arising from rapid growth of domestic water supply, and high-tech industrial parks. This study develops a simulation model for the ten-day period reservoir operation to calculate the ten-day water shortage index under varying rule curves. A genetic algorithm is coupled to the simulation model to find the optimal rule curves using the minimum ten-day water shortage index as an objective function. This study generates many sets of synthetic streamflows for risk, reliability, resiliency, and vulnerability analyses of reservoir operation. ARMA and disaggregation models are developed and applied to the synthetic streamflow generation. The optimal rule curves obtained from this study perform better in the ten-day shortage index when compared to the originally designed rule curves from a previous study. The optimal rule curves are also superior to the originally designed rule curves in terms of vulnerability. However, in terms of reliability and resiliency, the optimal rule curves are inferior to the those originally designed. Results from this study have provided in general a set of improved rule curves for operation of the Tien-Hua-Hu Reservoir. Furthermore, results from reliability, resiliency and vulnerability analyses offer much useful information for decision making in reservoir operation.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 625
Author(s):  
Xinyu Wu ◽  
Rui Guo ◽  
Xilong Cheng ◽  
Chuntian Cheng

Simulation-optimization methods are often used to derive operation rules for large-scale hydropower reservoir systems. The solution of the simulation-optimization models is complex and time-consuming, for many interconnected variables need to be optimized, and the objective functions need to be computed through simulation in many periods. Since global solutions are seldom obtained, the initial solutions are important to the solution quality. In this paper, a two-stage method is proposed to derive operation rules for large-scale hydropower systems. In the first stage, the optimal operation model is simplified and solved using sampling stochastic dynamic programming (SSDP). In the second stage, the optimal operation model is solved by using a genetic algorithm, taking the SSDP solution as an individual in the initial population. The proposed method is applied to a hydropower system in Southwest China, composed of cascaded reservoir systems of Hongshui River, Lancang River, and Wu River. The numerical result shows that the two-stage method can significantly improve the solution in an acceptable solution time.


Author(s):  
A. Meghdari ◽  
H. Sayyaadi

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.


Author(s):  
Chen Wu ◽  
Yibo Wang ◽  
Jing Ji ◽  
Pan Liu ◽  
Liping Li ◽  
...  

Reservoirs play important roles in hydropower generation, flood control, water supply, and navigation. However, the regulation of reservoirs is challenged due to their adverse influences on river ecosystems. This study uses ecoflow as an ecological indicator for reservoir operation to indicate the extent of natural flow alteration. Three reservoir optimization models are established to derive ecological operating rule curves. Model 1 only considers the maximization of average annual hydropower generation and the assurance rate of hydropower generation. Model 2 incorporates ecological objectives and constraints. Model 3 not only considers the hydropower objectives but also simulates the runoff and calculates the ecological indicator values of multiple downstream stations. The three models are optimized by a simulation-optimization framework. The reservoir ecological operating rule curves are derived for the case study of China's Three Gorges Reservoir. The results represent feasible schemes for reservoir operation by considering both hydropower and ecological demands. The average annual power generation and assurance rate of a preferred optimized scheme for Model 3 are increased by 1.06% and 2.50%, respectively. Furthermore, ecological benefits of the three hydrologic stations are also improved. In summary, the ecological indicator ecoflow and optimization models could be helpful for reservoir ecological operations.


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