A non-iterative distributed approximate dynamic programming algorithm for frequency security-constrained stochastic economic dispatch
•Stochastic economic dispatch model considering the system frequency security constraints.•A golden section search-based approximate linear constraint generation algorithm.•A non-iterative distributed approximate dynamic programming algorithm.•Test results show the computational efficiency of the pr...
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| Veröffentlicht in: | International journal of electrical power & energy systems Jg. 166; S. 110543 |
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| Sprache: | Englisch |
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01.05.2025
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| ISSN: | 0142-0615 |
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| Abstract | •Stochastic economic dispatch model considering the system frequency security constraints.•A golden section search-based approximate linear constraint generation algorithm.•A non-iterative distributed approximate dynamic programming algorithm.•Test results show the computational efficiency of the proposed algorithm.
Due to uncertainties associated with the power output of offshore wind farms, the active power balance and frequency security control of power systems with lots of offshore wind farms are highly challenging. To address this problem, in this study, a new stochastic economic dispatch model of a power system with offshore wind farms considering the system frequency security constraints is established to obtain economic and secure dispatch decisions. Furthermore, the nonlinear convexity of frequency security constraints provides considerable theoretical support for the global optimality of decision-making, and a golden section search-based approximate linear constraint generation algorithm is designed to approximate nonlinear frequency security constraints for improving computational efficiency. Next, a non-iterative distributed approximate dynamic programming algorithm based on the equivalent projection method is designed for the distributed solution of the established model. In the algorithm, first, the model is decoupled from time periods. Next, the high-dimensional feasible region of the offshore wind farm optimization model is projected into a low-dimensional feasible region and substituted into the transmission grid optimization model, and solves the models of the transmission grid and the offshore wind farms sequentially to achieve the non-iterative distributed solution. Finally, case studies on a modified IEEE 39-bus system with two offshore wind farms and an actual provincial system with seven offshore wind farms demonstrate the effectiveness and superiority of the proposed model and algorithm, reducing solution time by over 86.4% compared to the alternating direction method of multipliers-based distributed approximate dynamic programming algorithm. |
|---|---|
| AbstractList | •Stochastic economic dispatch model considering the system frequency security constraints.•A golden section search-based approximate linear constraint generation algorithm.•A non-iterative distributed approximate dynamic programming algorithm.•Test results show the computational efficiency of the proposed algorithm.
Due to uncertainties associated with the power output of offshore wind farms, the active power balance and frequency security control of power systems with lots of offshore wind farms are highly challenging. To address this problem, in this study, a new stochastic economic dispatch model of a power system with offshore wind farms considering the system frequency security constraints is established to obtain economic and secure dispatch decisions. Furthermore, the nonlinear convexity of frequency security constraints provides considerable theoretical support for the global optimality of decision-making, and a golden section search-based approximate linear constraint generation algorithm is designed to approximate nonlinear frequency security constraints for improving computational efficiency. Next, a non-iterative distributed approximate dynamic programming algorithm based on the equivalent projection method is designed for the distributed solution of the established model. In the algorithm, first, the model is decoupled from time periods. Next, the high-dimensional feasible region of the offshore wind farm optimization model is projected into a low-dimensional feasible region and substituted into the transmission grid optimization model, and solves the models of the transmission grid and the offshore wind farms sequentially to achieve the non-iterative distributed solution. Finally, case studies on a modified IEEE 39-bus system with two offshore wind farms and an actual provincial system with seven offshore wind farms demonstrate the effectiveness and superiority of the proposed model and algorithm, reducing solution time by over 86.4% compared to the alternating direction method of multipliers-based distributed approximate dynamic programming algorithm. Due to uncertainties associated with the power output of offshore wind farms, the active power balance and frequency security control of power systems with lots of offshore wind farms are highly challenging. To address this problem, in this study, a new stochastic economic dispatch model of a power system with offshore wind farms considering the system frequency security constraints is established to obtain economic and secure dispatch decisions. Furthermore, the nonlinear convexity of frequency security constraints provides considerable theoretical support for the global optimality of decision-making, and a golden section search-based approximate linear constraint generation algorithm is designed to approximate nonlinear frequency security constraints for improving computational efficiency. Next, a non-iterative distributed approximate dynamic programming algorithm based on the equivalent projection method is designed for the distributed solution of the established model. In the algorithm, first, the model is decoupled from time periods. Next, the high-dimensional feasible region of the offshore wind farm optimization model is projected into a low-dimensional feasible region and substituted into the transmission grid optimization model, and solves the models of the transmission grid and the offshore wind farms sequentially to achieve the non-iterative distributed solution. Finally, case studies on a modified IEEE 39-bus system with two offshore wind farms and an actual provincial system with seven offshore wind farms demonstrate the effectiveness and superiority of the proposed model and algorithm, reducing solution time by over 86.4% compared to the alternating direction method of multipliers-based distributed approximate dynamic programming algorithm. |
| ArticleNumber | 110543 |
| Author | Liu, Mingbo Liang, Yutao Liu, Yanghua Feng, Xiangyong Lin, Shunjiang |
| Author_xml | – sequence: 1 givenname: Xiangyong surname: Feng fullname: Feng, Xiangyong organization: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China – sequence: 2 givenname: Shunjiang orcidid: 0000-0001-8201-2045 surname: Lin fullname: Lin, Shunjiang email: linshj@scut.edu.cn organization: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China – sequence: 3 givenname: Yutao surname: Liang fullname: Liang, Yutao organization: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China – sequence: 4 givenname: Yanghua surname: Liu fullname: Liu, Yanghua organization: School of Electromechanical Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China – sequence: 5 givenname: Mingbo orcidid: 0000-0001-9097-9045 surname: Liu fullname: Liu, Mingbo organization: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China |
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| Cites_doi | 10.35833/MPCE.2020.000918 10.1109/TPWRS.2023.3252502 10.1016/j.energy.2020.117347 10.1016/j.energy.2023.126892 10.35833/MPCE.2021.000734 10.1016/j.energy.2020.117130 10.1109/TPWRS.2021.3051523 10.1016/j.ijepes.2022.108190 10.1109/TSTE.2019.2931908 10.1109/JSYST.2022.3158959 10.1109/TPWRS.2021.3074634 10.1109/TPWRS.2020.3019828 10.1109/TSG.2023.3263273 10.1016/j.ijepes.2021.107802 10.1016/j.ijepes.2019.01.013 10.1109/TPWRS.2023.3258066 10.1007/s10107-010-0393-3 10.1109/TPWRS.2015.2434837 10.35833/MPCE.2023.000019 10.1109/TPWRS.2020.2996821 10.4236/jamp.2015.31008 10.1109/TPWRS.2023.3257033 10.1016/j.ijepes.2022.108768 10.1016/j.ijepes.2024.109993 10.1016/j.ijepes.2023.109599 10.1109/TIA.2021.3091663 10.1109/TSTE.2022.3221276 |
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| Keywords | Frequency security constraint Approximate dynamic programming algorithm Non-iterative distributed algorithm Stochastic economic dispatch Offshore wind farm |
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| SubjectTerms | Approximate dynamic programming algorithm Frequency security constraint Non-iterative distributed algorithm Offshore wind farm Stochastic economic dispatch |
| Title | A non-iterative distributed approximate dynamic programming algorithm for frequency security-constrained stochastic economic dispatch |
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