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Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system
Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. Howev...
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Published in: | IET renewable power generation 2017-12, Vol.11 (14), p.1832-1840 |
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creator | Zargar, Mubashar Yaqoob Mufti, Mairaj Ud-Din Lone, Shameem Ahmad |
description | Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives. |
doi_str_mv | 10.1049/iet-rpg.2017.0074 |
format | article |
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Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. 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Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives.</description><subject>adaptive control</subject><subject>adaptive generalised predictive control scheme</subject><subject>AGPC scheme</subject><subject>converter rating</subject><subject>diesel‐electric power stations</subject><subject>discrete time model</subject><subject>discrete time systems</subject><subject>encapsulate online identification</subject><subject>improved frequency control</subject><subject>isolated power system</subject><subject>least squares approximations</subject><subject>MATLAB</subject><subject>power convertors</subject><subject>power generation control</subject><subject>power system identification</subject><subject>predictive control</subject><subject>recursive least‐square algorithm</subject><subject>reduced‐order model</subject><subject>Research Article</subject><subject>small capacity SMES unit</subject><subject>SMES device</subject><subject>superconducting magnet energy storage</subject><subject>superconducting magnetic energy storage device</subject><subject>S‐function code</subject><subject>wind power plants</subject><subject>wind‐diesel power system</subject><issn>1752-1416</issn><issn>1752-1424</issn><issn>1752-1424</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFkMtKAzEUhoMoWKsP4C4vMDW3zsVdLbUKFcV2H2JyIilzM5m2zNubsSK40dX5F-c7lw-ha0omlIjixkGX-PZ9wgjNJoRk4gSNaDZlCRVMnP5kmp6jixC2hEwLkqcjtJ8Z1XZuD7j1YJz-irqpO9-UuLFY4VCpssRatUq7rsfrp8Ua72rXYdt47KrWN3sw2Hr42EGt-9_wwdUmMQ4ClLhtDuBx6EMH1SU6s6oMcPVdx2hzv9jMH5LV8_JxPlslmnMRD-aWCJpzIyC1GVGQcjDKWkOApiyngqsidhjKtC6USIEykqUiy5QqaP7Gx4gex2rfhODByta7SvleUiIHbzJ6k9GbHLzJwVtkbo_MwZXQ_w_I15clu7uPkbMIJ0d4aNs2O1_H7_5Y9gk8UoVC</recordid><startdate>20171213</startdate><enddate>20171213</enddate><creator>Zargar, Mubashar Yaqoob</creator><creator>Mufti, Mairaj Ud-Din</creator><creator>Lone, Shameem Ahmad</creator><general>The Institution of Engineering and Technology</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20171213</creationdate><title>Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system</title><author>Zargar, Mubashar Yaqoob ; Mufti, Mairaj Ud-Din ; Lone, Shameem Ahmad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3342-13f04183d4e6f70ae63edaffd0e1628143a9f04d12cc9a46e12076477aa918b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>adaptive control</topic><topic>adaptive generalised predictive control scheme</topic><topic>AGPC scheme</topic><topic>converter rating</topic><topic>diesel‐electric power stations</topic><topic>discrete time model</topic><topic>discrete time systems</topic><topic>encapsulate online identification</topic><topic>improved frequency control</topic><topic>isolated power system</topic><topic>least squares approximations</topic><topic>MATLAB</topic><topic>power convertors</topic><topic>power generation control</topic><topic>power system identification</topic><topic>predictive control</topic><topic>recursive least‐square algorithm</topic><topic>reduced‐order model</topic><topic>Research Article</topic><topic>small capacity SMES unit</topic><topic>SMES device</topic><topic>superconducting magnet energy storage</topic><topic>superconducting magnetic energy storage device</topic><topic>S‐function code</topic><topic>wind power plants</topic><topic>wind‐diesel power system</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zargar, Mubashar Yaqoob</creatorcontrib><creatorcontrib>Mufti, Mairaj Ud-Din</creatorcontrib><creatorcontrib>Lone, Shameem Ahmad</creatorcontrib><collection>CrossRef</collection><jtitle>IET renewable power generation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zargar, Mubashar Yaqoob</au><au>Mufti, Mairaj Ud-Din</au><au>Lone, Shameem Ahmad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system</atitle><jtitle>IET renewable power generation</jtitle><date>2017-12-13</date><risdate>2017</risdate><volume>11</volume><issue>14</issue><spage>1832</spage><epage>1840</epage><pages>1832-1840</pages><issn>1752-1416</issn><issn>1752-1424</issn><eissn>1752-1424</eissn><abstract>Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives.</abstract><pub>The Institution of Engineering and Technology</pub><doi>10.1049/iet-rpg.2017.0074</doi><tpages>9</tpages></addata></record> |
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subjects | adaptive control adaptive generalised predictive control scheme AGPC scheme converter rating diesel‐electric power stations discrete time model discrete time systems encapsulate online identification improved frequency control isolated power system least squares approximations MATLAB power convertors power generation control power system identification predictive control recursive least‐square algorithm reduced‐order model Research Article small capacity SMES unit SMES device superconducting magnet energy storage superconducting magnetic energy storage device S‐function code wind power plants wind‐diesel power system |
title | Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system |
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