Heuristic solution of a joint electric control reserve and wholesale market model

Research output: Contribution to journalArticleResearchpeer review

View graph of relations

Details

Original languageEnglish
Article number1940001
Pages (from-to)1940001-1 - 1940001-20
Number of pages20
JournalInternational Journal of Modeling, Simulation, and Scientific Computing
Volume10
Issue number2
Early online date25 Jul 2018
Publication statusPublished - 1 Apr 2019

Abstract

A mixed integer linear programming (MILP) approach for the joint simulation of electric control reserve and electricity wholesale markets is presented. This generation dispatch model extends an existing integrated grid and electricity market (IGEM) model covering the Continental European electric power system. By explicitly incorporating the markets for primary and secondary control reserves (PCR and SCR), the model can reproduce the decisions of generating unit operators on which markets get involved. Besides, the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up. Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year, temporal and geographical interdependencies are used to solve it heuristically. The heuristic therefore splits the model into various sub-problems so that on the one hand, the number of variables, especially of integer variables, per sub-problem is reduced significantly and on the other hand, the relevant interdependencies remain considered. The heuristic is evaluated in terms of accuracy and computation time by means of two case studies. Both case studies show satisfactory accuracy and significant advantages in computation time.

Keywords

    Mixed-integer linear programming, rolling horizon heuristic, unit commitment

ASJC Scopus subject areas

Cite this

Heuristic solution of a joint electric control reserve and wholesale market model. / Breithaupt, Timo Jens; Leveringhaus, Thomas; Hofmann, Lutz.
In: International Journal of Modeling, Simulation, and Scientific Computing, Vol. 10, No. 2, 1940001, 01.04.2019, p. 1940001-1 - 1940001-20.

Research output: Contribution to journalArticleResearchpeer review

Breithaupt, TJ, Leveringhaus, T & Hofmann, L 2019, 'Heuristic solution of a joint electric control reserve and wholesale market model', International Journal of Modeling, Simulation, and Scientific Computing, vol. 10, no. 2, 1940001, pp. 1940001-1 - 1940001-20. https://doi.org/10.1142/s1793962319400014
Breithaupt, T. J., Leveringhaus, T., & Hofmann, L. (2019). Heuristic solution of a joint electric control reserve and wholesale market model. International Journal of Modeling, Simulation, and Scientific Computing, 10(2), 1940001-1 - 1940001-20. Article 1940001. https://doi.org/10.1142/s1793962319400014
Breithaupt TJ, Leveringhaus T, Hofmann L. Heuristic solution of a joint electric control reserve and wholesale market model. International Journal of Modeling, Simulation, and Scientific Computing. 2019 Apr 1;10(2):1940001-1 - 1940001-20. 1940001. Epub 2018 Jul 25. doi: 10.1142/s1793962319400014
Breithaupt, Timo Jens ; Leveringhaus, Thomas ; Hofmann, Lutz. / Heuristic solution of a joint electric control reserve and wholesale market model. In: International Journal of Modeling, Simulation, and Scientific Computing. 2019 ; Vol. 10, No. 2. pp. 1940001-1 - 1940001-20.
Download
@article{dd591e493a8544c9a2e0493bba9a1b39,
title = "Heuristic solution of a joint electric control reserve and wholesale market model",
abstract = "A mixed integer linear programming (MILP) approach for the joint simulation of electric control reserve and electricity wholesale markets is presented. This generation dispatch model extends an existing integrated grid and electricity market (IGEM) model covering the Continental European electric power system. By explicitly incorporating the markets for primary and secondary control reserves (PCR and SCR), the model can reproduce the decisions of generating unit operators on which markets get involved. Besides, the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up. Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year, temporal and geographical interdependencies are used to solve it heuristically. The heuristic therefore splits the model into various sub-problems so that on the one hand, the number of variables, especially of integer variables, per sub-problem is reduced significantly and on the other hand, the relevant interdependencies remain considered. The heuristic is evaluated in terms of accuracy and computation time by means of two case studies. Both case studies show satisfactory accuracy and significant advantages in computation time.",
keywords = "Mixed-integer linear programming, rolling horizon heuristic, unit commitment",
author = "Breithaupt, {Timo Jens} and Thomas Leveringhaus and Lutz Hofmann",
note = "Publisher Copyright: {\textcopyright} 2019 World Scientific Publishing Company. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",
year = "2019",
month = apr,
day = "1",
doi = "10.1142/s1793962319400014",
language = "English",
volume = "10",
pages = "1940001--1 -- 1940001--20",
number = "2",

}

Download

TY - JOUR

T1 - Heuristic solution of a joint electric control reserve and wholesale market model

AU - Breithaupt, Timo Jens

AU - Leveringhaus, Thomas

AU - Hofmann, Lutz

N1 - Publisher Copyright: © 2019 World Scientific Publishing Company. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - A mixed integer linear programming (MILP) approach for the joint simulation of electric control reserve and electricity wholesale markets is presented. This generation dispatch model extends an existing integrated grid and electricity market (IGEM) model covering the Continental European electric power system. By explicitly incorporating the markets for primary and secondary control reserves (PCR and SCR), the model can reproduce the decisions of generating unit operators on which markets get involved. Besides, the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up. Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year, temporal and geographical interdependencies are used to solve it heuristically. The heuristic therefore splits the model into various sub-problems so that on the one hand, the number of variables, especially of integer variables, per sub-problem is reduced significantly and on the other hand, the relevant interdependencies remain considered. The heuristic is evaluated in terms of accuracy and computation time by means of two case studies. Both case studies show satisfactory accuracy and significant advantages in computation time.

AB - A mixed integer linear programming (MILP) approach for the joint simulation of electric control reserve and electricity wholesale markets is presented. This generation dispatch model extends an existing integrated grid and electricity market (IGEM) model covering the Continental European electric power system. By explicitly incorporating the markets for primary and secondary control reserves (PCR and SCR), the model can reproduce the decisions of generating unit operators on which markets get involved. Besides, the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up. Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year, temporal and geographical interdependencies are used to solve it heuristically. The heuristic therefore splits the model into various sub-problems so that on the one hand, the number of variables, especially of integer variables, per sub-problem is reduced significantly and on the other hand, the relevant interdependencies remain considered. The heuristic is evaluated in terms of accuracy and computation time by means of two case studies. Both case studies show satisfactory accuracy and significant advantages in computation time.

KW - Mixed-integer linear programming

KW - rolling horizon heuristic

KW - unit commitment

UR - http://www.scopus.com/inward/record.url?scp=85052627817&partnerID=8YFLogxK

U2 - 10.1142/s1793962319400014

DO - 10.1142/s1793962319400014

M3 - Article

VL - 10

SP - 1940001-1 - 1940001-20

JO - International Journal of Modeling, Simulation, and Scientific Computing

JF - International Journal of Modeling, Simulation, and Scientific Computing

IS - 2

M1 - 1940001

ER -

By the same author(s)