Accelerated dual dynamic integer programming applied to short-term power generation scheduling

•Use of Dual Dynamic Integer Programming framework.•Inclusion of multiperiod stages and overlapping strategies to accelerate the method.•Solving the Short-Term Power Generation Scheduling problem.•Validation of the proposed scheme on the IEEE 118-bus system. The short-term generation scheduling (STG...

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Veröffentlicht in:International journal of electrical power & energy systems Jg. 145; S. 108689
Hauptverfasser: Santos, Kenny Vinente dos, Colonetti, Bruno, Finardi, Erlon Cristian, Zavala, Victor M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.02.2023
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ISSN:0142-0615
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Abstract •Use of Dual Dynamic Integer Programming framework.•Inclusion of multiperiod stages and overlapping strategies to accelerate the method.•Solving the Short-Term Power Generation Scheduling problem.•Validation of the proposed scheme on the IEEE 118-bus system. The short-term generation scheduling (STGS) problem defines which units must operate and how much power they must deliver to satisfy the system demand over a planning horizon of up to two weeks. The problem is typically formulated as a large-scale mixed-integer linear programming problem, where off-the-shelf commercial solvers generally struggle to efficiently solve realistic instances of the STGS, mainly due to the large-scale of these models. Thus, decomposition approaches that break the model into smaller instances that are more easily handled are attractive alternatives to directly employing these solvers. This paper proposes a dual dynamic integer programming (DDiP) framework for solving the STGS problem efficiently. As in the standard DDiP approach, we use a nested Benders decomposition over the time horizon but introduce multiperiod stages and overlap strategies to accelerate the method. Simulations performed on the IEEE-118 system show that the proposed approach is significantly faster than standard DDiP and can deliver near-optimal solutions.
AbstractList •Use of Dual Dynamic Integer Programming framework.•Inclusion of multiperiod stages and overlapping strategies to accelerate the method.•Solving the Short-Term Power Generation Scheduling problem.•Validation of the proposed scheme on the IEEE 118-bus system. The short-term generation scheduling (STGS) problem defines which units must operate and how much power they must deliver to satisfy the system demand over a planning horizon of up to two weeks. The problem is typically formulated as a large-scale mixed-integer linear programming problem, where off-the-shelf commercial solvers generally struggle to efficiently solve realistic instances of the STGS, mainly due to the large-scale of these models. Thus, decomposition approaches that break the model into smaller instances that are more easily handled are attractive alternatives to directly employing these solvers. This paper proposes a dual dynamic integer programming (DDiP) framework for solving the STGS problem efficiently. As in the standard DDiP approach, we use a nested Benders decomposition over the time horizon but introduce multiperiod stages and overlap strategies to accelerate the method. Simulations performed on the IEEE-118 system show that the proposed approach is significantly faster than standard DDiP and can deliver near-optimal solutions.
ArticleNumber 108689
Author Finardi, Erlon Cristian
Santos, Kenny Vinente dos
Colonetti, Bruno
Zavala, Victor M.
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  givenname: Kenny Vinente dos
  surname: Santos
  fullname: Santos, Kenny Vinente dos
  email: kennyvinente@ufam.edu.br
  organization: Department of Oil and Gas, Federal University of Amazonas, 6200 Gen. Rodrigo, Octavio Av., Coroado I, Manaus 69080-900, Amazonas, Brazil
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  givenname: Bruno
  surname: Colonetti
  fullname: Colonetti, Bruno
  organization: Department of Electrical and Electronic Engineering, Federal University of Santa Catarina, Trindade, Florianopolis 88040-900, Santa Catarina, Brazil
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  givenname: Erlon Cristian
  surname: Finardi
  fullname: Finardi, Erlon Cristian
  organization: Department of Electrical and Electronic Engineering, Federal University of Santa Catarina, Trindade, Florianopolis 88040-900, Santa Catarina, Brazil
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  givenname: Victor M.
  surname: Zavala
  fullname: Zavala, Victor M.
  organization: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA
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Keywords Short-term generation scheduling
Dual dynamic integer programming
Mixed-integer linear programming
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Snippet •Use of Dual Dynamic Integer Programming framework.•Inclusion of multiperiod stages and overlapping strategies to accelerate the method.•Solving the Short-Term...
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StartPage 108689
SubjectTerms Dual dynamic integer programming
Mixed-integer linear programming
Short-term generation scheduling
Title Accelerated dual dynamic integer programming applied to short-term power generation scheduling
URI https://dx.doi.org/10.1016/j.ijepes.2022.108689
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