Sustainability Report ENEVA 2020
5.2.2 R&D
Projects
[EU8]
Celso
5.2.2.2
Analytical Solutions
Forward Curve
It aims to develop a front-end tool for
probabilistic forecasting of electricity
forward contract prices through the
creation of software based on statistical
models, which consider both the current
Brazilian market scenario and also future
changes involving hourly prices. It also
takes into account the trading of new
financial products and uses an
international benchmark analysis of
energy market structures.
Broker Back-office
It encompasses the development of an
integrated platform for energy contract
trading and back-office management.
The project will create an electronic
environment for bilateral contracting
with potential reduction of back-office
and financial risks through the
Organized OTC Market. This initiative
increases trust between the negotiating
parties and reduces the informality of
contracts and default in execution,
creating a safer environment for the
growth of the free market, already
underway through PLS 232/2016.
Coal Belts
It aims to develop an inspection system
with image analysis software based on
machine learning that identifies overlap
in coal-fired power plant conveyor belts,
focusing on failure prediction and
increasing their service life. Thus, the
project intends to create a digital
platform that integrates the capture
of thermal images by drone with
processing via machine learning
algorithm, in order to automatically
generate reports that facilitate
maintenance routines and prevent
financial losses by demurrage.
|
Machine Learning 2.0
To improve methodologies and tools
for characterizing regions with potential
gas accumulation for the Parnaíba
Thermal Power Complex within the
ALINE (Automated Learning Intelligence
for Exploration) computer system. The
project aims to improve efficiency in
the interpretation of seismic data and
reduce exploration costs for natural
gas reservoirs. The initiative is a
continuation of the ANP R&D project
"Detection of gas accumulation
signatures in seismic traces using deep-
learning", in which the alpha version of
the ALINE system was developed, using
post-stack seismic image processing
methodology and machine learning
algorithms to more accurately identify
regions with potential gas accumulation.
Expected total amount:
R$ 2,072,740
Amount allocated until 2020:
R$ 1,656,397
(R$ 1,380,607 in 2020)
Expected total amount:
R$ 2,829,190
Amount allocated in 2020:
R$ 1,243,786
Expected total amount:
R$ 2,796,098
Amount allocated in 2020:
R$ 2,214,809
Expected total amount:
R$ 1,817,491
Amount allocated in 2020:
R$ 181,474
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SUSTAINABILITY REPORT [ENEVA 2020]
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