scholarly journals An optimal algorithm for cascaded reservoir operation by combining the grey forecasting model with DDDP

2017 ◽  
Vol 18 (1) ◽  
pp. 142-150 ◽  
Author(s):  
Yong Peng ◽  
Xiaoli Zhang ◽  
Wei Xu ◽  
Yajun Shi ◽  
Zixin Zhang
Keyword(s):  
Power Generation ◽  
Dynamic Programming ◽  
Reservoir Operation ◽  
Optimal Algorithm ◽  
Computing Time ◽  
Forecasting Model ◽  
Differential Dynamic Programming ◽  
Reservoir System ◽  
Grey Forecasting ◽  
Grey Forecasting Model

Abstract The operation of cascaded reservoirs is a complex problem, and lots of algorithms have been developed for optimal cascaded reservoir operation. However, the existing algorithms usually have disadvantages such as the ‘curse of dimensionality’ and prematurity. This study proposes a grey discrete differential dynamic programming (GDDDP) algorithm for effectively optimizing the cascaded reservoir operation model, which is a combination of the grey forecasting model and discrete differential dynamic programming (DDDP). Additionally, a modification of the grey forecasting model is presented for better forecast accuracy. The proposed method is applied to optimize the Baishan-Fengman cascaded reservoir system in the northeast of China. The results show that GDDDP obtains more power generation than DDDP with less computing time in three cases, i.e., dry years, wet years and the whole series. Especially in the case of the whole series, the power generation of GDDDP is 2.13 MWH more than that of DDDP, while the computing time is decreased by 66,161 ms. Moreover, the power generation of GDDDP is comparable with that of dynamic programming but the computing time is much less. All these indicate GDDDP has high accuracy and efficiency, which implies that it is practicable for the operation of a cascaded reservoir system.

Study of a discrete grey forecasting model based on the quality cost characteristic curve

2017 ◽  
Vol 7 (3) ◽  
pp. 376-384 ◽  
Author(s):  
Wenjie Dong ◽  
Sifeng Liu ◽  
Zhigeng Fang ◽  
Xiaoyu Yang ◽  
Qian Hu ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Characteristic Curve ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Quality Level ◽  
Cost Models ◽  
Quality Cost ◽  
Content Type ◽  
Grey Forecasting ◽  
Grey Forecasting Model

Purpose The purpose of this paper is to clarify several commonly used quality cost models based on Juran’s characteristic curve. Through mathematical deduction, the lowest point of quality cost and the lowest level of quality level (often depicted by qualification rate) can be obtained. This paper also aims to introduce a new prediction model, namely discrete grey model (DGM), to forecast the changing trend of quality cost. Design/methodology/approach This paper comes to the conclusion by means of mathematical deduction. To make it more clear, the authors get the lowest quality level and the lowest quality cost by taking the derivative of the equation of quality cost and quality level. By introducing the weakening buffer operator, the authors can significantly improve the prediction accuracy of DGM. Findings This paper demonstrates that DGM can be used to forecast quality cost based on Juran’s cost characteristic curve, especially when the authors do not have much information or the sample capacity is rather small. When operated by practical weakening buffer operator, the randomness of time series can be obviously weakened and the prediction accuracy can be significantly improved. Practical implications This paper uses a real case from a literature to verify the validity of discrete grey forecasting model, getting the conclusion that there is a certain degree of feasibility and rationality of DGM to forecast the variation tendency of quality cost. Originality/value This paper perfects the theory of quality cost based on Juran’s characteristic curve and expands the scope of application of grey system theory.

A comparative study of univariate models for container throughput forecasting of major ports in Asia

2021 ◽  
pp. 147509022110236
Author(s):  
Juan Huang ◽  
Ching-Wu Chu ◽  
Hsiu-Li Hsu
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Forecasting Model ◽  
Short Term ◽  
Autoregressive Integrated Moving Average ◽  
Port Authorities ◽  
Grey Forecasting ◽  
Grey Forecasting Model ◽  
Short Term Forecasting ◽  
Trigonometric Regression

This study aims to make comparisons on different univariate forecasting methods and provides a more accurate short-term forecasting model on the container throughput for rendering a reference to relevant authorities. We collected monthly data regarding container throughput volumes for three major ports in Asia, Shanghai, Singapore, and Busan Ports. Six different univariate methods, including the grey forecasting model, the hybrid grey forecasting model, the multiplicative decomposition model, the trigonometric regression model, the regression model with seasonal dummy variables, and the seasonal autoregressive integrated moving average (SARIMA) model, were used. We found that the hybrid grey forecasting model outperforms the other univariate models. This study’s findings can provide a more accurate short-term forecasting model for container throughput to create a reference for port authorities.

scholarly journals A New Reservoir Operation Chart Drawing Method Based on Dynamic Programming

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3355 ◽  
Author(s):  
Zhiqiang Jiang ◽  
Yaqi Qiao ◽  
Yuyun Chen ◽  
Changming Ji
Keyword(s):  
Power Generation ◽  
Dynamic Programming ◽  
Global Convergence ◽  
Local Convergence ◽  
Reservoir Operation ◽  
Optimization Methods ◽  
Simulation Results ◽  
Conventional Methods ◽  
Drawing Method ◽  
New Reservoir

A reservoir operation chart is an important tool in guiding actual reservoir operation at present. There are mainly two kinds of methods in drawing the operation chart, i.e., conventional methods and optimization methods, but each of them has some shortcomings, such as the repeated empirical inspection and correction of conventional methods, and the sensitivity to the initial trajectories of some optimization algorithms. In view of this, based on the principle of dynamic programming (DP), this paper coupled the reservoir operation chart drawing model and the DP model, and proposed a new reservoir operation chart drawing method which has no empirical inspection and correction, no requirement for initial solution, no problem of premature convergence and local convergence. In addition, this method can guarantee the global convergence of the results to a certain extent because of the global convergence of DP. Ya Yangshan reservoir in the Li Xianjiang River of China was selected as the research object to derive the operation chart by the drawing method. The simulation results show that the proposed method in this paper presents better performance compared with the conventional method on power generation, guaranteed output, and assurance rate, especially on the latter, which has a 2.68% increase. In addition, compared with the deterministic optimization results of DP, it is found that the results of the proposed method are very close to that of deterministic DP, the differences are only 1.8 GWh (0.36% decline) and 1.6 GWh (0.32% decline). So, the validity and rationality of the proposed method are further verified by the simulation results.

Vulnerability of hydropower generation to climate change in China: Results based on Grey forecasting model

Energy Policy ◽  
2014 ◽  
Vol 65 ◽  
pp. 701-707 ◽  
Author(s):  
Bing Wang ◽  
Xiao-Jie Liang ◽  
Hao Zhang ◽  
Lu Wang ◽  
Yi-Ming Wei
Keyword(s):  
Climate Change ◽  
Forecasting Model ◽  
Hydropower Generation ◽  
Grey Forecasting ◽  
Grey Forecasting Model
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