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Stochastic Energy Scheduling in Microgrids With Intermittent Renewable Energy Resources
Renewable energy resources such as wind and solar are an important component of a microgrid. However, the inherent intermittency and variability of such resources complicates microgrid operations. Meanwhile, more controllable loads (e.g., plug-in electric vehicles), distributed generators (e.g., mic...
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Published in: | IEEE transactions on smart grid 2014-07, Vol.5 (4), p.1876-1883 |
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container_title | IEEE transactions on smart grid |
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creator | Su, Wencong Wang, Jianhui Roh, Jaehyung |
description | Renewable energy resources such as wind and solar are an important component of a microgrid. However, the inherent intermittency and variability of such resources complicates microgrid operations. Meanwhile, more controllable loads (e.g., plug-in electric vehicles), distributed generators (e.g., micro gas turbines and diesel generators), and distributed energy storage devices (e.g., battery banks) are being integrated into the microgrid operation. To address the operational challenges associated with these technologies and energy resources, this paper formulates a stochastic problem for microgrid energy scheduling. The proposed problem formulation minimizes the expected operational cost of the microgrid and power losses while accommodating the intermittent nature of renewable energy resources. Case studies are performed on a modified IEEE 37-bus test feeder. The simulation results demonstrate the effectiveness and accuracy of the proposed stochastic microgrid energy scheduling model. |
doi_str_mv | 10.1109/TSG.2013.2280645 |
format | article |
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However, the inherent intermittency and variability of such resources complicates microgrid operations. Meanwhile, more controllable loads (e.g., plug-in electric vehicles), distributed generators (e.g., micro gas turbines and diesel generators), and distributed energy storage devices (e.g., battery banks) are being integrated into the microgrid operation. To address the operational challenges associated with these technologies and energy resources, this paper formulates a stochastic problem for microgrid energy scheduling. The proposed problem formulation minimizes the expected operational cost of the microgrid and power losses while accommodating the intermittent nature of renewable energy resources. Case studies are performed on a modified IEEE 37-bus test feeder. The simulation results demonstrate the effectiveness and accuracy of the proposed stochastic microgrid energy scheduling model.</description><identifier>ISSN: 1949-3053</identifier><identifier>EISSN: 1949-3061</identifier><identifier>DOI: 10.1109/TSG.2013.2280645</identifier><identifier>CODEN: ITSGBQ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Batteries ; Degradation ; Electric utilities ; Energy resources ; Generators ; Microgrid ; Microgrids ; plug-in electric vehicle (PEV) ; renewable energy ; Renewable resources ; smart grid ; Stochastic processes ; stochastic programming ; Wind ; Wind power generation</subject><ispartof>IEEE transactions on smart grid, 2014-07, Vol.5 (4), p.1876-1883</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The simulation results demonstrate the effectiveness and accuracy of the proposed stochastic microgrid energy scheduling model.</description><subject>Batteries</subject><subject>Degradation</subject><subject>Electric utilities</subject><subject>Energy resources</subject><subject>Generators</subject><subject>Microgrid</subject><subject>Microgrids</subject><subject>plug-in electric vehicle (PEV)</subject><subject>renewable energy</subject><subject>Renewable resources</subject><subject>smart grid</subject><subject>Stochastic processes</subject><subject>stochastic programming</subject><subject>Wind</subject><subject>Wind power generation</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNo9kE1rAjEQhkNpoWK9F3pZ6Hltvk2ORawVLAW1eAy760QjmrVJpPjvG7F1LjMM7zsfD0KPBPcJwfplMR_3KSasT6nCkosb1CGa65JhSW6vtWD3qBfjFudgjEmqO2g5T22zqWJyTTHyENanYt5sYHXcOb8unC8-XBPadXCrWCxd2hQTnyDsXUrgUzEDDz9VvYN_7wxiewwNxAd0Z6tdhN5f7qKvt9Fi-F5OP8eT4eu0bBjlqVRKrWqrBlUDqsaa06rmmtFcWolJrYUgXGpBaSUYq6miyuYmtkBYPbBEsi56vsw9hPb7CDGZbT7A55WGDIRmXGmqswpfVPmXGANYcwhuX4WTIdicCZpM0JwJmj-C2fJ0sTgAuMqllJRLyn4BxjFr5Q</recordid><startdate>20140701</startdate><enddate>20140701</enddate><creator>Su, Wencong</creator><creator>Wang, Jianhui</creator><creator>Roh, Jaehyung</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Batteries Degradation Electric utilities Energy resources Generators Microgrid Microgrids plug-in electric vehicle (PEV) renewable energy Renewable resources smart grid Stochastic processes stochastic programming Wind Wind power generation |
title | Stochastic Energy Scheduling in Microgrids With Intermittent Renewable Energy Resources |
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