scholarly journals Compromise Mixed Allocation in Multivariate Stratified Sampling Using Dynamic Programming Technique

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
A. H. Ansari ◽  
◽  
Rahul Varshney ◽  
M. J. Ahsan ◽  
◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Stratified Sampling ◽  
Programming Technique ◽  
Multivariate Stratified Sampling

scholarly journals A note on optimum allocation in multivariate stratified sampling

2003 ◽  
Vol 21 (1) ◽  
pp. 91 ◽  
Author(s):  
M. G. M. Khan ◽  
M. J. Ahsan
Keyword(s):  
Dynamic Programming ◽  
Random Sampling ◽  
Decision Problem ◽  
Stratified Random Sampling ◽  
Nonlinear Programming Problem ◽  
Programming Technique ◽  
Population Means ◽  
Compromise Allocation ◽  
Multivariate Stratified Sampling ◽  
Sampling Cost

In stratified random sampling when several characteristics are to be estimated simultaneously, an allocation that is optimum for one characteristic may be far away from optimum for others. To resolve this conflict the authors formulate the problem of determining optimum compromise allocation as a nonlinear programming problem (NLPP). The allocation obtained is optimum in the sense that it minimizes the sum of weighted variances of the estimated population means of the characteristics subject to a fixed sampling cost. The formulated NLPP is treated as multistage decision problem and solved using dynamic programming technique. A numerical example is presented to illustrate the computational details.

scholarly journals Dynamic Operation Management of a Renewable Microgrid including Battery Energy Storage

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Shaozhen Jin ◽  
Zhizhong Mao ◽  
Hongru Li ◽  
Wenhai Qi
Keyword(s):  
Dynamic Programming ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Main Idea ◽  
Optimal Operation ◽  
Optimal Control Strategy ◽  
Programming Technique ◽  
Battery Energy Storage ◽  
Comparison Results ◽  
Battery Energy

In this paper, a novel dynamic programming technique is presented for optimal operation of a typical renewable microgrid including battery energy storage. The main idea is to use the scenarios analysis technique to proceed the uncertainties related to the available output power of wind and photovoltaic units and dynamic programming technique to obtain the optimal control strategy for a renewable microgrid system in a finite time period. First, to properly model the system, a mathematical model including power losses of the renewable microgrid is established, where the uncertainties due to the fluctuating generation from renewable energy sources are considered. Next, considering the dynamic power constraints of the battery, a new performance index function is established, where the Lagrange multipliers and interior point method will be presented for the equality and inequality operation constraints. Then, a feedback control scheme based on the dynamic programming is proposed to solve the model and obtain the optimal solution. Finally, simulation and comparison results are given to illustrate the performance of the presented method.

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