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Industrial energy efficiency has received increasing attention in many countries because of its importance in the pursuit of energy supply security, increased economic competitiveness and in the mitigation of greenhouse gases emissions. This paper aimed to evaluate the energy consumption development of the Brazilian pulp and paper industry through an energy decomposition analysis and an energy efficiency index approach over a 30 years period. An international comparison with other important paper-producing countries (i.e., Canada, United States of America, Finland and Sweden) was carried out. It was concluded that despite a significant increase in the energy efficiency levels, responsible for 5.6 PJ savings in electricity consumption and for 38.6 PJ savings in fuels consumption between 1979 and 2009, a saving potential of 7.8 PJ and 146.2 PJ related to the annual consumption of electricity and fuels, respectively, could be identified in the Brazilian pulp and paper industry. Among the countries evolved in the international comparison, both the Swedish and Finnish industries were the most efficient, followed by the Brazilian, American and Canadian, the latter being the only one where there was a reduction in the energy efficiency levels from 1979 to 2009. [ABSTRACT FROM AUTHOR]

Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs' development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development. [ABSTRACT FROM AUTHOR]

This paper addresses the optimization of contracted electricity demand (CD) for commercial and industrial entities, focusing on cost reduction within the Brazilian time-of-use electricity tariff scheme. Leveraging genetic algorithms (GAs), this study proposes a practical approach to determining the optimal CD profile, considering the complex dynamics of energy demand on a city-like load. The methodology is applied to a case study at the Federal University of Pará, Brazil, where energy efficiency and demand response initiatives as well as renewable energy projects are underway. The findings highlight the significance of tailored demand management strategies in achieving energy-related cost reduction for large-scale consumers, with implications for economic efficiency in energy consumption. [ABSTRACT FROM AUTHOR]

On average, 70% of the world's freshwater is used in agriculture, with farmers transitioning to electrical irrigation systems to increase productivity, reduce climate uncertainties, and decrease water consumption. In Brazil, where agriculture is a significant part of the economy, this transition has reached record levels over the last decade, further increasing the impact of energy consumption. This paper presents a methodology that utilizes the U-Net model to detect flooded rice fields using Sentinel-2 satellite images and estimates the electrical energy consumption required to pump water for this irrigation. The proposed approach involves grouping the detected flooded areas using k-means clustering with the electricity customers' geographical coordinates, provided by the Power Distribution Company. The methodology was evaluated in a dataset of satellite images from southern Brazil, and the results demonstrate the potential of using U-Net models to identify rice fields. Furthermore, comparing the estimated electrical energy consumption required for irrigation in each cluster with the billed energy values provides valuable insights into the sustainable management of rice production systems and the electricity grid, helping to identify non-technical losses and improve irrigation efficiency. [ABSTRACT FROM AUTHOR]

The energy balance constitutes a powerful management instrument for government agencies, as it offers an overview of the energy situation of the country (or region) and serves as a guide for energy policies and monitoring of these policies. Although Brazil has published the national energy balance for more than half a century, the national publication does not adequately address energy statistics at the level of the states. This occurs either due to the lack of specific data or the absence of total disaggregation. Accordingly, the elaboration and implementation of public policies for the energy sector in the Brazilian states lack consistent energy statistics. Therefore, this paper aims to present a model for the Brazilian states to elaborate the energy balance. The proposed model consists of applying internationally referenced methodologies to develop a user-friendly software, which includes automatic energy unit conversions, different chart styles, high-level data organization, and Sankey diagrams. As a result, the software can be adopted by local governments as a tool to maintain the state energy balance publication periodically, and hence obtain the detailed information necessary to manage and formulate energy policies. The advantage of the software is that it can be operated by non-experts and the energy flow as well as the entire report can be generated automatically. The proposed software was successfully used to generate the energy balance of the Mato Grosso do Sul state. [ABSTRACT FROM AUTHOR]

In this paper, a methodology was developed to analyze the results of energy efficiency programs used in the electricity distribution sector in Brazil. Analyzing the gains obtained through the investments made, and classifying which actions resulted in the best performance, contributed to decision making on the best allocation of investments to obtain the greatest energy savings. The Brazilian Energy Efficiency program was analyzed with a developed non-parametric model, using the data envelopment analysis method, and the categories of projects with better performance were determined. A database of the results from 1704 projects, from 2008 to 2016 in the Energy Efficiency program in Brazil's electricity distribution sector, was used. The results obtained show that the best performance was achieved by projects in the industrial and cogeneration categories; however, in Brazil these constitute only 4.24% of the projects presented and 5.28% of the total investments in the last eight years, indicating a need to review the regulatory strategies for energy efficiency in this country. [ABSTRACT FROM AUTHOR]

This article examines the inefficient use of resources in the Brazilian transportation system. The energy use growth and external cost generation in this essential economic sector are considerable, and the trend is towards an increasing problem in the coming years. The continued expansion of Brazilian cities and the increase in demand for mobility is a result of a substantial growth in the number of road transport users, as increased earnings enable lower income groups to acquire and use individual motorized means of transport. The aim of this paper is to estimate the potential gains from reducing individual motorized transport by the year 2020. This investigation concludes that in a conservationist scenario, by prioritizing low cost, low technology public policies--which include operation of Bus Rapid Transit systems, walking and cycling facilities and congestion charges, among others--it should be possible to save over USD 30 billion and USD 26 billion in external transportation and infrastructure costs, respectively, up to 2020. In addition, these public policies can save more than 35 million Tons of Oil Equivalents in energy consumption and avoid almost 4,000 thousand tons of local pollution emissions and 37,500 thousand tons of GHG emissions in the same period. [ABSTRACT FROM AUTHOR]

The city of Aripuana is one of the largest wood producer in the state of Mato Grosso, Brazil. Wood residues are used in the electricity generation at three thermoelectric plants in this region. However, the plants have high costs in transporting the wood residues (due to poor road conditions). Hence, this paper compares the energy performance of wood residues in natura and compacted as briquettes by calculating the heating value and determining the influence of moisture content on the energy characteristics of wood residues. The goal is to demonstrate the viability of using briquettes in order to improve thermoelectric generation. The wood residues from this region are affected by the high humidity of the biome. An alternative to improve the use of energy contained in the wood residues is to produce briquettes with lower humidity. This allows one to maintain high levels of heat energy in a lower volume, facilitating handling and storage. The results show that the use of briquettes improved the performance of thermoelectric plants, generating 1 MW of electricity power with less than 1 ton of briquettes. This contributes to the preservation of the environment, reducing operating costs, transportation and storage of the raw materials. [ABSTRACT FROM AUTHOR]

Over the years, electricity consumption behavior in Brazil has been analyzed due to financial and social problems. In this context, it is important to simulate energy prices of the energy efficiency auctions in the Brazilian electricity market. The Markov Chain Monte Carlo (MCMC) method generated simulations; thus, several samples were generated with different sizes. It is possible to say that the larger the sample, the better the approximation to the original data. Then, the Kernel method and the Gaussian mixture model used to estimate the density distribution of energy price, and the MCMC method were crucial in providing approximations of the original data and clearly analyzing its impact. Next, the behavior of the data in each histogram was observed with 500, 1000, 5000 and 10,000 samples, considering only one scenario. The sample which best approximates the original data in accordance with the generated histograms is the 10,000th sample, which consistently follows the behavior of the data. Therefore, this paper presents an approach to generate samples of auction energy prices in the energy efficiency market, using the MCMC method through the Metropolis–Hastings algorithm. The results show that this approach can be used to generate energy price samples. [ABSTRACT FROM AUTHOR]