Please use this identifier to cite or link to this item: http://localhost:80/handle/Hannan/154381
Title: Optimal Fast Control and Scheduling of Power Distribution System Using Integrated Receding Horizon Control and Convex Conic Programming
Authors: Seyedmahdi Moghadasi;Sukumar Kamalasadan
subject: Radial Distribution System|Convex Optimization|Real-time Optimization
Year: 2016
Publisher: IEEE
Abstract: In this paper, a convex optimal power flow (OPF) formulation integrated within receding horizon control (RHC) architecture using second-order conic programming (SOCP) is proposed. The main advantages of the proposed method are 1) global optimal scheduling with faster computation time; 2) dynamic models with online control within optimization routine; and 3) integration of uncertain resources and measurements. The effectiveness of this method is evaluated using modified IEEE 32-bus and IEEE 119-bus distribution test systems considering network constraints such as energy market interactions, storage dynamics, and uncertain model of wind generation. The efficiency of the proposed method compared to RHC ac optimal power flow (RHC-ACOPF) is also evaluated using real-time simulator. The results show that the proposed method outperforms the RHC-ACOPF and guarantees global optimal solution. The proposed method also provides effective usage of energy storage system since dynamic modeling of energy storage within the optimization algorithm is possible using RHC integration.
URI: http://localhost/handle/Hannan/154381
ISSN: 0093-9994
1939-9367
volume: 52
issue: 3
More Information: 2596
2606
Appears in Collections:2016

Files in This Item:
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7410031.pdf2.87 MBAdobe PDFThumbnail
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Title: Optimal Fast Control and Scheduling of Power Distribution System Using Integrated Receding Horizon Control and Convex Conic Programming
Authors: Seyedmahdi Moghadasi;Sukumar Kamalasadan
subject: Radial Distribution System|Convex Optimization|Real-time Optimization
Year: 2016
Publisher: IEEE
Abstract: In this paper, a convex optimal power flow (OPF) formulation integrated within receding horizon control (RHC) architecture using second-order conic programming (SOCP) is proposed. The main advantages of the proposed method are 1) global optimal scheduling with faster computation time; 2) dynamic models with online control within optimization routine; and 3) integration of uncertain resources and measurements. The effectiveness of this method is evaluated using modified IEEE 32-bus and IEEE 119-bus distribution test systems considering network constraints such as energy market interactions, storage dynamics, and uncertain model of wind generation. The efficiency of the proposed method compared to RHC ac optimal power flow (RHC-ACOPF) is also evaluated using real-time simulator. The results show that the proposed method outperforms the RHC-ACOPF and guarantees global optimal solution. The proposed method also provides effective usage of energy storage system since dynamic modeling of energy storage within the optimization algorithm is possible using RHC integration.
URI: http://localhost/handle/Hannan/154381
ISSN: 0093-9994
1939-9367
volume: 52
issue: 3
More Information: 2596
2606
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7410031.pdf2.87 MBAdobe PDFThumbnail
Preview File
Title: Optimal Fast Control and Scheduling of Power Distribution System Using Integrated Receding Horizon Control and Convex Conic Programming
Authors: Seyedmahdi Moghadasi;Sukumar Kamalasadan
subject: Radial Distribution System|Convex Optimization|Real-time Optimization
Year: 2016
Publisher: IEEE
Abstract: In this paper, a convex optimal power flow (OPF) formulation integrated within receding horizon control (RHC) architecture using second-order conic programming (SOCP) is proposed. The main advantages of the proposed method are 1) global optimal scheduling with faster computation time; 2) dynamic models with online control within optimization routine; and 3) integration of uncertain resources and measurements. The effectiveness of this method is evaluated using modified IEEE 32-bus and IEEE 119-bus distribution test systems considering network constraints such as energy market interactions, storage dynamics, and uncertain model of wind generation. The efficiency of the proposed method compared to RHC ac optimal power flow (RHC-ACOPF) is also evaluated using real-time simulator. The results show that the proposed method outperforms the RHC-ACOPF and guarantees global optimal solution. The proposed method also provides effective usage of energy storage system since dynamic modeling of energy storage within the optimization algorithm is possible using RHC integration.
URI: http://localhost/handle/Hannan/154381
ISSN: 0093-9994
1939-9367
volume: 52
issue: 3
More Information: 2596
2606
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7410031.pdf2.87 MBAdobe PDFThumbnail
Preview File