Multi-period Optimization Model for the ARE Power Sector

Alberto Betancourt-Torcat; Ali Almansoori

doi:10.1016/j.egypro.2015.07.545

Multi-period Optimization Model for the ARE Power Sector

Alberto Betancourt-Torcat, Ali Almansoori

Chemical and Petroleum Engineering

Research output: Contribution to journal › Conference article › peer-review

8 Scopus citations

Abstract

A multi-period power optimization model for the ARE's electricity sector is presented. The model aims to minimize the cumulative costs and CO₂ emission of the ARE's power sector during the planning horizon. The optimization problem was formulated as a multi-period MILP model in the GAMS modelling system. Previous studies have analyzed the ARE power infrastructure using standard simulation software such as MARKAL and MESSAGE. The present work's novelty consists of determining the optimal evolution of the power generation infrastructure during different time periods under operational and environmental constraints. The optimization model was used to study the ARE's power system for the time periods comprised between the years 2015 and 2040. The simulation results show that the mathematical model is a valuable tool for planning the optimal evolution of the power plants' fleet in the country, reduce levelized electricity costs and emissions, meet energy targets, and evaluate new power technologies.

Original language	British English
Pages (from-to)	2791-2797
Number of pages	7
Journal	Energy Procedia
Volume	75
DOIs	https://doi.org/10.1016/j.egypro.2015.07.545
State	Published - 2015
Event	7th International Conference on Applied Energy, ICAE 2015 - Abu Dhabi, United Arab Emirates Duration: 28 Mar 2015 → 31 Mar 2015

Keywords

ARE
Multi-period
Nuclear
Optimization
Power system
Renewables

UN SDGs

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

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10.1016/j.egypro.2015.07.545

Cite this

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title = "Multi-period Optimization Model for the ARE Power Sector",

abstract = "A multi-period power optimization model for the ARE's electricity sector is presented. The model aims to minimize the cumulative costs and CO2 emission of the ARE's power sector during the planning horizon. The optimization problem was formulated as a multi-period MILP model in the GAMS modelling system. Previous studies have analyzed the ARE power infrastructure using standard simulation software such as MARKAL and MESSAGE. The present work's novelty consists of determining the optimal evolution of the power generation infrastructure during different time periods under operational and environmental constraints. The optimization model was used to study the ARE's power system for the time periods comprised between the years 2015 and 2040. The simulation results show that the mathematical model is a valuable tool for planning the optimal evolution of the power plants' fleet in the country, reduce levelized electricity costs and emissions, meet energy targets, and evaluate new power technologies.",

keywords = "ARE, Multi-period, Nuclear, Optimization, Power system, Renewables",

author = "Alberto Betancourt-Torcat and Ali Almansoori",

note = "Publisher Copyright: {\textcopyright} 2015 The Authors. Published by Elsevier Ltd.; 7th International Conference on Applied Energy, ICAE 2015 ; Conference date: 28-03-2015 Through 31-03-2015",

year = "2015",

doi = "10.1016/j.egypro.2015.07.545",

language = "British English",

volume = "75",

pages = "2791--2797",

journal = "Energy Procedia",

issn = "1876-6102",

publisher = "Elsevier Ltd",

}

TY - JOUR

T1 - Multi-period Optimization Model for the ARE Power Sector

AU - Betancourt-Torcat, Alberto

AU - Almansoori, Ali

PY - 2015

Y1 - 2015

N2 - A multi-period power optimization model for the ARE's electricity sector is presented. The model aims to minimize the cumulative costs and CO2 emission of the ARE's power sector during the planning horizon. The optimization problem was formulated as a multi-period MILP model in the GAMS modelling system. Previous studies have analyzed the ARE power infrastructure using standard simulation software such as MARKAL and MESSAGE. The present work's novelty consists of determining the optimal evolution of the power generation infrastructure during different time periods under operational and environmental constraints. The optimization model was used to study the ARE's power system for the time periods comprised between the years 2015 and 2040. The simulation results show that the mathematical model is a valuable tool for planning the optimal evolution of the power plants' fleet in the country, reduce levelized electricity costs and emissions, meet energy targets, and evaluate new power technologies.

AB - A multi-period power optimization model for the ARE's electricity sector is presented. The model aims to minimize the cumulative costs and CO2 emission of the ARE's power sector during the planning horizon. The optimization problem was formulated as a multi-period MILP model in the GAMS modelling system. Previous studies have analyzed the ARE power infrastructure using standard simulation software such as MARKAL and MESSAGE. The present work's novelty consists of determining the optimal evolution of the power generation infrastructure during different time periods under operational and environmental constraints. The optimization model was used to study the ARE's power system for the time periods comprised between the years 2015 and 2040. The simulation results show that the mathematical model is a valuable tool for planning the optimal evolution of the power plants' fleet in the country, reduce levelized electricity costs and emissions, meet energy targets, and evaluate new power technologies.

KW - ARE

KW - Multi-period

KW - Nuclear

KW - Optimization

KW - Power system

KW - Renewables

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U2 - 10.1016/j.egypro.2015.07.545

DO - 10.1016/j.egypro.2015.07.545

M3 - Conference article

AN - SCOPUS:84947125365

SN - 1876-6102

VL - 75

SP - 2791

EP - 2797

JO - Energy Procedia

JF - Energy Procedia

T2 - 7th International Conference on Applied Energy, ICAE 2015

Y2 - 28 March 2015 through 31 March 2015

ER -

Multi-period Optimization Model for the ARE Power Sector

Abstract

Keywords

UN SDGs

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