Efficiently Including Time and Voltage Variability of Loads in Optimization of Distribution Systems Topology
The reconfiguration of distribution networks results in modifications to the voltage magnitudes of buses, subsequently influencing the power demands of connected loads. This variable load demand plays a pivotal role in determining the optimal system topology. While a few studies have recognized this...
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Published in | IEEE transactions on industry applications Vol. 60; no. 5; pp. 7470 - 7480 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.09.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | The reconfiguration of distribution networks results in modifications to the voltage magnitudes of buses, subsequently influencing the power demands of connected loads. This variable load demand plays a pivotal role in determining the optimal system topology. While a few studies have recognized this crucial aspect, they often present non-linear models or simplified formulations. Non-linear models, though solvable with commercial solvers, demand extensive computational time, particularly when accommodating the time variability of loads in the formulation. Alternatively, solving these models may require meta-heuristic methods, introducing the challenge of obtaining precise solutions. In contrast, existing linear models have been subject to approximation through piecewise linearization, introducing a level of uncertainty. Achieving accurate solutions for reconfiguration problems within a short computational timeframe is imperative for practical operational applications. As a result, present study addresses this challenge by introducing four effective reconfiguration methods that explicitly consider the voltage dependence of time-varying loads. These techniques leverage linear solvers, enabling the computation of precise solutions within a condensed computational timeframe. By adopting these proposed methods, the study aims to enhance the efficiency and accuracy of solving distribution network reconfiguration problems, thereby facilitating practical applications in real-time operational scenarios. The linear mathematical models introduced in the current study can find exact solutions in a short computational time, unlike meta-heuristic algorithms and non-linear formulations. Additionally, the proposed time and voltage variability formulation causes the presented reconfiguration frameworks to solve the problem in very low computational time compared to models with exact load variations inclusion. |
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AbstractList | The reconfiguration of distribution networks results in modifications to the voltage magnitudes of buses, subsequently influencing the power demands of connected loads. This variable load demand plays a pivotal role in determining the optimal system topology. While a few studies have recognized this crucial aspect, they often present non-linear models or simplified formulations. Non-linear models, though solvable with commercial solvers, demand extensive computational time, particularly when accommodating the time variability of loads in the formulation. Alternatively, solving these models may require meta-heuristic methods, introducing the challenge of obtaining precise solutions. In contrast, existing linear models have been subject to approximation through piecewise linearization, introducing a level of uncertainty. Achieving accurate solutions for reconfiguration problems within a short computational timeframe is imperative for practical operational applications. As a result, present study addresses this challenge by introducing four effective reconfiguration methods that explicitly consider the voltage dependence of time-varying loads. These techniques leverage linear solvers, enabling the computation of precise solutions within a condensed computational timeframe. By adopting these proposed methods, the study aims to enhance the efficiency and accuracy of solving distribution network reconfiguration problems, thereby facilitating practical applications in real-time operational scenarios. The linear mathematical models introduced in the current study can find exact solutions in a short computational time, unlike meta-heuristic algorithms and non-linear formulations. Additionally, the proposed time and voltage variability formulation causes the presented reconfiguration frameworks to solve the problem in very low computational time compared to models with exact load variations inclusion. |
Author | Jurado, Francisco Schmitt, Konrad Chamana, Manohar Marfo, Emmanuel Attah Mahdavi, Meisam Awaafo, Augustine Bayne, Stephen |
Author_xml | – sequence: 1 givenname: Meisam orcidid: 0000-0002-0454-5484 surname: Mahdavi fullname: Mahdavi, Meisam email: mmahdavi@ieee.org organization: Department of Electrical Engineering, University of Jaen, Jaen, Spain – sequence: 2 givenname: Augustine orcidid: 0009-0009-1026-1144 surname: Awaafo fullname: Awaafo, Augustine email: aa000145@red.ujaen.es organization: Department of Electrical Engineering, University of Jaen, Jaen, Spain – sequence: 3 givenname: Francisco orcidid: 0000-0001-8122-7415 surname: Jurado fullname: Jurado, Francisco email: fjurado@ujaen.es organization: Department of Electrical Engineering, University of Jaen, Jaen, Spain – sequence: 4 givenname: Emmanuel Attah orcidid: 0009-0003-7815-9572 surname: Marfo fullname: Marfo, Emmanuel Attah email: eamarfo1@aggies.ncat.edu organization: Electrical and Computer Engineering Department, North Carolina A&T State University, Greensboro, NC, USA – sequence: 5 givenname: Manohar orcidid: 0000-0002-5368-910X surname: Chamana fullname: Chamana, Manohar email: m.chamana@ttu.edu organization: National Wind Institute, Texas Tech University, Lubbock, TX, USA – sequence: 6 givenname: Konrad orcidid: 0000-0002-4595-3900 surname: Schmitt fullname: Schmitt, Konrad email: konradkorkschmitt@ieee.org organization: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USA – sequence: 7 givenname: Stephen orcidid: 0000-0002-7789-1820 surname: Bayne fullname: Bayne, Stephen email: stephen.bayne@ttu.edu organization: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USA |
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SubjectTerms | Algorithms Computational modeling Computing time Distribution efficiency enhancement Electric potential Exact solutions fluctuations in demand Heuristic methods influence of voltage on load power Load fluctuation Load modeling Mathematical analysis Mathematical models Network topologies optimal topology radial feeders Reactive power Real time operation Reconfiguration Solvers Time dependence Time-varying systems Topology Topology optimization Variability Voltage |
Title | Efficiently Including Time and Voltage Variability of Loads in Optimization of Distribution Systems Topology |
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