Distributed economic dispatch for smart grid system based on Nesterov gradient method

Economic dispatch (ED) is considered as one of well-studied and key problems in the power system research. For solving ED problems normally we have centralized methods (CM) and distributed methods (DM) that can obtain the optimal solution. CM and DM have their own advantages and disadvantages, wher...

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Main Author: Zhao, Chen
Other Authors: Wen Changyun
Format: Final Year Project
Language:English
Published: 2016
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Online Access:http://hdl.handle.net/10356/67780
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-677802023-07-07T16:58:35Z Distributed economic dispatch for smart grid system based on Nesterov gradient method Zhao, Chen Wen Changyun School of Electrical and Electronic Engineering DRNTU::Engineering Economic dispatch (ED) is considered as one of well-studied and key problems in the power system research. For solving ED problems normally we have centralized methods (CM) and distributed methods (DM) that can obtain the optimal solution. CM and DM have their own advantages and disadvantages, whereas the future treads will focus more on distributed methods. By decomposing centralized optimization into optimizations at local agents, an algorithm is developed for each agent to iteratively estimate a solution of the optimization problem in a distributed manner with limited communication among neighbors. In this report, it will present several methods especially a distributed economic dispatch strategy based on Nesterov gradient method for the smart grid systems. With the supports of appropriate mathematics functions and algorithms, this new distributed method will be more flexible and give a faster response, which helps the power system dispatching process more economical, efficient and effective. Bachelor of Engineering 2016-05-20T07:25:53Z 2016-05-20T07:25:53Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67780 en Nanyang Technological University 66 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Zhao, Chen
Distributed economic dispatch for smart grid system based on Nesterov gradient method
description Economic dispatch (ED) is considered as one of well-studied and key problems in the power system research. For solving ED problems normally we have centralized methods (CM) and distributed methods (DM) that can obtain the optimal solution. CM and DM have their own advantages and disadvantages, whereas the future treads will focus more on distributed methods. By decomposing centralized optimization into optimizations at local agents, an algorithm is developed for each agent to iteratively estimate a solution of the optimization problem in a distributed manner with limited communication among neighbors. In this report, it will present several methods especially a distributed economic dispatch strategy based on Nesterov gradient method for the smart grid systems. With the supports of appropriate mathematics functions and algorithms, this new distributed method will be more flexible and give a faster response, which helps the power system dispatching process more economical, efficient and effective.
author2 Wen Changyun
author_facet Wen Changyun
Zhao, Chen
format Final Year Project
author Zhao, Chen
author_sort Zhao, Chen
title Distributed economic dispatch for smart grid system based on Nesterov gradient method
title_short Distributed economic dispatch for smart grid system based on Nesterov gradient method
title_full Distributed economic dispatch for smart grid system based on Nesterov gradient method
title_fullStr Distributed economic dispatch for smart grid system based on Nesterov gradient method
title_full_unstemmed Distributed economic dispatch for smart grid system based on Nesterov gradient method
title_sort distributed economic dispatch for smart grid system based on nesterov gradient method
publishDate 2016
url http://hdl.handle.net/10356/67780
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