Retrofit Planning and Flexible Operation of Coal-Fired Units Using Stochastic Dual Dynamic Integer Programming

The continuous growth of wind power requires greater power system operational flexibility owing to the variability and uncertainty of wind power generation. Retrofitting existing coal-fired units is a demonstrated cost-effective method for improving system flexibility. This study proposes a decision...

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Published in:	IEEE transactions on power systems Vol. 39; no. 1; pp. 1 - 16
Main Authors:	Li, Zhuangzhuang, Yang, Ping, Zhao, Zhuoli, Lai, Loi Lei
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Benders decomposition Coal-fired power plants Coal-fired units Costs Decision support systems Flexibility flexibility retrofit flexible operation Integer programming Load modeling Mixed integer Nonlinear programming Operating costs Operational problems Planning renewable energy sources Retrofitting stochastic dual dynamic integer programming Stochastic processes System effectiveness Unit commitment Wind farms Wind forecasting Wind power Wind power generation
ISSN:	0885-8950, 1558-0679
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Abstract	The continuous growth of wind power requires greater power system operational flexibility owing to the variability and uncertainty of wind power generation. Retrofitting existing coal-fired units is a demonstrated cost-effective method for improving system flexibility. This study proposes a decision support tool that provides optimal investment decisions to enhance power system operational flexibility. A novel flexibility retrofit planning (FRP) model is proposed in which the embedded operational problem is a stochastic mixed-integer nonlinear programming (SMINLP) unit commitment problem. In the operational unit commitment model, novel mixed-integer nonlinear formulations are proposed to represent the coal-fired unit attribute (minimum power output, startup and shutdown times, and maximum ramp rate) modifications after retrofitting. A new solution method based on the Benders decomposition (BD) and stochastic dual dynamic integer programming (SDDIP) algorithms is proposed to solve the proposed FRP model. The modified IEEE 39-bus, 57-bus, and 118-bus test systems were used to verify the effectiveness of the proposed model and solution method. The results demonstrate that the proposed FRP model can balance the retrofitting and operational costs to minimize the total cost and accommodate more wind generation. The proposed solution method is computationally efficient for solving FRP models.
AbstractList	The continuous growth of wind power requires greater power system operational flexibility owing to the variability and uncertainty of wind power generation. Retrofitting existing coal-fired units is a demonstrated cost-effective method for improving system flexibility. This study proposes a decision support tool that provides optimal investment decisions to enhance power system operational flexibility. A novel flexibility retrofit planning (FRP) model is proposed in which the embedded operational problem is a stochastic mixed-integer nonlinear programming (SMINLP) unit commitment problem. In the operational unit commitment model, novel mixed-integer nonlinear formulations are proposed to represent the coal-fired unit attribute (minimum power output, startup and shutdown times, and maximum ramp rate) modifications after retrofitting. A new solution method based on the Benders decomposition (BD) and stochastic dual dynamic integer programming (SDDIP) algorithms is proposed to solve the proposed FRP model. The modified IEEE 39-bus, 57-bus, and 118-bus test systems were used to verify the effectiveness of the proposed model and solution method. The results demonstrate that the proposed FRP model can balance the retrofitting and operational costs to minimize the total cost and accommodate more wind generation. The proposed solution method is computationally efficient for solving FRP models.
Author	Yang, Ping Zhao, Zhuoli Lai, Loi Lei Li, Zhuangzhuang
Author_xml	– sequence: 1 givenname: Zhuangzhuang surname: Li fullname: Li, Zhuangzhuang organization: School of Electric Power, South China University of Technology, Guangzhou, China – sequence: 2 givenname: Ping surname: Yang fullname: Yang, Ping organization: School of Electric Power, South China University of Technology, Guangzhou, China – sequence: 3 givenname: Zhuoli orcidid: 0000-0003-2531-0614 surname: Zhao fullname: Zhao, Zhuoli organization: Department of Electrical Engineering, School of Automation, Guangdong University of Technology, Guangzhou, China – sequence: 4 givenname: Loi Lei orcidid: 0000-0003-4786-7931 surname: Lai fullname: Lai, Loi Lei organization: Department of Electrical Engineering, School of Automation, Guangdong University of Technology, Guangzhou, China
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SubjectTerms	Algorithms Benders decomposition Coal-fired power plants Coal-fired units Costs Decision support systems Flexibility flexibility retrofit flexible operation Integer programming Load modeling Mixed integer Nonlinear programming Operating costs Operational problems Planning renewable energy sources Retrofitting stochastic dual dynamic integer programming Stochastic processes System effectiveness Unit commitment Wind farms Wind forecasting Wind power Wind power generation
Title	Retrofit Planning and Flexible Operation of Coal-Fired Units Using Stochastic Dual Dynamic Integer Programming
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