Distributed optimal power flow for smart grid transmission system with renewable energy sources

Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will contribute to reducing the global warming effect from the power generation sector. In this paper, we propose a DPOPF (distributed and parallel OPF)...

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Vydané v:	Energy (Oxford) Ročník 56; s. 184 - 192
Hlavní autori:	Lin, Shin-Yeu, Chen, Jyun-Fu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier Ltd 01.07.2013 Elsevier
Predmet:	algorithms Applied sciences carbon Computational synchronization Distributed and parallel computation Energy energy conservation energy costs Exact sciences and technology global warming Optimal power flow Petri net power generation Renewable energy source renewable energy sources Smart grid Computational synchronization Distributed and parallel computation Renewable energy source Optimal power flow Smart grid Petri net Energy source Electric energy transportation Renewable energy
ISSN:	0360-5442
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Abstract	Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will contribute to reducing the global warming effect from the power generation sector. In this paper, we propose a DPOPF (distributed and parallel OPF) algorithm for the smart grid transmission system with renewable energy sources to account for the fast variation of the power generated by renewable energy sources. The proposed DPOPF algorithm is a combination of the recursive quadratic programming method and the Lagrange projected gradient method; it can achieve the complete decomposition and can be executed in the smart grid transmission system to make distributed and parallel computation possible. We also propose Petri nets to control the computational synchronization of the DPOPF algorithm under the asynchronous data arrival in the smart grid transmission system. The proposed DPOPF algorithm is applied to solve OPF problems in a smart grid transmission system with renewable energy sources on a 26-bus test system. The test results demonstrate the computational efficiency of the proposed DPOPF algorithm, which is fast enough to cope with the fast variation of the power generated by renewable energy sources, and justify the accuracy of the obtained solutions. •Distributed optimal power flow (DOPF) algorithm for smart grid with renewable energy sources.•DOPF algorithm achieves distributed and parallel computation.•DOPF algorithm is executed in smart grid to exploit its great computing and communication power.•Petri net model controls the computational synchronization of DOPF algorithm in smart grid.•Speed up factor of DOPF algorithm vs. COPF algorithm is 55 times in single PC and 2000 times, ideally.
AbstractList	Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will contribute to reducing the global warming effect from the power generation sector. In this paper, we propose a DPOPF (distributed and parallel OPF) algorithm for the smart grid transmission system with renewable energy sources to account for the fast variation of the power generated by renewable energy sources. The proposed DPOPF algorithm is a combination of the recursive quadratic programming method and the Lagrange projected gradient method; it can achieve the complete decomposition and can be executed in the smart grid transmission system to make distributed and parallel computation possible. We also propose Petri nets to control the computational synchronization of the DPOPF algorithm under the asynchronous data arrival in the smart grid transmission system. The proposed DPOPF algorithm is applied to solve OPF problems in a smart grid transmission system with renewable energy sources on a 26-bus test system. The test results demonstrate the computational efficiency of the proposed DPOPF algorithm, which is fast enough to cope with the fast variation of the power generated by renewable energy sources, and justify the accuracy of the obtained solutions. •Distributed optimal power flow (DOPF) algorithm for smart grid with renewable energy sources.•DOPF algorithm achieves distributed and parallel computation.•DOPF algorithm is executed in smart grid to exploit its great computing and communication power.•Petri net model controls the computational synchronization of DOPF algorithm in smart grid.•Speed up factor of DOPF algorithm vs. COPF algorithm is 55 times in single PC and 2000 times, ideally. Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will contribute to reducing the global warming effect from the power generation sector. In this paper, we propose a DPOPF (distributed and parallel OPF) algorithm for the smart grid transmission system with renewable energy sources to account for the fast variation of the power generated by renewable energy sources. The proposed DPOPF algorithm is a combination of the recursive quadratic programming method and the Lagrange projected gradient method; it can achieve the complete decomposition and can be executed in the smart grid transmission system to make distributed and parallel computation possible. We also propose Petri nets to control the computational synchronization of the DPOPF algorithm under the asynchronous data arrival in the smart grid transmission system. The proposed DPOPF algorithm is applied to solve OPF problems in a smart grid transmission system with renewable energy sources on a 26-bus test system. The test results demonstrate the computational efficiency of the proposed DPOPF algorithm, which is fast enough to cope with the fast variation of the power generated by renewable energy sources, and justify the accuracy of the obtained solutions. Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will contribute to reducing the global warming effect from the power generation sector. In this paper, we propose a DPOPF (distributed and parallel OPF) algorithm for the smart grid transmission system with renewable energy sources to account for the fast variation of the power generated by renewable energy sources. The proposed DPOPF algorithm is a combination of the recursive quadratic programming method and the Lagrange projected gradient method; it can achieve the complete decomposition and can be executed in the smart grid transmission system to make distributed and parallel computation possible. We also propose Petri nets to control the computational synchronization of the DPOPF algorithm under the asynchronous data arrival in the smart grid transmission system.
Author	Chen, Jyun-Fu Lin, Shin-Yeu
Author_xml	– sequence: 1 givenname: Shin-Yeu surname: Lin fullname: Lin, Shin-Yeu email: shinylin@mail.cgu.edu.tw – sequence: 2 givenname: Jyun-Fu surname: Chen fullname: Chen, Jyun-Fu email: nba200318@yahoo.com.tw
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Snippet	Utilizing renewable energy sources to reduce carbon emission and minimizing the fuel cost for energy saving in the OPF (optimal power flow) problem will...
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SubjectTerms	algorithms Applied sciences carbon Computational synchronization Distributed and parallel computation Energy energy conservation energy costs Exact sciences and technology global warming Optimal power flow Petri net power generation Renewable energy source renewable energy sources Smart grid
Title	Distributed optimal power flow for smart grid transmission system with renewable energy sources
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