Discrete optimization via simulation to determine reliable network investments

Tomas Lagos; Fernando Ordonez; Rafael Sacaan; Hugh Rudnick; Alejandro Navarro-Espinosa; Rodrigo Moreno

doi:10.1109/PESGM.2017.8274589

Discrete optimization via simulation to determine reliable network investments

Tomas Lagos
, Fernando Ordonez
, Rafael Sacaan
, Hugh Rudnick
, Alejandro Navarro-Espinosa
, Rodrigo Moreno

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Solving optimization problems in power systems planning often imposes a compromise between the accurate representation of the power system operation and the simplifications made in the mathematical methodologies used to find the optimal solution. Hence, classic heuristic algorithms go deep modelling operational details without having a clear message about the quality of the solution, whereas mathematical programming approaches find the optimal solution by (significantly) simplifying system operation. In this vein, this article proposes the utilization of Discrete Optimization via Simulation algorithms to solve optimization problems when a detailed representation of the system and information about the quality of the solution are required. In particular, the Industrial Strength COMPASS algorithm is applied to find the optimal set of new transmission lines that maximizes power system reliability given a certain budget and considering a detailed power system model, where a full unit commitment with network constraints and an hourly sequential Monte Carlo are implemented.

Original language	English
Title of host publication	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Publisher	IEEE Computer Society
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538622124
DOIs	https://doi.org/10.1109/PESGM.2017.8274589
State	Published - 29 Jan 2018
Externally published	Yes
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: 16 Jul 2017 → 20 Jul 2017

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-January
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Country/Territory	United States
City	Chicago
Period	16/07/17 → 20/07/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Discrete Optimization via Simulation
Optimization
Reliability
Sequential Monte Carlo Simulations

Access to Document

10.1109/PESGM.2017.8274589

Cite this

Lagos, T., Ordonez, F., Sacaan, R., Rudnick, H., Navarro-Espinosa, A., & Moreno, R. (2018). Discrete optimization via simulation to determine reliable network investments. In 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 (pp. 1-5). (IEEE Power and Energy Society General Meeting; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/PESGM.2017.8274589

@inproceedings{6dccbae63cfd421b9f562706ece8fb13,

title = "Discrete optimization via simulation to determine reliable network investments",

abstract = "Solving optimization problems in power systems planning often imposes a compromise between the accurate representation of the power system operation and the simplifications made in the mathematical methodologies used to find the optimal solution. Hence, classic heuristic algorithms go deep modelling operational details without having a clear message about the quality of the solution, whereas mathematical programming approaches find the optimal solution by (significantly) simplifying system operation. In this vein, this article proposes the utilization of Discrete Optimization via Simulation algorithms to solve optimization problems when a detailed representation of the system and information about the quality of the solution are required. In particular, the Industrial Strength COMPASS algorithm is applied to find the optimal set of new transmission lines that maximizes power system reliability given a certain budget and considering a detailed power system model, where a full unit commitment with network constraints and an hourly sequential Monte Carlo are implemented.",

keywords = "Discrete Optimization via Simulation, Optimization, Reliability, Sequential Monte Carlo Simulations",

author = "Tomas Lagos and Fernando Ordonez and Rafael Sacaan and Hugh Rudnick and Alejandro Navarro-Espinosa and Rodrigo Moreno",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 ; Conference date: 16-07-2017 Through 20-07-2017",

year = "2018",

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day = "29",

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language = "English",

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Lagos, T, Ordonez, F, Sacaan, R, Rudnick, H, Navarro-Espinosa, A & Moreno, R 2018, Discrete optimization via simulation to determine reliable network investments. in 2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Power and Energy Society General Meeting, vol. 2018-January, IEEE Computer Society, pp. 1-5, 2017 IEEE Power and Energy Society General Meeting, PESGM 2017, Chicago, United States, 16/07/17. https://doi.org/10.1109/PESGM.2017.8274589

Discrete optimization via simulation to determine reliable network investments. / Lagos, Tomas; Ordonez, Fernando; Sacaan, Rafael et al.
2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Computer Society, 2018. p. 1-5 (IEEE Power and Energy Society General Meeting; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Discrete optimization via simulation to determine reliable network investments

AU - Lagos, Tomas

AU - Ordonez, Fernando

AU - Sacaan, Rafael

AU - Rudnick, Hugh

AU - Navarro-Espinosa, Alejandro

AU - Moreno, Rodrigo

PY - 2018/1/29

Y1 - 2018/1/29

N2 - Solving optimization problems in power systems planning often imposes a compromise between the accurate representation of the power system operation and the simplifications made in the mathematical methodologies used to find the optimal solution. Hence, classic heuristic algorithms go deep modelling operational details without having a clear message about the quality of the solution, whereas mathematical programming approaches find the optimal solution by (significantly) simplifying system operation. In this vein, this article proposes the utilization of Discrete Optimization via Simulation algorithms to solve optimization problems when a detailed representation of the system and information about the quality of the solution are required. In particular, the Industrial Strength COMPASS algorithm is applied to find the optimal set of new transmission lines that maximizes power system reliability given a certain budget and considering a detailed power system model, where a full unit commitment with network constraints and an hourly sequential Monte Carlo are implemented.

AB - Solving optimization problems in power systems planning often imposes a compromise between the accurate representation of the power system operation and the simplifications made in the mathematical methodologies used to find the optimal solution. Hence, classic heuristic algorithms go deep modelling operational details without having a clear message about the quality of the solution, whereas mathematical programming approaches find the optimal solution by (significantly) simplifying system operation. In this vein, this article proposes the utilization of Discrete Optimization via Simulation algorithms to solve optimization problems when a detailed representation of the system and information about the quality of the solution are required. In particular, the Industrial Strength COMPASS algorithm is applied to find the optimal set of new transmission lines that maximizes power system reliability given a certain budget and considering a detailed power system model, where a full unit commitment with network constraints and an hourly sequential Monte Carlo are implemented.

KW - Discrete Optimization via Simulation

KW - Optimization

KW - Reliability

KW - Sequential Monte Carlo Simulations

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M3 - Conference contribution

AN - SCOPUS:85046349244

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SP - 1

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BT - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017

PB - IEEE Computer Society

T2 - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017

Y2 - 16 July 2017 through 20 July 2017

ER -

Discrete optimization via simulation to determine reliable network investments

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this