Model predictive control based optimal energy management considering the effect of battery aging

In recent years, energy supply from renewable energy sources (RESs) is a main trend towards future smart grid. Many countries including Singapore have increased their energy supply from RESs. However, power fluctuation can become more severe and unpredictable with the increase of RESs, which brings...

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Main Author: Zhang, Lingxi
Other Authors: Gooi Hoay Beng
Format: Theses and Dissertations
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/10356/72610
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-726102023-07-04T15:05:34Z Model predictive control based optimal energy management considering the effect of battery aging Zhang, Lingxi Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In recent years, energy supply from renewable energy sources (RESs) is a main trend towards future smart grid. Many countries including Singapore have increased their energy supply from RESs. However, power fluctuation can become more severe and unpredictable with the increase of RESs, which brings risk to the stability and reliability of power systems. To address the problem, more battery energy storage systems (BESSs) are connected to modern power systems. The optimal power coordination among different energy resources considering lifespan of BESSs is crucial. The author first establishes a state space model for the aging effect of lithium-ion battery. The effect of battery is later used as constraints for control. Then, the objectives are divided into two categories, long-time-scale and short-time-scale applications. The roles of BESSs in these applications are respectively investigated. For long-time-scale applications, peak load shifting is studied because it can save energy and reduce energy cost. For short-time-scale applications, the author focuses on real-time power balancing and power smoothing. There are two kinds of approaches, conventional PI (proportional–integral) controller and MPC (Model Predictive Control). They are studied and simulated separately. Finally, the comparison between them demonstrates the advantages of the proposed MPC approach. The key idea of this dissertation is to maintain system stability according to the swing equation. Meanwhile we keep batteries in the optimal status. The significance of this study can be summarized as the pursuit of secure and economical operation of a power system. Key words: BESS, battery aging effect, MPC, load frequency control Master of Science (Power Engineering) 2017-08-30T06:17:33Z 2017-08-30T06:17:33Z 2017 Thesis http://hdl.handle.net/10356/72610 en 70 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::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Zhang, Lingxi
Model predictive control based optimal energy management considering the effect of battery aging
description In recent years, energy supply from renewable energy sources (RESs) is a main trend towards future smart grid. Many countries including Singapore have increased their energy supply from RESs. However, power fluctuation can become more severe and unpredictable with the increase of RESs, which brings risk to the stability and reliability of power systems. To address the problem, more battery energy storage systems (BESSs) are connected to modern power systems. The optimal power coordination among different energy resources considering lifespan of BESSs is crucial. The author first establishes a state space model for the aging effect of lithium-ion battery. The effect of battery is later used as constraints for control. Then, the objectives are divided into two categories, long-time-scale and short-time-scale applications. The roles of BESSs in these applications are respectively investigated. For long-time-scale applications, peak load shifting is studied because it can save energy and reduce energy cost. For short-time-scale applications, the author focuses on real-time power balancing and power smoothing. There are two kinds of approaches, conventional PI (proportional–integral) controller and MPC (Model Predictive Control). They are studied and simulated separately. Finally, the comparison between them demonstrates the advantages of the proposed MPC approach. The key idea of this dissertation is to maintain system stability according to the swing equation. Meanwhile we keep batteries in the optimal status. The significance of this study can be summarized as the pursuit of secure and economical operation of a power system. Key words: BESS, battery aging effect, MPC, load frequency control
author2 Gooi Hoay Beng
author_facet Gooi Hoay Beng
Zhang, Lingxi
format Theses and Dissertations
author Zhang, Lingxi
author_sort Zhang, Lingxi
title Model predictive control based optimal energy management considering the effect of battery aging
title_short Model predictive control based optimal energy management considering the effect of battery aging
title_full Model predictive control based optimal energy management considering the effect of battery aging
title_fullStr Model predictive control based optimal energy management considering the effect of battery aging
title_full_unstemmed Model predictive control based optimal energy management considering the effect of battery aging
title_sort model predictive control based optimal energy management considering the effect of battery aging
publishDate 2017
url http://hdl.handle.net/10356/72610
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