Real-Time Optimal Power Flow
Future power networks are expected to incorporate a large number of distributed energy resources, which introduce randomness and fluctuations as well as fast control capabilities. But traditional optimal power flow methods are only appropriate for applications that operate on a slow timescale. In th...
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| Veröffentlicht in: | IEEE transactions on smart grid 2017-11, Vol.8 (6), p.2963-2973 |
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| container_title | IEEE transactions on smart grid |
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| creator | Yujie Tang Dvijotham, Krishnamurthy Low, Steven |
| description | Future power networks are expected to incorporate a large number of distributed energy resources, which introduce randomness and fluctuations as well as fast control capabilities. But traditional optimal power flow methods are only appropriate for applications that operate on a slow timescale. In this paper, we build on recent work to develop a real-time algorithm for AC optimal power flow, based on quasi-Newton methods. The algorithm uses second-order information to provide suboptimal solutions on a fast timescale, and can be shown to track the optimal power flow solution when the estimated second-order information is sufficiently accurate. We also give a specific implementation based on L-BFGS-B method, and show by simulation that the proposed algorithm has good performance and is computationally efficient. |
| doi_str_mv | 10.1109/TSG.2017.2704922 |
| format | Article |
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We also give a specific implementation based on L-BFGS-B method, and show by simulation that the proposed algorithm has good performance and is computationally efficient.</description><subject>Algorithms</subject><subject>Computational modeling</subject><subject>Computer simulation</subject><subject>Cost function</subject><subject>Distributed generation</subject><subject>Energy sources</subject><subject>Heuristic algorithms</subject><subject>Mathematical model</subject><subject>Newton methods</subject><subject>Optimal power flow</subject><subject>Power flow</subject><subject>Power system stability</subject><subject>quasi-Newton method</subject><subject>Reactive power</subject><subject>Real time</subject><subject>Real-time systems</subject><subject>time-varying optimization</subject><subject>Wideband communications</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1Lw0AQhhdRsNTeBT0EPCfO7ma_jlJsFQoVjecl2cxCSmriJqX4792S0rnMHN6P4SHknkJGKZjn4mudMaAqYwpyw9gVmVGTm5SDpNeXW_BbshiGHcThnEtmZuTxE8s2LZo9Jtt-bPZlm3x0RwzJqu2Od-TGl-2Ai_Oek-_Va7F8Szfb9fvyZZO6GDOmSmvmpMpl5ZEL6euSOSWpqV3sAdS1c4hGe42V1HXlhIbaVbryWvqKaeBz8jTl9qH7PeAw2l13CD-x0lIjhBJKg4wqmFQudMMQ0Ns-xIfDn6VgTxhsxGBPGOwZQ7Q8TJYGES9yZZjJQfN_qs5WpA</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Yujie Tang</creator><creator>Dvijotham, Krishnamurthy</creator><creator>Low, Steven</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| ispartof | IEEE transactions on smart grid, 2017-11, Vol.8 (6), p.2963-2973 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Computational modeling Computer simulation Cost function Distributed generation Energy sources Heuristic algorithms Mathematical model Newton methods Optimal power flow Power flow Power system stability quasi-Newton method Reactive power Real time Real-time systems time-varying optimization Wideband communications |
| title | Real-Time Optimal Power Flow |
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