Hello.
In this session we will address the Integrated Assessment Models and introduce the MEDEAS
models.
In the previous topic we have seen the seriousness and complexity of the problem of sustainability.
The international community has reacted in different ways to this alarm.
In the case of the European Union, one of the political actions has been to promote
research into energy sustainability and climate change.
Within the Research & Innovation actions of the H2020 program, one of the calls was Competitive
Low-Carbon Energy, and one of the topics was: Modeling and Analyzing the energy system,
its transformation and impacts.
Through this call, the Horizon 2020 program has funded 4 research projects:
REFLEX.
Analysis of the European energy system under the aspects of flexibility and technological
progress.
REEEM.
Role of technologies in an energy efficient economy – model based analysis policy measures
and transformation pathways to a sustainable energy system
SET-NAV.
Navigating the roadmap for clean, secure and efficient energy innovation.
MEDEAS.
Guiding European policy toward a low-carbon economy.
Modelling energy system development under environmental and socioeconomic constraints.
The general objective of these projects has been to understand the complex links, interactions
and interdependencies between the different actors, the available technologies and the
impact of the different interventions on all levels from the individual to the whole energy
system.
To achieve this goal it has been necessary to provide model based decision support tools
for the different actors in the energy system in order to facilitate handling the complex
system.
For this reason, one of the main results of the MEDEAS project has been the development
of a set of integrated assessment models aimed at helping decision-making on energy and climate
change.
One of the fundamental objectives of this course is to facilitate the use of these integrated
assessment models.
But, what is an integrated assessment model?
An Integrated Assessment Model (IAM) is a mathematical computer model that integrates
economic, technological, environmental and social variables, in order to understand the
effects of some variables on others and help in the political decision making in these
areas.
Sometimes we will refer to these models as integrated energy-economy-environment models,
or E3 models.
Some of the usual purposes for developing an IAM are:
To provide a coherent framework for organizing and assessing knowledge about climate change.
To assist in the assessment of the consequences of different policy options.
To understand which of the many uncertainties about the modeled systems are most important.
To better understand the interaction between the components of the modeled system (e.g.
economy, technological, and environmental subsystems).
Some of the most known IAMs are: World3, DICE, IMAGE, GCAM, POLES, MAGICC, MERGE, GEM-E3,
TIMES or WIAGEM … If there are so many IAMs, why have we developed
a new one in the MEDEAS project?
Each of these IAMs has different characteristics and a large field of application, but most
of them have some shortcomings or limitations.
The set of IAMs developed in the MEDEAS project tries to overcome some of these shortcomings
and provides some relevant developments: Representation of economic processes: integration
of input-output analysis with system dynamics modelling.
Consideration of geological constraints for the extraction of non-renewable energy sources.
Simple and transparent methodology to integrate climate change damages.
Assessment of mineral demand associated to the energy transition.
Endogenous and dynamical implementation of net energy approach considering energy investments
for the transition (EROI).
All these points will be explained in later topics of this course, but it is advisable
to have a previous idea about the systems dynamics methodology.
System dynamics is a methodology and mathematical modeling technique to understanding the nonlinear
behaviour of complex systems over time using stocks, flows, internal feedback loops, functions
and time delays.
Two of the key elements are stocks and flows.
Stocks are accumulations.
They characterize the state of the system and generate the information upon which decisions
and actions are based.
Stocks give systems inertia and provide them with memory.
They are represented by rectangles.
Flow variables are the derivatives of the stocks.
They may be inflow or outflow.
Stocks are the integral of the difference between its inflow and its outflow.
It is represented by a valve sign.
For example, the concentration of CO2 in the atmosphere is a stock that has two flows:
CO2 emissions that increase the concentration (INFLOW) and CO2 removals that reduce the
concentration of CO2 (OUTFLOW).
In the MEDEAS models there are hundreds of stocks, flows, equations, delays and auxiliary
variables.
In order to understand the model it is necessary to have a general overview of it.
In later topics each of the parts of the model will be described.
The MEDEAS models have been initially programmed with the Vensim software and subsequently
have been translated into python.
Therefore, there are two versions available.
in order to use the Vensim version, it is necessary to have the Vensim software in one
of its versions: "Reader" or "DSS".
However, the python version is open-source and does not require any commercial software.
The MEDEAS models have been developed in three geographic scales: World, Europe and country.
The country models (Austria and Bulgaria only) need data provided by the European model.
In turn, the European model needs data provided by the world model.
The structure of these models is essentially the same, and therefore in this course we
will focus on understanding the world model.
The MEDEAS model is conceptually organized in 7 large modules: economy, energy, infrastructures,
materials, land use, social and environmental impacts indicators and climate change.
The modules of economy and energy are the most extensive and reach the highest degree
of disaggregation.
The model consists of a modular and flexible structure, where each module can be expanded/simplified/replaced
by another version or new modules can be added.
The figure in the slide shows the interrelations between the 7 modules represented by boxes.
The main characteristics are: Economy and population: the economy of MEDEAS
is modelled following a Post-Keynesian approach assuming disequilibrium, demand driven growth
and supply constraints.
The economic structure is captured by the integration of IOT (35 industrial sectors
and households).
Energy.
This module includes the renewable and non-renewable energy resources potentials and availability,
taking into account biophysical and temporal constraints.
Five types of final energy (electricity, heat, solids, gases and liquids) and 23 primary
energy sources have been considered.
A wide variety of energy technologies are modeled and the EROI is estimated.
The energy infrastructures module represents the facilities of power plants to generate
electricity and heat.
Climate.
This module projects the climate change levels due to the GHG emissions generated by the
human societies, which also feed-back through a damage function.
Materials.
Materials are required by the economy and MEDEAS especially tracks the material requirements
for the construction and O&M of the energy facilities.
The extraction demands are subsequently compared with the levels of available metrics of reserves
and resources.
Land-use.
This is the less developed module of MEDEAS, and it mainly accounts for the land requirements
of the renewable energies.
Social and environmental impacts.
This module translates the “biophysical” results of the simulations into metrics related
with social and environmental impacts.
The objective of this module is to contextualize the implications for human societies in terms
of well-being for each simulation.
The economic module demands energy from the energy module.
The energy consumption produces GHG emissions that are the input of the climate module.
In turn, climate change damages the economy, which is an important feedback loop.
The construction of new energy facilities implies an important consumption of materials.
The use of land also influences our climate.
Finally, the availability of energy resources, the economy and the climate determine some
of the most important social and environmental impact indicators.
In order to run the models, we need to define the values of a set of inputs (hypotheses
and policies) that define a scenario.
The scenarios are a key point to be able to properly use the models.
But, what is a scenario?
Socioeconomic scenarios are plausible representations of the future based on coherent, and internally
consistent, assumptions about the evolution of key social and economic drivers.
Examples of these drivers are economic growth, technological development and population.
They are not intended to be predictive, but are designed to explore the implications of
different futures.
In summary, after this topic we should be able to answer at least the following questions:
What is an integrated assessment model?
What is the general structure of the MEDEAS models?
What are the general characteristics of the MEDEAS model?
What are the scenarios?
In the following topics we will describe each module of the MEDEAS models.