Optimal power flow in distribution networks under stochastic N−1 disruptions
It is important to include contingencies in operations and have a post-contingency recovery plan for distribution systems, akin to transmission systems. We consider a multi-period optimal power flow (OPF) problem in distribution systems subject to stochastic N−1 contingency (disruption) in a distrib...
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| Published in: | Electric power systems research Vol. 189; no. C; p. 106689 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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01-12-2020
Elsevier Science Ltd Elsevier |
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| Abstract | It is important to include contingencies in operations and have a post-contingency recovery plan for distribution systems, akin to transmission systems. We consider a multi-period optimal power flow (OPF) problem in distribution systems subject to stochastic N−1 contingency (disruption) in a distribution line or a distributed energy resource. The disruption is stochastic in nature, a type of infrequent event with random magnitude and timing, and that every disruption typically has an associated recovery time. We formulate a multi-stage stochastic convex program, considering modeling features like linearized AC power flow physics, engineering limits and battery devices with efficiencies curves, and develop an efficient decomposition algorithm. We demonstrate the computational effectiveness of our algorithm over the extensive formulation and show that the stochastic-disruption-aware operating costs can be 60% cheaper than the deterministic counterparts. |
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| AbstractList | It is important to include contingencies in operations and have a post-contingency recovery plan for distribution systems, akin to transmission systems. We consider a multi-period optimal power flow (OPF) problem in distribution systems subject to stochastic N−1 contingency (disruption) in a distribution line or a distributed energy resource. The disruption is stochastic in nature, a type of infrequent event with random magnitude and timing, and that every disruption typically has an associated recovery time. We formulate a multi-stage stochastic convex program, considering modeling features like linearized AC power flow physics, engineering limits and battery devices with efficiencies curves, and develop an efficient decomposition algorithm. We demonstrate the computational effectiveness of our algorithm over the extensive formulation and show that the stochastic-disruption-aware operating costs can be 60% cheaper than the deterministic counterparts. It is important to include contingencies in operations and have a post-contingency recovery plan for distribution systems, akin to transmission systems. We consider a multi-period optimal power flow (OPF) problem in distribution systems subject to stochastic N - 1 contingency (disruption) in a distribution line or a distributed energy resource. The disruption is stochastic in nature, a type of infrequent event with random magnitude and timing, and that every disruption typically has an associated recovery time. We formulate a multi-stage stochastic convex program, considering modeling features like linearized AC power flow physics, engineering limits and battery devices with efficiencies curves, and develop an efficient decomposition algorithm. We demonstrate the computational effectiveness of our algorithm over the extensive formulation and show that the stochastic-disruption-aware operating costs can be 60% cheaper than the deterministic counterparts. |
| ArticleNumber | 106689 |
| Author | Nagarajan, Harsha Yang, Haoxiang |
| Author_xml | – sequence: 1 givenname: Haoxiang surname: Yang fullname: Yang, Haoxiang – sequence: 2 givenname: Harsha orcidid: 0000-0002-1210-8428 surname: Nagarajan fullname: Nagarajan, Harsha email: harsha@lanl.gov |
| BackLink | https://www.osti.gov/biblio/2279443$$D View this record in Osti.gov |
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| Cites_doi | 10.1109/TPWRS.2017.2748060 10.1016/j.orl.2008.01.013 10.1016/j.energy.2019.05.119 10.1287/moor.2014.0664 10.1137/15M1020575 10.1016/j.ejor.2018.10.033 10.1016/j.epsr.2019.02.012 10.1109/TSG.2017.2715074 10.1109/MPE.2015.2397337 10.1109/TSG.2015.2388736 10.1016/j.ejor.2010.08.007 10.5711/morj.14.2.19 10.1109/TSG.2015.2513048 10.1109/TPWRS.2020.2973596 10.1109/TAC.2014.2332712 10.1007/BF01582895 |
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| Keywords | Multi-stage stochastic program OPF Recovery Distribution network N−1 contingency Stochastic disruption |
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Power Syst. doi: 10.1109/TPWRS.2020.2973596 contributor: fullname: Babaei – volume: 60 start-page: 72 issue: 1 year: 2014 ident: 10.1016/j.epsr.2020.106689_bib0015 article-title: Exact convex relaxation of optimal power flow in radial networks publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2014.2332712 contributor: fullname: Gan – volume: 52 start-page: 359 issue: 1–3 year: 1991 ident: 10.1016/j.epsr.2020.106689_bib0018 article-title: Multi-stage stochastic optimization applied to energy planning publication-title: Math. Program. doi: 10.1007/BF01582895 contributor: fullname: Pereira – year: 2017 ident: 10.1016/j.epsr.2020.106689_sbref0018 article-title: SDDP.jl: a Julia package for stochastic dual dynamic programming publication-title: Optimization Online contributor: fullname: Dowson |
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| SubjectTerms | [formula omitted] contingency Algorithms Batteries Contingency Disruption Distributed generation Distribution network Electric power distribution Electricity distribution Energy sources Heat recovery systems Multi-stage stochastic program OPF Power flow Recovery Recovery time Stochastic disruption Stochastic models |
| Title | Optimal power flow in distribution networks under stochastic N−1 disruptions |
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