Optimization and Control of Power Flow in Distribution Networks

<p>Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale ad...

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Main Author: Farivar, Masoud
Format: Others
Published: 2016
Online Access:https://thesis.library.caltech.edu/9317/1/Masoud_Farivar_PhD_Thesis.pdf
Farivar, Masoud (2016) Optimization and Control of Power Flow in Distribution Networks. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9JW8BSM. https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773 <https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773>
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spelling ndltd-CALTECH-oai-thesis.library.caltech.edu-93172020-05-27T03:02:51Z Optimization and Control of Power Flow in Distribution Networks Farivar, Masoud <p>Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.</p> <p>Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.</p> <p>The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.</p> 2016 Thesis NonPeerReviewed application/pdf https://thesis.library.caltech.edu/9317/1/Masoud_Farivar_PhD_Thesis.pdf https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773 Farivar, Masoud (2016) Optimization and Control of Power Flow in Distribution Networks. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9JW8BSM. https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773 <https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773> https://thesis.library.caltech.edu/9317/
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description <p>Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.</p> <p>Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.</p> <p>The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.</p>
author Farivar, Masoud
spellingShingle Farivar, Masoud
Optimization and Control of Power Flow in Distribution Networks
author_facet Farivar, Masoud
author_sort Farivar, Masoud
title Optimization and Control of Power Flow in Distribution Networks
title_short Optimization and Control of Power Flow in Distribution Networks
title_full Optimization and Control of Power Flow in Distribution Networks
title_fullStr Optimization and Control of Power Flow in Distribution Networks
title_full_unstemmed Optimization and Control of Power Flow in Distribution Networks
title_sort optimization and control of power flow in distribution networks
publishDate 2016
url https://thesis.library.caltech.edu/9317/1/Masoud_Farivar_PhD_Thesis.pdf
Farivar, Masoud (2016) Optimization and Control of Power Flow in Distribution Networks. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9JW8BSM. https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773 <https://resolver.caltech.edu/CaltechTHESIS:12092015-021431773>
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