Integrated Planning

Tools

Applying pioneering integrated planning modeling tools, CenergiaLab supports energy and climate policymakers in understanding the synergies and trade-offs of technological innovation pathways towards a low-carbon transition in Brazil, in Latin America and in the world.

 

CenergiaLab team has developed integrated optimization energy models, especially with the MESSAGE platform since 2003 and, more recently, with TIMES and REMIX-CEM-B. Over time, these top-down integrated assessment models (IAMs) have been upgraded and tailored to better represent the Brazilian, Latin American countries and global regions. These models incorporate over 10,000 energy supply and demand technological options, and evaluate their interactions with economic development, climate change, local air pollution, water footprint, land use change and climate policies.

 

The IAMs developed in CenergiaLab are integrated with sectoral models to better understand specificities of energy planning from a bottom-up perspective. It also includes softlinks with other tools based on life cycle assessment (LCA), process analysis, econometrics and input-output matrix methods to identify interlinkages between energy planning and other multiple dimensions of sustainability.

 

Global Models

COFFEE
Computable Framework For Energy and the Environment

Platform: MESSAGE

  •  Perfect foresight linear programming optimization model

  •  Global model with 18 regions

Time Horizon:From 2010 to 2100, in 14 steps

  •  Includes all the Energy and the Land-use Systems

Main Purpose:

  • Assessment of potential synergies/trade-offs in energy, environmental and climate policies

  •  Completely integrated (hard-link) between energy and land

  •  First global IAM built in a developing country

Sources:

TEA
Total Economy Assessment

Platform: GAMS

  • Recursive dynamic general equilibrium model

  • Global model with 18 regions

Time Horizon: From 2010 to 2100, in 14 steps

  • All economic sectors (GTAP database), with focus on Energy and Land-use Systems

Main purpose:

  • Assessment of climate change mitigation and economic impacts

  • Based on the frameworks of the GTAPinGAMS and EPPA models

  • Soft-linked with COFFEE and BLUES

Sources:

 

National Models

BLUES
Brazilian Land-Use and Energy Systems model

Platform: MESSAGE

  •  Perfect foresight linear programming optimization model

  • Main Region:Brazil

  •  5 regions

Time Resolution: From 2010 to 2050 (9 steps), with 288 time steps (monthly/hourly) per year

  •  Includes all the Energy and the Land-use Systems

Main Purpose:

  • Assessment of technology, energy, environmental and climate policies for Brazil

  •  Enhanced regional, sectorial and land-cover characterizations

  •  Very high-level of technological detail (bottom-up) with country-specific parameters

Sources:

ELENA
Ecuador Land Use and Energy Network Analysis Model

Platform: MESSAGE

  •  Perfect foresight linear programming optimization model

  • Main Region: Ecuador

  •  4 regions

Time Resolution: from 2015 to 2050 (8 steps), with 60 time steps (monthly with 5-periods daily) per year

  •  Includes all the Energy and the Land-use Systems

Main Purpose:Assessment of energy and climate policies for Ecuador

  •  Based on the BLUES platform, with specific considerations for Ecuador

  •  Suitable for assessing long-term scenarios

Sources:

  • Currently in development (under review). Developer: Rafael Soria.

 

Sectoral Models

ORION
Oil Refining Industry Optimization and syNergies
Multi-regional optimization model for refining industries

Platform: GAMS

  •  MIP optimization model

  • Regions:Custom (Default: multi-regional for Brazil)

Time Resolution: From 2015 to 2040

Main Purpose:

  • Optimization of refinery capacity expansion, production profile and GHG emissions

  •  High level of technological detail in refining processes

  •  Details fourteen processing units, Hydrogen generation and Cogeneration units

  •  Considers three crude oil options and nine types of oil derivatives

Sources:

STORM
Short-Term power system OpeRation Model
Optimization dispatch model for power sector

Platform: GAMS

  •  Deterministic optimization model (with Robust optimization option)

  • Regions:Custom (Default: Brazilian sub-systems)

Time Resolution: Custom (Default: hourly resolution)

Main Purpose:

  • Dispatch of power sector, dealing with hydrothermal Unit Commitment

  •  Deals with the hydrothermal Unit Commitment problem

  •  Considers technical restrictions of power plants, as well as transmission capacity limitations

  •  Modelling of wind generation and hydro production cascade effects

Sources:

  • Viviescas Latorre C. C., 2019. "Robust optimization applied to a hydrothermal unit commitment problem with dispatchable wind power". DSc thesis, Programa de Planejamento Energético, COPPE/UFRJ.

CAESAR
Carbon and Energy Strategy Analysis for Refineries
Simulation of oil refineries with focus on energy efficiency and carbon emission

Platform: Excel

  •  Simulation, with LP optimization option for energy consumption and mitigation of GHG

  • Regions:Custom single region (eg: single refinery, refinery block, country)

Time Resolution:5 time steps

Main Purpose:

  • Assessment of production profile, energy and consumption, and GHG emissions

  •  Includes fifteen processing units with estimated utilities and water consumption coefficients

  •  Includes over 200 energy efficiency and mitigation options, such as CCS

Sources:

MESH
Model for Evaluation of Solar Heat
Optimization Model for Solar Thermal Energy Dimensioning

Platform: GAMS

  • Mixed-Interger Nonlinear Programming

  • Regions: Custom single region (defined by solar resource input) 

Time Resolution: hourly 

Main Purpose:

  • Definition of optimal solar collector, heat transfer fluid and solar field configuration

  • Optimization of heat sources dispatch

  • Considers hourly variability of solar resource and collector efficiency

  • Modelling of solar collector and heat transfer fluid as function of solar irradiance and working temperature

Sources:

©2021 

Energy Planning Program, COPPE, Universidade Federal do Rio de Janeiro

Centro de Tecnologia, Sala C-211, Cidade Universitária, Ilha do Fundão

21941-972 Rio de Janeiro, RJ, Brazil

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