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The emerging energy transition is particularly described as a move towards a cleaner, lower-carbon system. In the context of the global shift towards sustainable energy sources, this paper reviews the potential and roadmap for hydrogen energy as a crucial component of the clean energy landscape. The primary objective is to present a comprehensive literature overview, illuminating key themes, trends, and research gaps in the scientific discourse concerning hydrogen production and energy policy. This review focuses particularly on specified geographic contexts, with an emphasis on understanding the unique energy policies related to renewable energy in Brazil, Austria, and Germany. Given their distinct social systems and developmental stages, this paper aims to delineate the nuanced approaches these countries adopt in their pursuit of renewable energy and the integration of hydrogen within their energy frameworks. Brazil exhibits vast renewable energy potential, particularly in wind and solar energy sectors, positioning itself for substantial growth in the coming years. Germany showcases a regulatory framework that promotes innovation and technological expansion, reflecting its highly developed social system and commitment to transitioning away from fossil fuels. Austria demonstrates dedication to decarbonization, particularly through the exploration of biomethane for residential heating and cooling. [ABSTRACT FROM AUTHOR]

Purpose: Energy consumption and renewable energy sources are included in the goals for the 2030 Sustainable Development Goal 7 (SDG7) agenda, and target buildings are the biggest electricity consumers. In turn, Netzero energy buildings (NZEB) contribute to achieve SDG7 goals. This paper aims to identify which Brazilian higher education institutions (HEIs) practices contribute to developing the NZEB concept. Design/methodology/approach: Case studies were selected to identify which implanted practices applied by HEIs in Brazil, listed in the UI GreenMetric 2020 Ranking, are related to the NZEB concept. The implemented sustainable practices were also analyzed to evaluate the connections and impact between universities and the local community. Findings: Results show the lighting and air conditioning retrofit were among the most common practices related to energy efficiency to reduce consumption. For renewable energy generation, photovoltaic solar energy is the most common practice used by HEIs. Research limitations/implications: Only Brazilian HEIs listed in the UI Green Metric Ranking were analyzed. No standard regulation or formal reports support the wide dissemination of the strategies adopted by HEIs in Brazil. Practical implications: The strategies adopted by HEIs related to Netzero buildings can reduce emissions, optimize operating costs and improve building comfort conditions, which connect all SDGs. Social implications: HEIs can promote awareness related to energy use and clean energy generation within the local community. Originality/value: This paper presents the most common strategies adopted by Brazilian HEIs. However, limitations related to lack of strategies, data transparency and specific Netzero energy regulation were also found. These issues can hinder other HEIs to adopt similar strategies and contribute to the promotion of SDG7 in Brazil. [ABSTRACT FROM AUTHOR]

The use of renewable energy, notably solar and wind energy, has grown exponentially in Brazil. Consumers can generate their energy using renewable sources, whether interconnected to the distribution system (on-grid) or not (off-grid). In this paper, a fuzzy method is developed for the recommendation of solar and wind sources, for any location in the Brazilian territory. In many aspects, it can be viewed as a representation of human decision-making using sets and inference rules and also can be with vagueness and uncertainty, being very useful to idealize recommendation systems. Georeferenced and historical data were obtained from 2003 to 2019 on solar irradiation and wind speed, and electricity consumption until 2021. With the energy generation data from photovoltaic panels and wind turbines, this method allows us to propose installed areas by each technology and obtain the membership of fuzzy recommendation between solar, wind, both solar and wind, unfeasible or hybrid. In addition, a long short-term memory neural network and the seasonal autoregressive integrated moving average model were used to predict consumption for more than 30 months ahead, allowing the recalculation of fuzzy memberships and updating the installation area by respective technologies. As a result, the recommendation is given as the installed area (m2) of each technology per km2 of consumer units, as a function of the regional consumption density (MWh/km2). It can be concluded that it is possible to plan the viability of the type of renewable energy used, according to regional characteristics for smaller consumer units (farms, cooperatives, industries, consortiums), given the diversity of these factors in the huge Brazilian territory. This methodology is in line with the Brazilian Normative Resolution that authorizes the generation of energy by landowners. [ABSTRACT FROM AUTHOR]

The present paper explored the effect of renewable energy, financial development, and technological innovation on the ecological footprint in Brazil using a yearly dataset stretching between 1990 and 2018. The research leverage dynamic autoregressive distributed lag, Bayern and Hank cointegration, and frequency domain causality to explore these interrelationships. The ARDL bounds test outcome confirms a long-run connection between ecological footprint and its drivers. Besides, we employed the Bayern and Hank cointegration, and the outcome resonated with the ARDL bounds test result. Moreover, the dynamic ARDL outcomes disclosed that economic progress worsens the ecosystem whilst renewable energy, trade globalization, and technological innovation lessen the ecological footprint. In addition, no significant interrelationship was found between financial development and ecological footprint. Moreover, with the exemption of financial development, all the exogenous variables can forecast the ecological footprint in Brazil. The study proposes that policymakers in Brazil should undertake investments in research and development in order to achieve technological innovation. Furthermore, since technological innovation has been shown to contribute significantly to lowering the ecological footprint, it is possible to assume that enhancing current technology is the ultimate remedy to Brazil's ecological problems. • Dynamic ARDL applied to Brazil's time series data. • Renewable energy and Technology innovation improve environmental quality. • Trade and globalization also reduce Ecological Footprints (EF). • Economic Growth contributes to higher EF. [ABSTRACT FROM AUTHOR]

The world is moving towards a low-carbon economy through renewable energy sources. In this context, concentrating solar power (CSP) technologies can exploit the rich solar resource in Brazil, diversifying the national electricity mix. The aim of this paper is to support the insertion of CSP generation in the Brazilian bottom-up model MATRIZ by analyzing the environmental performance of three CSP technologies: (i) solar tower power (STP) with a thermal storage system (TSS) of 7.5 h; (ii) solar thermal parabolic trough (STPT) with a TSS of 6 h; and (iii) STPT without TSS. From a life cycle perspective, their freshwater consumption and greenhouse gas (GHG) emissions are addressed by employing the software SimaPro, the Ecoinvent database, and the ReCiPe 2016 method, as well as information from the system advisory model (SAM) and the literature. As a result, STP is the most environmentally sound CSP alternative, presenting lower GHG emissions and water consumption than the two STPT technologies. In general, CSP generation proves to be more environmentally attractive than some fossil-fired power plants and renewable energy sources. Moreover, moving the manufacturing of CSP technologies to Brazil has the potential to reduce GHG emissions from the upstream processes of their value chain. [ABSTRACT FROM AUTHOR]

Hydroelectric power plants have been losing competitiveness to renewable resources in Brazil, specifically wind and solar power resources, given the current water crisis in the country, which has left main reservoirs in the Brazilian hydroelectric power system depleted. However, other renewable energy resources show disadvantages in terms of intermittence and energy storage. Pumped Hydropower Storage (PHS) can help mitigate this problem, supplying energy with fewer variations. This paper studied using PHS concepts together with solar and/or wind renewable resources to recover water levels at the Furnas reservoir in terms of energy and economic performance. The energy studies were developed by sizing the PHS and identifying solar and wind resource potential for supplying energy for pumps in the hydropower plant. The economic analyses considered three different scenarios (I; II and III), and used the NPV (Net Present Value), and LCOE (Levelized Cost of Electricity) methods for a period of 30 years. Energy calculations showed that 1692 MWh/day of energy could be generated using PHS. However, 2729 MWh/day of energy would be needed to store generated energy, and a 1037 MWh negative energy balance will be compensated for by using daily wind and/or solar photovoltaic power production. This would allow the Furnas reservoir to regain 0.45 m of its water level per year. The economic studies showed economic viability for PHS scenarios I and III, with estimated NPV at 151.5 million dollars, and 64.5 million dollars for the last year of the project, respectively. Scenario II was unviable, giving rise to several strong discussions on this application within Brazil. • Wind and solar sources were considered for the pump energy supply. • The proposed system can recover 0.45 m/year of the level in the Furnas reservoir. • The energy production of the reversible power plant was estimated as 1,692MWh/day. • Economic feasibility was evaluated in many scenarios using NPV and LCOEmethods. • Market regulation is required for the diffusion of this technology in Brazil. [ABSTRACT FROM AUTHOR]

Brazil has great potential for diversification and decarbonization of its energy matrix, with the insertion of a clean and renewable energy source such as hydrogen. This paper seeks to evaluate the surplus energy potential of solar and nuclear plants installed in the country for the production of green and purple hydrogen using high and low temperature electrolysis methods. Based on official reports and databases of energy production and demand, the results indicated that the total potential of surplus solar energy is equal to 4.29E+07 (kWh.d−1). Further, the total potential of electricity production from the hydrogen obtained through surplus solar energy was equivalent to1.87E+07 (kWh.d−1); and the total cost of producing solar hydrogen is equal to 1.07E+03 (USD.kWh−1). In conclusion, the study contributed to demonstrate the pathways to the establishment of strategies that assist the transition to a hydrogen economy in Brazil. [Display omitted] • Surplus energy potential of solar and nuclear plants for green and purple hydrogen production. • Potential of surplus solar energy is equal to 4.29E+07 kWh.d−1. • Electricity production equal to.87E+07 kWh.d−1. [ABSTRACT FROM AUTHOR]

The power system long-term expansion planning is a computer-intensive problem as demands a varied set of studies especially considering the increasing deployment of intermittent renewables. In the case of the Brazilian power sector planning, the responsible institutions mostly use proprietary software. This paper presents the multiyear two-stage academic generation and transmission expansion planning software, called CARTHER, developed by the authors in order to provide the academy an open-source and non-commercial software, with a friendly interface and with several applications for expansion planning of hydrothermal systems with high intermittent renewables penetration. CARTHER is then calibrated for a case study in the Brazilian power sector, considering the most recent governmental goals for renewable energies for the horizons of 2030, 2040, 2050 and 2060. The results demonstrate the functionality and the qualitative capacity of CARTHER optimization under the expansion's criteria of flexibility and reliability in the face of the intermittent renewables penetration. [ABSTRACT FROM AUTHOR]

Brazil is a case of the achievement of a high share of wind energy integration to an interconnected power system in an emerging market. A series of successful energy supply programmes and a strong renewable-oriented finance framework implemented since 2002, have promoted alternative renewables – wind installed capacity increased over 22-fold from 927 MW in 2011 to 21 GW in 2022, reaching 11.77% of total procured power. From this, about 90% are concentrated in Brazil's least developed region, the Northeast, where wind investment should create jobs and propel socioeconomic development. Despite that, there is no studies specific assessing the regional and economy-wide effects of those programmes, gap that this paper aims to fill by applying the regional Computable General Equilibrium (CGE) model TERM-BR10. We assess that by modelling an alternative scenario for the period 2010-19 based on an official electricity matrix built in 2010, that projected 3.4 additional GW of wind power while not considering all the success of renewable policies, against the observed installed capacity expansion, where wind power was 3.7 times higher than what had been planned. Our results show that in the absence of renewable policies, Brazil would have faced economic losses such as GDP (−0.27%) and investment (−4.76%). The Northeast region would have been the most impacted in terms of GDP (−1.3%), real wage (−2.99%) and employment creation (−0.1%). We propose that such socioeconomic co-benefits are incorporated in energy planning, which could promote regional equality through renewable energy expansion. • Wind power capacity increased over 20-fold from 2011 to 2022. • 90% are in the poorest region where policies propel development and job creation. • Policy absence would entail a GDP loss of 0.27% nationally and of 1.3% in the region. • Negative impacts to labour market are mostly over skilled jobs. [ABSTRACT FROM AUTHOR]

Geothermal energy is now clearly an important option for the Brazilian energy grid due to the demand for renewable energy sources. The northern and central regions of the Paraná Basin (Brazil) were identified as prospects for additional research into the region's geothermal energy potential in this context by prior geothermal studies. A thorough investigation based on geological, geophysical, and thermal data is necessary to identify regions with a high potential for geothermal energy. When used by various authors to execute these tasks, the Multicriteria Decision Analysis (MCDA) approach built on Geospatial Information Systems (GIS) has shown considerable promise. The weights of the following parameters-rock type, fault proximity, heat flow, magnetic anomaly, and gravimetric anomaly-were determined in this study using the Analytic Hierarchy Process (AHP) approach, which was incorporated into the MCDA. Five favorability maps were created using the data pertaining to these criteria after they had been processed, standardized, and classed. From "very low" to "very high" levels, there were five classes for each selected parameter. From them, we created a map of the geothermal potential based on the list of criteria and the weights assigned to each. In order to verify the findings, we compared the locations of hot springs and aquifers considered indicators of geothermal activity with those of the places with higher potential. Using only one data source, the results showed that four regions had a high index of geothermal favorability, one of which had been previously identified as promising. As a result, the first map produced in the research area using the MCDA-GIS technique is shown in this paper. The strategy proposes a novel way to direct future research to deepen and thoroughly explore these four promising areas. • Geothermal energy gains prominence in Brazil's energy matrices. • Northern & central Paraná Basin offer potential for geothermal energy research, based on prior studies. • MCDA-GIS approach with AHP method proves effective in mapping geothermal favorability. • Hot springs & aquifers compared with high-potential areas validate geothermal activity indicators. [ABSTRACT FROM AUTHOR]

• A new Angle Difference Controller to adapt the power order of embedded HVDC links. • Simulations with the proposed ADC in the official Brazilian Power System model. • Performance comparison of the ADC implemented in LCC HVDC link and VSC HVDC link. • A tutorial example to make it clear the appearance of loop flows in AC-DC systems. This paper discusses the power flow control of embedded HVDC links in the Brazilian grid, with special attention to the requirements of intermittent energy sources where frequent load changes are needed, including power reversal, and automated action is called for. Recently two North-South bipoles, 4000 MW each, ±800 kV, have entered into service, these being embedded in the grid and with separate receiving end converter stations. In this case "reverse" power flow is foreseen, but only on a seasonal basis when water flow is low at the North region. The increasing capacity in wind and solar energy, especially in the Northeast region and the possibility of a new embedded HVDC link to carry the surplus power from this region, call for an adaptable power setpoint in the DC links in order to avoid adverse effects as loop flows and increased losses. The paper investigates the use of angle difference control and proposes a new controller to mitigate those adverse effects. [ABSTRACT FROM AUTHOR]

Before the COVID pandemic, oil and gas companies invested only a small fraction of their capital on sustainable energy technologies. With the substantial improvement in the performance of batteries and their rapid cost reduction, the oil and gas industry could potentially lose a large share of their market in the transport sector. A similar shift in energy sources is happening with the surge in renewable energy sources to supply electricity, heating and cooling. In an ever more sustainable future, the need for an oil and gas industry could reduce significantly. This paper reviews the possible paths that an oil and gas company could follow to become a sustainable development corporation and continue to be relevant in the future. This paper aims to describe alternative sustainable pathways such as the extraction of natural hydrogen, a hydrogen economy, offshore wind power, deep sea mining, biorefineries, seawater air-conditioning, geothermal and geoengineering. This paper also proposes the use of electrolysis ships for the flexible production of green hydrogen and showed that its investment cost can be three times smaller than in fixed electrolysis plants. The oil and gas industry has substantial intellectual, financial capital and geopolitical influence that would not be lost during a shift to a more sustainable world. Indeed, these assets should be used to facilitate the transition to a more sustainable future. • Hydrogen is a good alternative for sustainable development in O&G companies. • Natural hydrogen is a good alternative to the upstream O&G companies. • Benefits of electrolysis ships to produce green hydrogen. • Case study to produce green hydrogen in Brazil. [ABSTRACT FROM AUTHOR]

• Lean combustion in SI engines fueled with both pure CO and hydrogen-rich gas. • Low efficiency of the engine when using pure CO. • Emissions were reduced for syngas H 2 /CO ∼ 1. The possibility of using renewable energy generated in the industrial sector for the combined generation of electricity and heat is becoming one of the most efficient energy generation methods, without the need for sophisticated systems of biogas compression for its use. Different fuels are able to extend the lean threshold of spark ignition engines (SI). Although synthesis gas (syngas) lean combustion raises combustion efficiency, its use can result in high carbon monoxide (CO) emissions, making it urgent to investigate the CO combustion process in SI engines. Currently, only data referring to the combustion of pure hydrogen are found. Also, studies on the emissions from the use of syngas generated from peach kernels and rice husks are scarce. Therefore, the innovation and goal of this paper were to investigate the emissions resulting from lean combustion in SI engines fueled with both pure CO and hydrogen-rich gas with close characteristics of syngas generated from rice husk and peach kernel, two highly produced biomasses in Brazil. As the main results, regarding nitrogen oxide (NO x) emissions, the combustion of pure CO was quite high when compared to syngas. The syngas H2/CO ∼ 1 was also responsible for the largest emission of hydrocarbons (HC), a little less than twice that of H2/CO ∼ 0.38. Furthermore, by allowing lean combustion, the temperatures of the flared gas can be kept below the NO x formation limit. Moreover, the combustion of pure CO resulted in reduced efficiency and increased COV of IMEP. Besides emissions reduction, the use of waste for biofuel production is essential for the overall strategy for a transition to a circular economy. [ABSTRACT FROM AUTHOR]

The global economy is advancing towards a low-carbon future. Alongside this energy transition, the sustainability concept has become a fundamental value of our society, encouraging a worldwide discussion on the consideration of socio-environmental issues by the energy sector. In Brazil, the electricity generation expansion planning has not been doing enough to incorporate these issues into its decision-making process, especially in regards to alternative and renewable energy sources. Considering that Life Cycle Sustainability Assessment (LCSA) is suitable for addressing this situation, we focus on one of its first steps, which consists of defining a set of indicators able to communicate sustainability issues. With this in mind, this paper aims at incorporating sustainability into the decision-making process concerning electricity generation in Brazil by formulating a set of indicators. We carry out a systematic review for collecting the leading environmental, social, and economic indicators used by scientific papers focused on recent and practical LCSA studies concerning electricity generation and that contemplate alternative and renewable energy sources. Thus, we analyze the frequency of indicators in a sample of 41 papers and screen them against selection criteria and their relevance for the Brazilian context. As a result, we establish a set of 28 indicators (18 environmental, four social, and six economic). It is clear from our findings that LCSA practitioners have been facing different levels of methodological and practical challenges depending on the dimension of sustainability, which reflects on the number of environmental, social, and economic indicators collected from the overall sample. • 28 indicators have been selected from a systematic review of practical LCSA studies. • Traditional communities and protected areas were included in this set of indicators. • The final set of indicators covers environmental, social, economic dimensions. • They can be used to incorporate sustainability into the Brazilian electricity sector. • Practical LCSA studies in the electricity sector mainly address environmental issues. [ABSTRACT FROM AUTHOR]

• Emissions may not be reduced under current government guidelines. • Efforts must be made to increase renewables building rates. • Fossil fuels will continue to be important to ensure demand attendance. The use of renewable energy sources in electricity systems has become an important strategy to reduce greenhouse gas emissions in the power sector and to avoid depletion of natural resources. However, uncertainties on renewable power generation, diurnal and seasonal variability, technology costs and regional resources availability are factors that have challenged their large-scale adoption. In this context, studies have been focused on how to best integrate different generation technologies with regards to costs and security of supply. Taking the Brazilian electricity system expansion as a case study, this paper proposes a new hierarchical modelling framework that integrates two electricity planning optimization models: (i) a portfolio theory-based model that deals with the trade-off between security of supply and expected supply cost and (ii) a deterministic least cost model that finds the amount of electricity to be produced by each generation technology. The proposed approach can provide information regarding expected total supply cost, electricity deficit risks, capacity expansion and expected greenhouse gas emissions. Additionally, current government guidelines for renewables expansion are discussed with respect to the Brazilian targets for emissions reduction. Results point to a slight increase in renewables share from 82.4% in 2020 to 85.3% in 2035; however maximum established building rates for renewable generation projects are shown to be very tight and may hamper the achievement of emissions reduction. Overall, it is shown that renewable technologies are attractive for both the environmental and economic spheres, but fossil fuels will continue to play an important role for meeting demand. [ABSTRACT FROM AUTHOR]

• We evaluate decarbonization of passenger transportation in Rio de Janeiro, Brazil. • Public transport and carpooled shared mobility rise system capacity and reduces CO 2. • Biofuels reduce CO 2 emissions at no increased system cost. • CO 2 price is the most effective decarbonization policy, but it is costlier. • Increased renewable electricity and electrification of the fleet reduce the most CO 2. This paper applies an energy systems model to evaluate how shared mobility (ride-hailing and shared autonomous vehicles), public buses, alternative energy sources (electricity and biofuels) and carbon pricing contribute to reduce passenger vehicles CO 2 emissions in Rio de Janeiro state, Brazil, from 2016 to 2050. Public buses and carpooled shared mobility increase system capacity, resulting in lower vehicle ownership, energy demand and CO 2 emissions, as well as savings per ton of CO 2 abated (from $3 to $4186). Biofuels reduce CO 2 emissions at no increased system cost, while carbon pricing is the most effective policy to reduce CO 2 emissions, but it is costlier than the alternatives and results in greater private vehicle use (up to 260%) if the expansion of zero-carbon public transportation remains limited due to technology adoption. The policy that reduces the most emissions (by 84%) combines the expansion of renewable electricity generation and implementation of a CO 2 price. [ABSTRACT FROM AUTHOR]

Forecasting photovoltaic electricity generation is one of the key components to reducing the impacts of solar power natural variability, nurturing the penetration of renewable energy sources. Machine learning is a well-known method that relies on the principle that systems can learn from previously measured data, detecting patterns which are then used to predict future values of a target variable. These algorithms have been used successfully to predict incident solar irradiation, but the results depend on the specificities of the studied location due to the natural variability of the meteorological parameters. This paper presents an extensive comparison of the three ML algorithms most used worldwide for forecasting solar radiation, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Extreme Learning Machine (ELM), aiming at the best prediction of daily solar irradiance in a São Paulo context. The largest dataset in Brazil for meteorological parameters, containing measurements from 1933 to 2014, was used to train and compare the results of the algorithms. The results showed good approximation between measured and predicted global solar radiation for the three algorithms; however, for São Paulo, the SVM produced a lower Root-Mean-Square Error (RMSE), and ELM, a faster training rate. Using all 10 meteorological parameters available for the site was the best approach for the three algorithms at this location. [ABSTRACT FROM AUTHOR]

This paper proposes a novel dynamic pricing scheme for demand response with individualized tariffs by consumption profile, aiming to benefit both customers and utility. The proposed method is based on the genetic algorithm, and a novel operator called mutagenic agent is proposed to improve algorithm performance. The demand response model is set by using price elasticity theory, and simulations are conducted based on elasticity, demand, and photovoltaic generation data from Brazil. Results are evaluated considering the integration effects of renewable energy sources and compared with other two pricing strategies currently adopted by Brazilian utilities: flat tariff and time-of-use tariff. Simulation results show the proposed dynamic tariff brings benefits to both utilities and consumers. It reduces the peak load and average cost of electricity and increases utility profit and load factor without the undesirable rebound effect. [ABSTRACT FROM AUTHOR]