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Title of Thesis  
MATHEMATICAL MODELING FOR GENERATING SYNTHETIC VALUES TO BE USED IN NON-CONVENTIONAL ENERGY SYSTEMS  
Author(s)  
LALARUKH KAMAL  
Institute/University/Department Details  
University of Balochistan  
Status (Published/ Not Published/ In Press etc)  
Published  
Date of Publishing  
2001  
Subject  
Mathematics  
Number of Pages  
161  
   
Keywords (Extracted from title, table of contents and abstract of thesis)  
Mathematical Modeling, Non-Conventional Energy Systems, Non-Conventional Energy, Solar Radiation, Wind speed, Markov transition, Matrix (MTM), Autogressive moving average (ARMA), Autoregressive integrated moving average (ARIMA), Wind energy,  

 

 
Abstract  

After having reviewed, all the existing deterministic and stochastic models, being used currently, allover the world, to generate data for non-conventional energy systems, a need was felt for appropriate mathematical models to generate solar radiation and wind speed for realistic operating conditions for energy systems, by mathematical equations characterizing the deterministic and the stochastic components of the long term measured records, specially from the point of view of our country, Pakistan. Stochastic modeling of hourly global solar radiation; Markov transition matrix (MTM) model; triangulation method (modified Angstrom model) for mean monthly daily global solar radiations; autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models for wind; discrete state stochastic simulation of daily averaged wind speed; simulation of wind energy for different wind turbines are the models, which we fitted and tested their validity for solar and wind data of different cities of Pakistan. The generation of synthetic sequences using these models was also done and the results obtained by these models were compared. Using stochastic modeling of hourly global solar radiation, AR(l) models give the best results showing good agreement between generated and observed solar data. MTM approach to generate hourly averaged global radiation led to a reliable simulator. The method of triangulation was found better than any single regression equation methods. For generation of wind data, ARMA(2, 0) ARMA(2, 2); ARMA(l, 0) and ARMA(2, 0) are the best fitted models for winter, spring, summer and autumn respectively. The time series model, which we used to generate wind power for different turbines, suggested MOD2 turbines, the best suited for the coastal area considered.

 
   
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Sr.No Chapter Table of Contents
 
viii 180.kbs
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1 1

INTRODUCTION

1
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1.1

Non-Conventional Energy: An Introduction

 2
1.2 Critical Review 26
2 2 METHODOLOGIES, RESULTS AND DISCUSSIONS 40
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 2.1 Stochastic modeling and generation of synthetic sequences Hourly Global solar radiation  42
 2.2 Markov Transition Matrices (MTM)  52
 2.3 Triangulation method (modified Angstrom model) for mean Monthly daily global solar radiations  64
 2.4 ARMA and ARIMA models for generating wind speed  78
 2.5 Discrete state stochastic simulation of daily averaged wind speed  95
 2.6 Simulation of wind energy for different wind turbines  106
3 3 CONCLUSIONS AND FUTURE WORK 119
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 3.1 Conclusions  120
 3.2 Future work  125
4 4 REFERENCES 128-161
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