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Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide. [ABSTRACT FROM AUTHOR]

Since the 1970s, Brazil has carried out the most successful world program of commercial biomass for use and production of energy by stimulating its sugarcane industry and promoting the large-scale production of ethanol nationwide in response to the first oil shock. Today, the technologies behind ethanol production are well established. Brazil is the world's largest sugarcane supplier, producing its ethanol at a competitive price. If other sugarcane producing countries decided to join Brazil's move toward the production of this biofuel, what impacts might there be for each country's economy and employment? This is what we investigate in this paper. Prime candidates for ethanol production include Australia, China, Colombia, India, Indonesia, Mexico, Pakistan, the Philippines, Thailand, and the United States of America. We evaluated the potential socioeconomic impacts of developing this promising industry by using an input–output approach. More specifically, we adapted the Brazilian method of producing ethanol to these countries' distinct economies. We augmented the input–output table of each country, inserting a new ethanol industry based on the Brazilian ethanol production model. We also augmented their new ethanol industry's sales following a hypothetical hydrous and anhydrous ethanol consumption scenario. Thereafter, we reconcile the national accounts, concluding our analysis by quantifying and comparing the different net effects of this new industry for each of the assessed countries for the year of 2009. We demonstrate which industries would be expected to be positively or negatively impacted by this substitution in each country; and find that not all of the countries we assessed would experience positive socioeconomic results from emulating Brazil's production of ethanol. [ABSTRACT FROM AUTHOR]

Software-defined networking and network functions virtualisation are making networks programmable and consequently much more flexible and agile. To meet service-level agreements, achieve greater utilisation of legacy networks, faster service deployment, and reduce expenditure, telecommunications operators are deploying increasingly complex service function chains (SFCs). Notwithstanding the benefits of SFCs, increasing heterogeneity and dynamism from the cloud to the edge introduces significant SFC placement challenges, not least adding or removing network functions while maintaining availability, quality of service, and minimising cost. In this paper, an availability- and energy-aware solution based on reinforcement learning (RL) is proposed for dynamic SFC placement. Two policy-aware RL algorithms, Advantage Actor-Critic (A2C) and Proximal Policy Optimisation (PPO), are compared using simulations of a ground truth network topology based on the Rede Nacional de Ensino e Pesquisa Network, Brazil's National Teaching and Research Network backbone. The simulation results show that PPO generally outperformed A2C and a greedy approach in terms of both acceptance rate and energy consumption. The biggest difference in the PPO when compared to the other algorithms relates to the SFC availability requirement of 99.965%; the PPO algorithm median acceptance rate is 67.34% better than the A2C algorithm. A2C outperforms PPO only in the scenario where network servers had a greater number of computing resources. In this case, the A2C is 1% better than the PPO. [ABSTRACT FROM AUTHOR]

Transitioning from a carbon-intensive development path to a low-carbon economy requires understanding of emission sources and its drivers. To achieve Nationally Determined Contribution targets discussed under the Paris Agreement, countries must project emission baselines considering different levels of ambition and sectoral performances and monitor government policies and mitigation actions. This study develops a Monitoring, Reporting, and Verification (MRV) framework based on energy use and carbon emission scenarios for Brazil up to 2030, focusing on transport. Three scenarios are developed based on different political commitments. All scenarios and mitigation actions are discussed under the Brazilian Forum on Climate Change, which is recognized as one of the most important institutional instruments of the National Policy on Climate Change. Results reveal a 41% abatement in CO2e emissions when comparing the most ambitious scenario to the conservative one. MRV framework indicates that Brazil is on track to a low carbon economic transition, although joint action is needed. This is mainly due to the increasing penetration of bioenergy into the transport energy matrix, while electromobility does not expand in Brazil at the pace of major international players such as Europe and China. Special contribution of this paper is on the role of bioenergy in prospective carbon emission scenarios, which is a lack in the literature. [ABSTRACT FROM AUTHOR]

In this paper, we forecast residential electricity consumption in Brazil considering the variability in consumption behavior in different regions. In order to do so, we use a bottom-up approach to estimate long-term electricity consumption that considers three technology-driven scenarios: one assuming reference efficiency development, another one based on the Brazilian government's predictions, and the third one assuming high efficiency. The results show an increase of residential electricity consumption due to the increasing appliance ownership rate, especially air conditioning, as well as the increasing number of households. In addition, it is shown that 96 TWh of electricity could be saved in the highest efficiency scenario due to significant efficiency gains between 2016 and 2050. Further, the results indicate the southeast of the country has the highest potential for consumption reduction: by 27% in the most efficient scenario. This work is the first to use a bottom-up approach to forecast the residential electricity consumption by region and by technology-driven scenarios in Brazil. With this methodology, it is possible to indicate which types of appliances should be targeted by policy makers when designing energy efficiency incentives. Hence, this model can be used as a roadmap to achieve the desired efficiency gains in Brazil. [ABSTRACT FROM AUTHOR]

One of the main barriers to the development of energy efficiency (EE) projects in Brazil is the decision-makers' lack of knowledge about the risks of the projects. The Brazilian Government's Procedures of Energy Efficiency Program (PROPEE) is currently one of the main sources of funding for energy efficiency (EE) projects. The method for evaluating the technical and economic feasibility of projects presented in PROPEE applies the traditional discounted cash flow (DCF) methodology to calculate the net present value (NPV). The energy price used in this model is a fixed value calculated through the postponement of investments (cost of avoided demand) and/or reduction of operating expenses (avoided energy cost). The avoided costs for a given voltage level are incurred throughout the power system, upstream of the consumption unit (view of the electrical system's operator). The PROPEE's methodology, applied on a large scale in Brazil, does not consider some technical uncertainties present in EE projects, nor the market uncertainty regarding the fluctuation of the energy price paid by the consumer units. This paper evaluates the investment risk of EE projects (consumer's perspective) adopted by the Brazilian market, taking as example a large electricity consumer. A methodology is proposed, which, considering the technical and economic uncertainties, performs a more comprehensive and realistic analysis of the complex business scenario involving the EE projects. This case study considered the data collected by a team of independent engineers, for the first time in January 2009 and updated in January 2015, to assess the energy efficiency potential of a commercial consumer unit installed in the city of Rio de Janeiro and connected to the grid of local distribution level voltage 13.8 kV. This study demonstrates a model that made the risk management projects viable in energy efficiency demand-side management (DSM). However, it could also be applied in other markets as well. Understanding how the uncertainties affect decision-making in EE projects is essential for developing a more comprehensive outlook on constructive and regulatory perspective, contributing to the promotion of energy efficiency projects. [ABSTRACT FROM AUTHOR]