Investor Presentaiton

eneva Categories Project A brief description of the projects developed in 2021 Forward Curve Back-office Broker Coal Belts Analytical solutions Machine Learning 2.0 Machine Learning 2.5 sustainability report 2021 This project 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 on energy market structures. This project involves the development of an integrated platform for energy contract trading and back-office management. It 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 defaulting in execution, creating a safer environment for the growth of the free market, already underway through PLS 232/2016. This project 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. The project therefore intends to create a digital platform that integrates the capture of thermal images by drone with processing via a machine learning algorithm, in order to automatically generate reports that facilitate maintenance routines and prevent financial losses by demurrage. This project is designed 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 "Detection of gas accumulation signatures in seismic traces using deep-learning" project, under 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. This project aims to evaluate the methodologies included in the ALINE (Automated Learning Intelligence for Exploration) computer system in different test scenarios, with the intention of checking performance and the level of accuracy in the detection of potential accumulations of gas. It also seeks to extend the ALINE algorithms to reading, data preparation and training of the Machine Learning systems employing 3D seismic data. Total expected cost (R$) Sum allocated through to Dec/2019 (R$) Sum allocated in 2020 (R$) 116 > Sum allocated in 2021 (R$) 2,036,440.00 275,790.00 1,380,607.50 380,042.50 3,163,776.69 0.00 1,243,786.25 1,677,990.69 3,143,201.76 0.00 2,214,809.23 928,392.53 1,729,582.70 0.00 181,474.16 1,548,108.54 1,630,742.74 0.00 0.00 815,371.37 annexes

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