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<!doctype html>
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<title>Oldies | Gabriel Kasmi</title>
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<h1 class="title">Older projects</h1>
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<ul>
<li><a href="#Atlas">ATLAS Model</a></li>
<li><a href="#Tassu">Wolfpacks</a></li>
<li><a href="#APE">French deputies</a></li>
<li><a href="research.html">Back to research</a></li>
<li><a href="index.html">Back to home</a></li>
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<section>
<h2 id="Atlas">ATLAS: modelling short-term European electricity markets</h2>
<p>
The ATLAS model simulates the various stages of the electricity market chain in Europe,
including the formulation of offers by different market actors, the coupling of European
markets, strategic optimization of production portfolios and, finally, real-time
system balancing processes. ATLAS was designed to simulate the various electricity
markets and processes that occur from the day ahead timeframe to real-time with a high
level of detail. Its main aim is to capture impacts from imperfect actor coordination,
evolving forecast errors and a high-level of technical constraints--both regarding
different production units and the different market constraints.
</p>
<p>
During my work-study contract at RTE, I was involved with the implementation of
the "day-ahead-orders" module of the simulation model. This module consists in simulating
the formulation of market orders. This formulation aims at maximizing the market participant's
profit, but should reflect the technical constraints of their portfolio of means of productions.
A particular emphasis was laid on implementing an optimization program for the
formulation of thermal orders, aiming at reflecting the technical constraints of
these technologies. This optimization program for thermal units relies heavily on mixed-integer
linear programming (MILP).
</p>
<p>
The deliverable resulting from the project is accessible
<a href="https://www.osmose-h2020.eu/wp-content/uploads/2022/02/OSMOSE-D2.3-ModelsForMarketSimulation_Final.pdf">here</a>,
and the supporting preprint is accessible
<a href="https://arxiv.org/abs/2402.12848">here</a>.
</p>
<p>
<b>Reference</b>:
<ul>
<li>
Little, E., Cogen, F., Bustarret, Q., Dussartre, V., Lâasri, M.,
Kasmi, G., ... & Bourmaud, J. Y. (2024). ATLAS: A Model of Short-term European
Electricity Market Processes under Uncertainty. <i>arXiv preprint arXiv:2402.12848</i>.
</li>
</ul>
</p>
<h2 id="Tassu">Counting wolfpacks in Finland</h2>
<p>
In January 2019 the University of Jyvaskyla and the
National Resources Institute Finland (Luke) started a collaboration to implement a new
approach for estimating the wolves population in southern Finland.
The end goal is to its aim is to propose an online assessment of the
Finnish wolf population using a multiple target tracking algorithm based on a
dynamic statistical model.
</p>
<p>
Currently, estimations are carried out using yearly surveys and population
simulation models are used to fill the gap between two rounds of estimation.
The model is run using different specifications and when new data is available,
prediction outside the observed realizations are discarded.
Fresh data then serves as the new initial conditions of the model.
This method allows for online and frequent estimation of the number of wolves.
</p>
<p>
On the other hand, as part of the wolves monitoring policy in Finland,
Luke maintains a database of wild animals observations.
This database, called TASSU, is updated on a daily basis and the
idea would be to develop a statistical model that could provide a
real-time estimation of the number of wolves packs.
This estimation would then be available to the public through a dedicated website.
Besides, compared to other approaches (e.g. surveys or GPS tracking)
this method, if proven reliable, could be much more cost-efficient.
</p>
<p>
The Department of Mathematics and Statistics focuses on developing the
estimation algorithm based on a statistical model. In order to do so,
it is necessary to first construct a dynamic and an observation model.
The former describes how new packs are formed or disappear while the observation model
links the latent dynamics to the actual observations that feed the TASSU database.
Among others, this observation model needs to takes into account the fact that all
packs are not necessarily immediately observed.
</p>
<p>
From a mathematical perspective, this setting can be seen as a filtering problem,
i.e., a dynamic situation where incomplete signals (the observations) are received from
a latent unobserved system (the wolf packs population).
These observations can be noisy and yet one wants to use them in order to provide a
”best estimation” of the current status of the system.
</p>
<p>
More precisely, the filtering method that was chosen is a particle filter
(or sequential Monte-Carlo) that allows computing Monte-Carlo approximations when
dealing with filtering problems. The construction of this filter is gradual.
The starting point is to simulate the dynamic and observation models in a very
simple manner and to see if inference in this context is feasible.
The main question of this internship was to know whether inference could be made
in the context of wolf packs tracking.
</p>
<p>
The internship report can be accessed
<a href="https://drive.google.com/file/d/1AEypPf6nrcfW42oFfEkHeYRWtLP9iR0M/view?usp=drive_link">here</a>
and the resulting publication is accessible <a href="https://doi.org/10.1016/j.ecolmodel.2022.110101">here</a>.
</p>
<p>
<b>Reference</b>:
<ul>
<li>
Karppinen, S., Rajala, T., Mäntyniemi, S., Kojola, I., & Vihola, M. (2022).
Identifying territories using presence-only citizen science data:
An application to the Finnish wolf population. <i> Ecological Modelling, 472</i>, 110101.
</li>
</ul>
</p>
<h2 id="APE">APE's master thesis</h2>
<p>
<b>Abstract</b>: What incentives do politicians respond to? Based on aggregated data of the French
National Assembly activities, we constructed a dataset designed for estimating the impact
of the majority. Our fixed-effect model allows us to document a 4.67% increase in the
probability to attend committee meetings and a decrease in 6.48% in the probability to
intervene in floor meetings associated with the majority. The qualitative pattern argues
in favor or a majority focused on moving the Government’s agenda forward while leaving
to the floor to the opposition during public meetings. Thus, it suggests that the
subordination of the National Assembly to the Executive branch originates from the subordination
of the majority group. These results provide renewed evidence of what has
been highlighted by earlier literature as a distinctive pattern of the National Assembly
and show how differences in political statuses can influence otherwise similar deputies.
</p>
<p>
You can access the master thesis
<a href="https://drive.google.com/file/d/1sWWr9xmrkHjb3-lnMT80lPfkOYjObcJx/view?usp=drive_link">here</a> and
the Beamer presentation <a href="https://drive.google.com/file/d/1QcPQoFzOgcXKomatCWT_WNexZ8U3J8os/view?usp=drive_link">here</a>.
For this project, I used the data gathered from the non-profit association <a href="https://www.regardscitoyens.org/">Regards Citoyens</a>
and accessible on the website <a href="https://www.nosdeputes.fr/">Nos Deputés</a>. The supporting dataset in .dta (Stata) format can be accessed here:
<a href="https://doi.org/10.5281/zenodo.10980404"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.10980404.svg" alt="DOI"></a>
</p>
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