Open AccessJournal Article
Application of two multi-dimensional dynamic programming algorithms in optimization of cascade reservoirs operation
7
TL;DR: It is concluded that the multilayer nested dynamic programming algorithm is superi-or to the group traversal dynamic Programming algorithm in the aspects of programming complexity and memory usage, but inferior in terms of run-time.
read more
Abstract: In view of the no global convergence problem to most of the improved dynamic programming al-gorithm and intelligent optimization algorithm in the application of cascade reservoirs joint operation optimiza-tion at present,two calculating modes of the multi-dimensional dynamic programming algorithm have beenproposed in this paper based on the idea of group traversal and multilayer nested structure Comparisonand analysis of the two methods were carried out in terms of memory usage,computation complexity andrun time Taking cascade reservoirs distributed in the Lixianjiang River basin as the research backgroundfor practical calculation,it is concluded that the multilayer nested dynamic programming algorithm is superi-or to the group traversal dynamic programming algorithm in the aspects of programming complexity andmemory usage,but inferior in terms of run-time In order to improve the computation efficiency of multilay-er nested dynamic programming algorithm, combination of this method with the parallel computation isshown in this paper,and case study shows that the parallel computing can ease the defect of long run-time to a certain extent
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Modeling and Solving of Joint Flood Control Operation of Large-Scale Reservoirs: A Case Study in the Middle and Upper Yangtze River in China
TL;DR: Wang et al. as mentioned in this paper proposed a large-scale reservoir flood control operation modeling method using Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods.
16
The Hydropower Station Output Function and its Application in Reservoir Operation
TL;DR: The improved DP based on HSOF can reduce the programming complexity of DP, thus effectively alleviates the time-consuming problem and in the meantime, keeps the global convergence feature of DP.
9
Model predictive control for multi-zone Variable Air Volume systems based on artificial neural networks
TL;DR: In this article , an artificial neural network (ANN) based system-level model predictive control framework is established for a variable air volume (VAV) system to improve its robustness and energy efficiency.
4
Research on Reservoir Optimal Operation Based on Long-Term and Mid-Long-Term Nested Models
TL;DR: In this article , a multi-objective optimal operation nested model of reservoirs is proposed to solve the problem that the existing optimal operation model cannot coordinate the contradiction between long-term and short-term benefits.
References
Modeling and Solving of Joint Flood Control Operation of Large-Scale Reservoirs: A Case Study in the Middle and Upper Yangtze River in China
TL;DR: Wang et al. as mentioned in this paper proposed a large-scale reservoir flood control operation modeling method using Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods.
16
The Hydropower Station Output Function and its Application in Reservoir Operation
TL;DR: The improved DP based on HSOF can reduce the programming complexity of DP, thus effectively alleviates the time-consuming problem and in the meantime, keeps the global convergence feature of DP.
9
The application of improved cuckoo search in cascade reservoir power generation optimized operation
TL;DR: An improved cuckoo algorithm is proposed that features a new neighbour sequence algorithm for global search and a variable neighbourhood descent algorithm for local search, and is applied to optimizing the operation of cascade reservoir power generation.