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The sugarcane industry has assumed an increasingly important role at a global level, with countries such as Brazil and India dominating the field. However, this causes environmental problems, since the industry produces large amounts of waste, such as sugarcane bagasse. This by-product, which is energetically partially recovered in sugar mills and in the pulp and paper industry, can make a significant contribution to the general use of biomass energy, if the usual disadvantages associated with products with low density and a high moisture content are overcome. From this perspective, thermochemical conversion technologies, especially torrefaction, are assumed to be capable of improving the fuel properties of this material, making it more appealing for potential export and use in far-off destinations. In this work, sugarcane samples were acquired, and the process of obtaining bagasse was simulated. Subsequently, the bagasse was dried and heat-treated at 200 and 300 °C to simulate the over-drying and torrefaction process. Afterward, product characterization was performed, including thermogravimetric analysis, elemental analysis, calorimetry, and energy densification. The results showed significant improvements in the energy content, from 18.17 to 33.36 MJ·kg−1 from dried bagasse to torrefied bagasse at 300 °C, showing that despite high mass loss, there is potential for a future value added chain for this waste form, since the increment in energy density could enhance its transportation and use in locations far off the production site. [ABSTRACT FROM AUTHOR]

Considering the negative consequences of the excessive use of non-renewable energy and the development of technologies related to photovoltaic energy, the present paper aims to analyze if the photovoltaic systems are economically viable for university hospitals. A photovoltaic system was designed in the parking lot of the University Hospital of the Federal University of São Carlos (UFSCar) and analyzed the financial viability of its installation. As a result, the photovoltaic system is financially viable, with an expected generation of 194.2 MWh in the first year and a payback of 7 years. Thus, this paper contributes to the feasibility of photovoltaic projects in university hospitals, reducing electric energy consumption, reducing its operational costs, reducing the emission of pollution, and diversification of the Brazilian energy matrix. Furthermore, the results can be used as a scientific basis for other fields, such as public and private hospitals and clinics. [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]

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

Copyright of Revista em Agronegócio e Meio Ambiente is the property of Revista em Agronegocio e Meio Ambiente and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Natural resources in the current scenario of energy production and consumption demands appropriate management. Due to increasing urbanization worldwide, energy consumption optimization has become fundamental, including in the building sector. Many authors mention bioclimatic architecture as an intelligent way to achieve energy efficiency, reducing energy consumption while providing thermal comfort for the users. This paper aims to evaluate the energetic performance of a bioclimatic pilot plant in Bioclimatic zone 2. The methodology to evaluate the energetic performance of the bioclimatic building was developed from hygrothermal measurements and simulations in eQUEST version 3.65. The building was compared to its similar nonbioclimatic one by changing its envelope characteristics in the simulation. The results show the efficiency of bioclimatic strategies, which ensures the building's thermal and hygrometric stability, besides thermal comfort conditions most of the time. Consequently, these strategies allow one to reduce about 25% of the electric energy consumption compared to the nonbioclimatic building. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the information about protection of technologies related to distributed generation (DG) of electric energy, available in the Brazilian patent bank, in the period between 2011 and 2020. Considering that the energy sector has strategic role for companies and countries, analyzing technological trends in the area can help management and decision making. As a methodological procedure, (1) data were collected from the national database of the Instituto Nacional de Propriedade Industrial - INPI (National Institute of Industrial Property) -- in July 2020, (2) associated with keywords and the Classificação Internacional de Patentes - IPC (International Patent Classification) for research and (3) treated with the aid of Microsoft Excel and IBM SPSS Statistics version 25 software. The variables found and analyzed were: nature of the patent; order status; international classification; year of filing; publication of request; countries of origin of depositors; main depositors; state of origin of depositors; electrical system structure; and types of energy sources. The results demonstrated that the number of patent filings fluctuated over the years; that there was a significant growth in the number of deposits in the years that normative resolution n° 482/2012, responsible for regularizing DG in Brazil, was published or revised and that most of the technologies deposited are intended for power generation, with emphasis on that use wind energy. [ABSTRACT FROM AUTHOR]

In the literature, it is well known that there is a bidirectional causality between economic growth and energy consumption. This is why it is crucial to forecast energy consumption. In this study, four deep learning models, i.e., Long Short-Term Memory (LSTM), stacked LSTM, bidirectional LSTM, and Gated Recurrent Unit (GRU), were used to forecast energy consumption in Brazil, Canada, and France. After a training test period, the performance evaluation criterion, i.e., R2, mean square error, root mean square error, mean absolute error, and mean absolute percentage error, was performed for the performance measure. It showed that GRU is the best model for Canada and France, while LSTM is the best model for Brazil. Therefore, the energy consumption prediction was made for the 12 months of the year 2017 using LSTM for Brazil and GRU for Canada and France. Based on the selected model, it was projected that the energy consumption in Brazil was 38 597.14–38 092.88, 63 900–4 800 000 GWh in Canada, and 50 999.72–32 747.01 GWh in France in 2017. The projected consumption in Canada was very high due to the country's higher industrialization. The results obtained in this study confirmed that the nature of energy production will impact the complexity of the deep learning model. [ABSTRACT FROM AUTHOR]

Copyright of Revista CESUMAR: Ciências Humanas e Sociais Aplicadas is the property of Revista Cesumar - Ciencias Humanas e Sociais Aplicadas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ingenius, Revista Ciencia y Tecnología is the property of Universidad Politecnica Salesiana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Two economic activities have been integrated in southern Brazil: olive cultivation and sheep farming. The favorable edaphoclimatic conditions in the southern region for cultivating olive trees and cultural preferences for the consumption of sheep meat make this integration a valuable strategy. Considering that every activity causes environmental impact and the exploitation of natural resources, new systems that promote sustainable development and the efficient use of these resources become necessary. This paper presents the first study of the carbon footprint of the life cycle of integrating of sheep and olive farming, with the objective to build an inventory based on primary data collected on olive and sheep farms in Brazil, determine the carbon footprint of the conventional and integrated system and estimate the potential for mitigating GHG emissions. The evaluation was performed using the life cycle assessment (LCA) methodology. The study focuses on the detailed analysis of the processes and activities that are responsible for GHG emissions, including enteric methane emissions, methane emissions from manure management, emissions from nitrogen fertilizer use and limestone application and energy consumption. For this, two major scenarios were considered, the first centered around on the traditional olive cultivation and sheep farming systems individually, and the second involved their synergistic integration. The findings indicate that the conventional system is associated with a global warming impact of 6.8 kg CO 2 eq per liter olive oil and kg live weight. In contrast, the integrated system demonstrates a significant mitigation potential of 27.7%, resulting in a reduced global warming impact of 4.92 kg CO 2 eq. This advantage is a consequence of the synergy between the systems, as they now occupy the same area, which allows the sharing of agricultural activities and agrochemical inputs, in addition to optimizing nutrient recycling and complementing each other. Additionally, the results of a sensitivity analysis showed that enteric methane from sheep and the application of limestone to the soil are the most influential parameters on the carbon footprint, indicating that they are key parameters for the development of GHG mitigation strategies, some of which were discussed in the article. • First life cycle assessment of integration between olive and sheep farming in Brazil. • The inventory was constructed with primary data collected in situ. • The study assesses the carbon footprint of the olive and sheep farming system. • The results show environmental advantages of the integration of olive and sheep farming systems. [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]

Copyright of Exacta is the property of Exacta - Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Tourism serves as a crucial means of funding national development and ensuring the sustainability of local livelihoods in growing countries such as Brazil. Nevertheless, the accelerated growth of tourism in various nations might lead to significant environmental consequences due to heightened energy consumption. This surge in energy usage contributes to the exacerbation of global warming through the amplified release of carbon dioxide (CO2). In light of the increasingly evident impacts of climate change on the natural environment, a multitude of endeavors have been undertaken with the aim of attaining ecological sustainability. The objective of this study is to examine the dynamic effects of economic growth, energy consumption, and tourism on carbon emissions in Brazil by analyzing time series data spanning from 1990 to 2019. The stationarity of data was assessed through the application of unit root tests, while an autoregressive distributed lag (ARDL) approach was employed to analyze the relationship between the components, accounting for both the long-term and short-term dynamics. The empirical results indicate that a 1% rise in economic growth, energy consumption, and tourist arrivals leads to environmental deterioration by causing a respective increase in CO2 emissions of 1.37%, 1.06%, and 0.57% in the near term, and 0.72%, 0.62%, and 0.16% in the long term. This article presents policy ideas aimed at achieving carbon neutrality in Brazil by increasing the utilization of renewable energy sources, while simultaneously fostering sustainable tourism as a means to enhance the country's economy. Highlights •This study investigated the tourism-economy-energy-environment nexus in Brazil. •The econometric analysis revealed that tourism, energy use, and economic growth increase CO2 emissions. •This article offers policy suggestions to achieve sustainable tourism and carbon neutrality. [ABSTRACT FROM AUTHOR]

Summary: Fraud in electrical energy consumption represents a critical economic burden for utility companies around the world. Despite systematic efforts to mitigate electricity theft, this practice persists mostly in developing countries where companies rely on traditional detection methods. In Brazil it is estimated that around 7% of the total electrical energy available for consumption in 2016 was lost due to frauds. Here we describe an efficient and scalable system to predict fraudulent behavior and guide in loco inspections. We compared the performances of several machine learning algorithms using consumption and inspection data provided by CPFL Energia. We show that proper feature engineering and boosted classification trees trained with XGBoost are able to extract patterns related to fraud occurrence and to achieve predictive power of practical consequences. Moreover, we demonstrate how Shapley additive explanation (SHAP) values can be employed to build user friendly explanations. Together, the proposed model and its explainers contribute not only to reveal potentially fraudulent behavior but also to understand root causes, what can be used to devise robust mitigation strategies. [ABSTRACT FROM AUTHOR]

Study region: The Três Marias 396 MW power plant located on the São Francisco River in Brazil. Study focus: Hydropower generation is directly and indirectly affected by climate change. It is also a relevant source of energy for electricity generation in many countries. Thus, methodologies need to be developed to assess the impacts of future climate scenarios. This is essential for effective planning in the energy sector. Energy generation at the Três Marias power plant was estimated using the water balance of the reservoir and the future stream flow projections to the power plant, for three analysis periods: FUT1 (2011–2040); FUT2 (2041–2070); and FUT3 (2071–2100). The MGB-IPH hydrological model was used to assimilate precipitation and other climatic variables from the regional Eta climatic model, via global models HadGEM2-ES and MIROC5 for scenarios RCP4.5 and RCP8.5. New hydrological insights for the region: The results show considerable reductions in stream flows and consequently, energy generation simulations for the hydropower plant were also reduced. The average power variations for the Eta-MIROC5 model were the mildest, around 7% and 20%, while minimum variations for the Eta-HadGEM2-ES model were approximately 35%, and almost 65% in the worst-case scenario. These results reinforce the urgent need to consider climate change in strategic Brazilian energy planning. [ABSTRACT FROM AUTHOR]

Despite the concern about climate change and the associated negative impacts, fossil fuels continue to prevail in the global energy consumption. This paper aimed to propose the first model that relates CO2 emissions of Sao Paulo, the main urban center emitter in Brazil, with gross national product and energy consumption. Thus, we investigated the accuracy of three different methods: multivariate linear regression, elastic-net regression, and multilayer perceptron artificial neural networks. Comparing the results, we clearly demonstrated the superiority of artificial neural networks when compared with the other models. They presented better results of mean absolute percentage error (MAPE = 0.76%) and the highest possible coefficient of determination (R2 = 1.00). This investigation provides an innovative integrated climate-economic approach for the accurate prediction of carbon emissions. Therefore, it can be considered as a potential valuable decision-support tool for policymakers to design and implement effective environmental policies. [ABSTRACT FROM AUTHOR]

Abstract This paper is a multi-case study of three oil and gas projects in Brazil that investigates the tacit knowledge on how to best manage energy use during the construction phase. Twenty-two in-depth interviews form the primary evidence of the case studies. The methodology incorporates network analysis of concepts that influence energy use to formalize the case studies and collect additional knowledge. The framework comprises thirteen construction activities and twenty-one systems and factors related to design, resources and site characteristics, specific to the construction domain. This set of concepts can influence the energy consumption during the construction phase. Although these concepts are present in nearly every project, their dynamics and their inter-relations with project-specific systems change, depending on the context of the project. The proposed method, which employs network analysis, help identify their interrelationships and relative importance of these concepts. In addition to the opportunities and lessons learned that can guide future energy assessments and improve energy use in construction projects, the results show how promising network analytics is to obtain knowledge usually difficult to perceive in traditional knowledge processes. Besides, this work highlights the importance of supporting collaboration between project team members to study and decide on the plans to manage/reduce energy consumption during the construction phase in oil and gas facilities. While the energy savings are smaller than the upstream and operation phases, it has received much less attention. It is also a phase with much more subjective and contextualized knowledge – making the use of case-based analyses more suitable. Highlights • Supports collaboration in studying and planning energy use during the construction phase of O&G projects. • Three case studies are conducted supported by in-depth interviews. • Network analysis is used to represent construction activities, factors and systems. • The approach represents a meaningful way to formalize the knowledge in the cases. • Can help formalize the knowledge contained in a text case. [ABSTRACT FROM AUTHOR]

An emergent strategy to target sustainability involves an understanding of the water-energy interconnections. It takes water to produce energy, and it takes energy to source, treat, and distribute water. Sanitation and energy distribution are the world's pre-eminent development challenges. They are a magnifier of poverty, ill-health and mortality, and gender inequality. The word 'nexus' means the understanding of these interdependencies, tensions, and trade-offs. This paper investigates water-energy interconnections through critical analysis. We applied a bottom-up approach to describe Sao Paulo state's river basins, in Southeast Brazil, from the household to the regional scale. Initially, water availability, energy consumption and wastewater treatment data are inferred using per capita data. The subsequent data analysis then considered the positive and negative linkages among the basins. Local and state levels of dependency are also assessed, considering environmental and socioeconomic impacts. The significance of this paper lies in understanding these interconnections and their interdependence within the local context and individuals' behaviour. The results allow a comprehensive analysis of the water-energy Nexus across Sao Paulo state. The critical analysis also shows how the primary drivers contribute to urbanisation levels, population growth, and industrial activities. • Regional WE Nexus analysis is undertaken for the most industrialised state of Brazil. • The increase in wastewater treatment highlights the sustainability path. • Wastewater treatment growth rates are higher than population and GDP rates. • It develops a unique database for future studies using the Nexus approach. • Population growth, GDP, and industrial intensity are the main drivers in the WE Nexus. [ABSTRACT FROM AUTHOR]

Energy auctions are commonly used to contract energy projects and are extensively studied from the regulator's perspective. However, analyzing auctions from the stakeholders' perspective is critical to determine the impact of regulatory details on the bidder's revenues. In this study, we analyze a public energy auction in Roraima, a Brazilian state with a significant energy deficit and no grid connection, where many projects were successful in the non-intermittent Power Product category, typically unfavorable for biomass. Using Linear Programming to maximize bidders' revenues, we examine the regulatory formulas that contributed to the success of these projects and compare the optimization results to actual revenues. Our analysis shows that certain regulatory elements can benefit stakeholders by allowing them to make unconventional project design decisions. In addition, we identify a possible loophole in the formula that can have the opposite effect of the regulator's intent in the renewable Power Product category. Our findings can help bidders increase profits through optimization and regulators to change formulas if objectives are not met. This study brings the often-overlooked perspective of stakeholders to energy auctions, adding to the literature on this topic. [ABSTRACT FROM AUTHOR]

This study discusses the choice of dehumidification systems for high-moisture indoor environments, such as indoor swimming pools, supported by an eco-energetic performance comparison. Initially, the causes of the high relative humidity and condensation in these spaces are reported, as well as the available dehumidification technologies. Two different solutions are described: desiccant wheel dehumidification and re-cooling. The energy demand required by a refrigeration system is lower than the desiccant wheel; however, the former system requires less maintenance and does not require refrigerant fluid. An eco-energetic comparison is performed between the two systems in two countries with different energy matrices (Brazil and USA). In Brazil, the desiccant wheel is the best choice for the past 10 years, with a predicted 351,520 kgCO2 of CO2 emissions, which is 38% lower than the refrigeration system. In the USA, the best option is the refrigeration system (1,463,350 kgCO2), a 12% more efficient option than desiccant wheels. This model can be considered for energy and CO2 emissions assessment, predicting which system has better energy efficiency and lower environmental impact, depending on the refrigerant type, location and environmental conditions. [ABSTRACT FROM AUTHOR]

In Northeast Brazil, the use of biomass for energy generation is settled on traditional productive arrangements, such as a sugarcane production system in the humid Atlantic coastal area and firewood extraction from native tropical dry forests in the west. In parallel, substantial amounts of other biomass sources, such as residues from agricultural or urban processes, are still little used or wholly wasted, fudging the opportunity to generate new value chains based on these biomass sources. We hypothesize that using these non-traditional biomass sources to produce biofuels would significantly increase the regional bioenergy supply. In this context, this article discusses the potential for the production and use of biofuels and bioenergy in Northeast Brazil and its effects on regional development, which may be useful for both private actors and policymakers in the energy sector. The use of biomass sources for energy in the region is significant, reaching approximately 8.8 million tons of oil equivalent (toe) per year, emphasizing the already consolidated production of sugarcane and its derivatives. The use of all biomass resources in the Northeast region could supply around 4% of the Brazilian national electrical energy demand, with an environmental footprint of 0.055 tCO2eq per toe, which would contribute to reducing emissions from the Brazilian energy matrix generation. Regarding the spatial distribution of biomass sources, sugarcane prevails on the coast, firewood and livestock manure in the dryland area towards the west, and municipal solid waste is distributed throughout the region within urban areas. Different from what we expected, the potential energy recovery from municipal waste and animal manure would increase by only 17% the current bioenergy supply. In the future, since the majority of the region presents a semi-arid climate with limited rainfall, to increase the use of biomass as an energy source, there is a need to increase the supply of biomass sources with high efficiency in water use and good yields in drylands. For this, the cultivation and use of cacti and agave, for example, could contribute to making biorefineries viable in the region. Above all, public policies for harnessing bioenergy in NE Brazil must seek opportunities associated with the carbon/decarbonization economy, with studies being needed to assess the technical, economic, social, and environmental viability of future productive arrangements. [ABSTRACT FROM AUTHOR]

This study aims to determine the factors that affect the forest products footprint (FPF) in Brazil during the period 1965–2018 by proposing a new cointegration test which augments the Engle-Granger cointegration test with a Fourier function (Fourier Engle-Granger) and allows multiple structural breaks in the long-run relationship. Since the results of the unit root tests show that all variables are nonstationary, we applied the Fourier Engle-Granger cointegration test and revealed that there was a long-term relationship between the forest products' footprint, energy consumption, gross domestic product, and trade openness. Although energy consumption was found to have a decreasing effect on FPF, the remaining variables were found to have a healing effect on FPF. Policymakers in Brazil should consider shifting energy consumption to clean energy sources and sustain international trade and economic growth in the current form to consider the FPF. [ABSTRACT FROM AUTHOR]

This paper focuses on an analysis of the energy mix profile and energy efficiency of the Brazilian dairy industry. It investigates dairies’ energy mix and energy efficiency and identifies some actions for a cleaner energy mix. Primary data from 37 dairy cheese-making establishments distributed among the Brazilian regions were obtained from online surveys. The results indicate that woodfuel plays a critical role, being the most used fuel in thermal energy generation, while diesel is dominant in electric generation. It also emphasizes that only 51% of the dairy establishments utilize electric energy generators. Other alternative biomass sources are still incipient in the sector, restricted to just 9.5% of the cases for thermal energy generation and no cases for electricity. Regarding the energy efficiency analysis, the results suggest dairies are more scale efficient than pure technical efficient. However, the dairies present a low energy efficiency level. There is no evidence that inefficiencies are differently distributed according to their size. These findings are important for government agencies, industry associations, scientists, universities and research institutes. High inefficiencies, regarding the use of electricity and thermal energy, are a key issue in sustainable bioenergy production. [ABSTRACT FROM AUTHOR]

Recognizing the need to increase energy efficiency across various sectors of the economy, the Brazilian government through the national energy efficiency plan (adopted in 2011) seeks to avoid 30 million tons of CO2 emissions through a reduction in electricity consumption of about 10% by 2030. Notwithstanding, we believe that a complete realization of such initiative will be dependent on the level of substitutability between different production factors and fuel types. Using the translog production function method, this paper, first provides insight on the economic impact of both factor and fuel inputs in Brazil. Most importantly, we examine the possibility of substitution among capital, labor, petroleum, and electricity. The ridge regression technique was used to estimate the parameters after our data depicted the existence of multicollinearity. Our results show that capital and labor are positively linked to output; however, petroleum and electricity contribute negatively to economic output in Brazil of which corruption is a plausible reason. Again, all variable inputs are substitutes with their relative technological progress depicting features of convergence. This implies that Brazil can achieve a cleaner energy system without much challenges due to the possibility of switching from greenhouse gas (GHG) emitting petroleum to a cleaner energy electricity. Our findings also highlight the importance of policies that advance merger of enterprises, and renewable energy use. [ABSTRACT FROM AUTHOR]

Improvements in modelling energy systems of populous emerging economies are highly decisive for a successful global energy transition. The models used–increasingly open source–still need more appropriate open data. As an illustrative example, we take the Brazilian energy system, which has great potential for renewable energy resources but still relies heavily on fossil fuels. We provide a comprehensive open dataset for scenario analyses, which can be directly used with the popular open energy system model PyPSA and other modelling frameworks. It includes three categories: (1) time series data of variable renewable potentials, electricity load profiles, inflows for the hydropower plants, and cross-border electricity exchanges; (2) geospatial data on the administrative division of the Brazilian federal states; (3) tabular data, which contains power plant data with installed and planned generation capacities, aggregated grid network topology, biomass thermal plant potential, as well as scenarios of energy demand. Our dataset could enable further global or country-specific energy system studies based on open data relevant to decarbonizing Brazil's energy system. [ABSTRACT FROM AUTHOR]

• An overall panorama of the school buildings in Brazil was presented. • Energy billed data and survey evidence were used to build a statistical stock model. • The Weibull distribution was the most adequate to represent the continuous variables. • kWh/student·year was more suitable than kWh/m2·year to model Brazilian school buildings stock. • Thermal performance is an issue to be greatly improved in schools in Brazil. Understanding the actual conditions in school buildings regarding energy usage and environmental satisfaction gives way to the development of consistent building stock modelling. In the Brazilian context, a deep-rooted inefficient structure of energy management implies a lack of mapping the actual conditions of the public schools. Therefore, this paper aimed to assess the actual energy performance of school buildings in Brazil. This paper innovates by integrating questionnaire responses and billed energy data to allow the construction of an evidence-based stock model through a statistical approach, which was never performed for the Brazilian building stock. Moreover, the association of energy use intensity (EUI) with the core aspects of building characteristics, occupancy, environmental satisfaction and necessary improvements mapped the relevance of such aspects in energy usage patterns. Additionally, a discussion of the EUI indicators was addressed. Results showed an unprecedented broad panorama of the school building stock in Brazil and its main features. In terms of statistical analysis, the Weibull distribution was appropriate for representing the continuous variables of the stock. The EUI as a function of the number of students was more suitable than the floor-plan area to achieve a reliable energy performance analysis. Several tests were performed to assess if the energy management, environmental satisfaction and maintenance practices impacted the EUI or not. Finally, the main conclusion was that the stock model obtained was simple and fit the energy management structure in the Brazilian scenario. [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]

This paper explores the environmental impacts of a refrigerator recycling system in Brazil and quantifies its ecological advantages over primary resource production through a Life Cycle Assessment based on ISO 14040. The Life Cycle Assessment (LCA) accounts for savings of 720 kg CO 2 -eq per recycled refrigerator on average, thus demonstrating that an environmentally sound recycling process holds substantial emission reduction potential. In addition, the application of the recycling process in conjunction with collection and reverse logistics of refrigerators in a recycling system can reduce energy demand in Brazil by an average of 1.5 GJ per recycled unit. As a result, refrigerator recycling systems qualify as a valid and scalable energy efficiency measure in accordance with the Brazilian national framework for the evaluation of energy efficiency projects (PROPEE). The energy economics for projects based on recycling systems are shown for the 30 largest energy distributors in Brazil. Available budgets, calculated with diagnostics undertaken in conformity with the International Performance Measurement and Verification Protocol (IPMVP) for a threshold value (cost-benefit ratio = 0.8), clearly indicate the viability and competitiveness of these recycling systems as project opportunities for energy conservation under the national energy regulation agency ANEEL's energy efficiency program (PEE). [ABSTRACT FROM AUTHOR]

New rules and laws for the electricity sector in Brazil aim to produce severe reductions to the cost of electricity in order to reduce the so-called ‘Brazil Cost’. Taking into account those new rules and laws all electricity companies have an obligation to improve their processes. Among them the following actions are contemplated: intelligent use of resources; expansion of synergies; increase of the efficiency of internal procedures and processes; massive introduction of technological innovations; reduction of the amount of compensation paid in lawsuits; reduction of technical losses or losses by theft in the case of distribution of the generated energy. If the companies do not make plans and act quickly they will be bound to cause their shareholders very high losses of capital, leading to an expressive decrease of interest to invest in the sector. The absence of those plans and subsequent actions can also lead to investments in generation and distribution being returned to the state, which contributes to an increasing degree of state interference in the economy. In this paper the ordered groups of reading power consumption of clients that maximize the profits of a power plant are determined. The groups were determined by cluster analysis and their reading consumption groups ordered by making use of the Choquet integral. [ABSTRACT FROM AUTHOR]

The Paraná Hydrographic Region (PHR) is one of the main hydrographic basins in Brazil, standing out for its energy generation and consumption, among other ecosystem services. Thus, it is important to identify hydrological drought events and the driest periods inside of these droughts to understand the anomalous atmospheric circulation patterns associated with them (a multiscale study). This study used the standardized precipitation index (SPI) for the 12-month scale to identify hydrological drought episodes in the PHR from 1979 to 2021. For these episodes, the severity, duration, intensity, and peak were obtained, and the SPI-6 was applied to the longest and most severe drought to identify periods with dry conditions during the wet season. Anomalous atmospheric and oceanic patterns associated with such episodes were also analyzed. The results reveal that the longest and most severe hydrological drought on the PHR started in 2016. The end of this episode was not identified by the end of the analyzed period. The SPI-6 revealed three rainy seasons during this drought event marked by anomalous dry conditions: 2016/2017, 2019/2020, and 2020/2021. In general, the circulation patterns identified differ in each period, for example, in 2016/2017, an El Niño event was dominant, in 2019/2020, the tropical Pacific Ocean showed neutral conditions, and in 2020/2021, a La Niña episode was registered. Despite that, in the three periods, the anomalous atmospheric patterns contributed to the weakening of the low-level jet east of the Andes and, consequently, to the decreasing of the moisture transport to the PHR, then leading to dry conditions over the basin. [ABSTRACT FROM AUTHOR]

Energy management has been considered in the global agenda as a way to improve energy performance and greenhouse gas reduction in organizations. Industries account for a significant part of energy use worldwide and present opportunities for energy efficiency improvements. Within the industry, energy management is a complex task, regarding scenarios with variables related to the following perspectives: economics, contingency, technological change and behavioural. This paper aims at analyzing the influencing factors on energy management in industries from these perspectives. A survey with 40 variables was carried out with middle managers from different industrial sectors in Brazil. The variables were divided into three groups: drivers for investments in energy efficiency; organizational processes and actions in energy management; involvement of middle managers. Initially, an exploratory factor analysis technique was employed aiming at specifying the main factors influencing energy management. In the sequence , a confirmatory factor analysis was used to associate the variables to the main factors as well as to know how the factors relate to each other. The study showed a positive correlation among all the factors identified. Statistical tests suggested that the factors could not be explained separately. Hypotheses tests were applied to verify the influence of the factors among the groups surveyed. The final model comprised eight factors into the three groups: organizational (strategic , operational), involvement (motivation, support), drivers (production, economics , competitiveness, environment). The results and the main implications of the study are discussed in the paper. • The main factors on energy management presented a positive correlation among them. • Middle managers' involvement influenced strategy and operation on energy management. • Middle managers' involvement depended on the support and motivation from superiors. • Operational factor on energy management influenced drivers for energy efficiency. • Production process was a driver for energy efficiency influencing energy management. [ABSTRACT FROM AUTHOR]

• A top-down analysis of the non-residential building stock in Brazil is proposed. • The share of each building typology in the country energy consumption was assessed. • A statistical analysis showed variation of EUI according to type of building and region. • Reference values for the commercial building stock in Brazil is provided. This paper provides a pioneering, top-down analysis of the non-residential building stock in Brazil. A country-wide dataset was used, comprising 10,000 buildings divided into 12 typologies. Key indicators include floor area, energy use intensity, and operation patterns. In addition, predominant wall constructions, lighting systems, equipment, water heating, and HVAC systems for each typology were identified, including average density power for the systems. Data from the Brazilian Energy Balance report was correlated with the sample of buildings to determine the proportion of each building typology in the total energy consumption of the country, considering different energy sources. This study provides an innovative and up-to-date status of the characteristics of non-residential buildings in Brazil. A complementary statistical analysis addressed the correlation between energy use intensity and the building characteristics including an ANOVA test and a regression analysis in order to investigate the influence of the energy usage indicators (Lighting Power Density, Equipment Power Density, Cooling capacity) on the energy use intensity of each building typology in Brazil. This study is intended to serve as a reference for building characteristics and building energy performance in Brazil, and hence support diverse research regarding country-level building stock modeling, energy benchmarking, climate change impacts, and energy-efficiency related studies. [ABSTRACT FROM AUTHOR]

This study presents an analysis of the potential uses of BIM for managing the maintenance and refurbishment of existing housing assets to propose thermal comfort and energy efficiency guidelines for future social housing projects in Brazil. To do so, a case study analysis of a residential development with social–environmental certification in the city of Garanhuns, Pernambuco, Brazil was performed, and a literature review on the use of BIM for residential unit maintenance was conducted. The standard house in the residential development was found to be noncompliant with the Brazilian standard for ventilation openings (NBR 15.220). Therefore, three alternative layouts were created and analyzed to meet the requirements of the standard as well as the needs of the residents. The authors recommend that socio-environmental certifiers use BIM models so that energy performance and other simulations can be carried out. The study also proposes guidelines for BIM implementation in future government housing projects. These guidelines were grouped into five categories: BIM encouragement, energy efficiency, maintenance management, user requirement management, and continuous improvement. The significance of this study is in providing a path for the gradual implementation of BIM for maintenance and post-occupancy management in the Brazilian housing program. [ABSTRACT FROM AUTHOR]

The rate of technological progress is an important metric used for predicting the energy consumption and greenhouse gas emissions of future light-duty fleets. A trade-off between efficiency and performance is essential due to its implications on fuel consumption and efficiency improvement. These values are not directly available in the Brazilian fleet. Hence, this is the main gap in knowledge that has to be overcome. Tendencies in all relevant parameters were also unknown, and we have traced them as well, established on several publications data and models. We estimate the three indicators mentioned above for the Brazilian fleet from 1990 to 2020. Although the rate of technological progress was lower in Brazil than that in developed countries, it has increased from 0.39% to 0.61% to 1.7% to 1.9% in subsequent decades. Performance improvements offset approximately 31% to 39% of these efficiency gains. Moreover, the vehicle market is shifting toward larger vehicles, thus offsetting some efficiency improvements. We predict the fleet fuel efficiency for the years 2030 and 2035 using the above-mentioned factors. The predicted values for efficiency can vary by a factor of two. Thus, trade-off policies play a vital role in steering toward the desired goals of reducing the transportation sector's impact on the environment. [ABSTRACT FROM AUTHOR]

This paper estimates the Genuine Progress Indicator (GPI) for Brazil from 1970 to 2010 as an alternative indicator to the Gross Domestic Product (GDP). After a growing disparity between these two indicators in the 1980s, when Brazil's per capita GPI featured a 35% decline, there was a relative catch-up in per capita GPI, but not one sufficiently strong enough to reduce the historical GPI–GDP gap. The recent trend of rapidly increasing environmental and social costs, along with the decline in unpaid labour and infrastructure services, poses concerns about the sustainability of an increasing GPI for Brazil into the future. Policies aimed at reducing environmental costs are necessary if Brazil is to enjoy a sustainable pattern of non-declining economic welfare. Brazil must pursue a higher rate of productivity in material and energy consumption in order to keep environmental pressures to a minimum level. [ABSTRACT FROM AUTHOR]

The objective of this paper was to compare primary energy consumption and energy efficiency during the operation phase of different types and combinations of water heating systems in single-family dwellings. Systems with an electric shower, liquefied petroleum gas heater, and solar heater with electric backup were analysed. The analysis was performed by means of computer simulation using EnergyPlus. Three Brazilian cities with different climates were assessed, i.e., Curitiba, Brasília and Belém. The systems were compared in terms of final energy and primary energy consumption. Results showed that systems with an electric shower, which have a lower water flow rate, led to lower primary energy consumption. The solar heating system combined with an electric shower was the option with the lowest energy consumption, and the solar heating system with a heating element in the storage tank was the option that consumed more energy. The systems were sized according to the requirements of the Brazilian energy efficiency labelling for residential buildings, and the efficiency level was compared to the results of primary energy consumption. The electric shower was found to be the third lowest energy consumer, but it was ranked the least energy efficient by Brazilian labelling, while systems with high energy consumption, such as gas heaters and solar heaters with a heating element in the storage tank, were ranked the most energy efficient. Therefore, a review of the requirements and methodology of the Brazilian energy efficiency labelling for residential buildings is recommended in order to encourage the use of truly efficient systems. Public policies that encourage solar heating systems should establish requirements regarding the configuration and sizing both the solar heating system and the backup system. [ABSTRACT FROM AUTHOR]

The growth of the economy in urban centers is invariably accompanied by an increase in human activities and environmental interference, mainly related to waste generation. Due to the nature of these activities, large volumes of varied waste are generated daily without the establishment of compatible and adequate collection, logistics, and final disposal systems, bringing relevant impacts to society on health, the environment, and the economy itself. In Brazil, in 2019 alone, almost 30 million tons of MSW were not collected and the total collected, of approximately 44 million tons, went to landfills, with little or no energy use. There is therefore a great opportunity for energy use using this source, aiming not only to adapt to current legislation, but also to reduce GHG emissions, reduce the population's exposure to sanitary landfills and open air, and use the energy contained in these wastes. The purpose of this study is to analyze the main conditions and challenges of current technologies for harnessing the energy potential of biomass from urban solid waste (USW) to enable the insertion of mini thermal plants connected to distributed generation. [ABSTRACT FROM AUTHOR]

Summary: Considering Brazil an important player in the global market for the electricity production from solar sources and the recent investments in large power plants through public policies, this work evaluated a very large‐scale commercial photovoltaic power plant (VLS‐PVPP) performing an attributional life cycle assessment (LCA) in accordance with ISO 14040/44 standards. The comparative results obtained, for 18 impact categories, show that the use of global data tends to overestimate the impacts of energy production in the VLS‐PVPP implemented in Brazil, by at least double. When establishing scenarios for different regions of the Brazilian territory, the energy performance and emissions indicators used varied around 17% due to the high sensitivity of the solarimetric radiation index in the modeling. The carbon footprint ranged between 38.3 and 44.8 kgCO2eq/kWh, and the energy payback time (EPBT) ranged between 4.5 and 5.3 years. The fossil energy replacement ratio (FER) indicator was calculated to quantify the power plant sustainability, which, in the best scenario, showed that the system replenishes, with clean energy, 7.7 times the fossil energy used in its construction. The sensitivity study associated with the uncertainty analysis for the manufacturing location of photovoltaic modules showed little influence (about 1%) on these indicators, showing that the decision to import or manufacture PV modules does not involve an environmental bias, overturning this hypothesis. Furthermore, the sensitivity study of the photovoltaic modules showed that the multicrystalline silicon technology is still the best choice compared to the monocrystalline one, since the latter increased the environmental cost of the evaluated indicators by 20%. [ABSTRACT FROM AUTHOR]

The high consumption of electricity in Palmas, Brazil is a direct consequence of the high temperatures identified throughout the year. Therefore, it is necessary to search for sustainable technologies that contribute to comfort through passive cooling, thus reducing the energy consumption. This work presents the results of an experimental campaign of 11 months, in which the effects of shading devices, the use of a low-emissivity reflective film, the implementation of natural ventilation and the application of reflective painting are evaluated, when applied individually and combined. The results show that when applied individually, natural cross ventilation was the most effective at night, while reflective painting showed better performance during the day. Regarding the combinations of techniques, the best combination occurred when reflective painting was used together with natural ventilation, and the result was a relevant improvement in the performance, ensuring high temperature reductions when compared to the control. [ABSTRACT FROM AUTHOR]

• An innovative framework for energy benchmarking of buildings is proposed. • Entropy and cluster analysis reduced uncertainty in setting parameters of archetypes. • The machine learning technique used as a benchmarking tool showed high performance. • The benchmarking applied in actual buildings showed a high inefficiency ratio. Energy benchmarking of buildings has an important role in improving energy performance by establishing a reference for the energy efficiency of the building stock. The simulation of archetypes followed by a generalisation model has been widely used to obtain benchmarks. However, even though archetypes summarise the main features of the building stock, the uncertainties must be accounted for in the modelling process. Moreover, testing the response of the benchmarking model using the actual building stock data supports the reliability of the method. This paper aims to propose an innovative framework to reduce the uncertainty of archetypes for benchmarking buildings. A standard framework for data compiling is proposed and an assessment of the uncertainty of variables using entropy and cluster analysis allowed to obtain representative archetypes. An Artificial Neural Network (ANN) was used as a predictive tool, and it was applied to benchmark a sample of actual buildings. Also, the simulation outcomes were used to determine energy end-uses according to the climatic zones. The framework proposition is presented alongside with a practical application. The result is an unprecedented benchmarking model: the archetype considers more variation in parameters of the building stock with higher uncertainties. Additionally, the modelling process showed to be robust for combining different datasets, and the ANN achieved high-performance metrics. Conclusion indicates the potential of using the framework for other typologies. Moreover, the framework demonstration is used for a school stock in Brazil, showing a trend to the inefficiency while a specific case study was explored, showing the potential of the method to find faults in the building energy use. [ABSTRACT FROM AUTHOR]

This paper tackles the short-term hydro-power unit commitment problem in a multi-reservoir system — a cascade-based operation scenario. For this, we propose a new mathematical modeling in which the goal is to maximize the total energy production of the hydro-power plant in a sub-daily operation, and, simultaneously, to maximize the total water content (volume) of reservoirs. For solving the problem, we discuss the Multi-objective Evolutionary Swarm Hybridization (MESH) algorithm, a recently proposed multi-objective swarm intelligence-based optimization method which has obtained very competitive results when compared to existing evolutionary algorithms in specific applications. The MESH approach has been applied to find the optimal water discharge and the power produced at the maximum reservoir volume for all possible combinations of turbines in a hydro-power plant. The performance of MESH has been compared with that of well-known evolutionary approaches such as NSGA-II, NSGA-III, SPEA2, and MOEA/D in a realistic problem considering data from a hydro-power energy system with two cascaded hydro-power plants in Brazil. Results indicate that MESH showed a superior performance than alternative multi-objective approaches in terms of efficiency and accuracy, providing a profit of $412,500 per month in a projection analysis carried out. • An efficient Multi-objective Evolutionary Swarm Hybrid algorithm is proposed. • Development of a nonlinear model to operational control of Hydro-power plants. • Hydro-power plant data regression obtains the maximum efficiency of the power units. • Efficiency energy goals achieved an increasing the profit in the energy production. [ABSTRACT FROM AUTHOR]