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Long term annual electricity consumption forecasting is very important for country's energy planning. These forecasts are influenced by several factors (political, technological, social, environmental and economic), and brings with itself a high uncertainty degree in its results and difficulties in the evaluation of such factors over them. A methodology that eases to take into account these factors aiming improve the results and help understanding the electricity consumption annual trajectory till the forecast horizon is, therefore, very much useful and desired. So, we propose a modelling structure using the bottom-up approach to cope with these matters and to evaluate the trajectory of long term annual electricity consumption of a sector of the Brazilian industry up to 2050 considering energy efficiency (EE) scenarios. It is important to emphasize that Brazil is a developing country, and to build a bottom-up approach was a challenge, mainly due to the fact that this model is data intensive. In particular, this modelling was applied in the pulp and paper sector. The main goal was to consider technological diffusion scenarios in EE measures, and show the energy savings achieved. The results point an energy savings in the order of 25% when an actual scenario is considered. [ABSTRACT FROM AUTHOR]

Brazil has an energy system with a hydrothermal characteristic that interconnects consumers and generators covering 98% of the demand for energy supplies. Most of the plants are concentrated in the southeast region, where the largest consumers and the largest population concentration are located. The expansion of this system, considering the hydroelectric contributions, will occur exploring the potentials located in the Amazon region. This analysis paper shows that the variations imposed by climate changes on some climatological variables create significant uncertainties about the power generation forecasts of the hydroelectric power plants to be installed in the Amazon, thus compromising the financial economic feasibility of these enterprises and also possibly compromising the expansion plans of the Brazilian energy system. The methodological approach uses information from various climate change scenarios and compares those with historical hydrological patterns and generation information. By exploring the characteristics of a large-scale hydrothermal system with high dependence on water resources, this paper provides valuable insights on how energy policy would address hydroelectric vulnerabilities and climate change. This analysis is focused on the Brazilian case but reveals important issues related to systems with hydro thermal characteristics. [ABSTRACT FROM AUTHOR]

The electric energy matrix in Brazil mostly comprises energy from hydroelectric power plants, approximately 60.8%. This large participation presents some vulnerability in periods of drought and often the country's electric energy matrix is complemented by the use of other energy sources, such as thermoelectric. Even though it is currently among the largest onshore wind power producers in the world, Brazil has not yet started developing this energy source in the offshore segment. However, this study shows that offshore wind energy can be a complementary energy source for the country's electric energy matrix, and thus replace other energy sources which have more impact on the environment. Therefore, this study sought to develop a methodology that can be easily replicated using free access tools, aiming to contribute to the development of offshore wind technology and future research in the country. The results show a large production of offshore wind energy in the southeastern region of Brazil. The "Cabo Frio 2″ data collection point presented the highest annual production of offshore wind energy. However the study opted for the "Arraial do Cabo-A606″ collection point located in the state of Rio de Janeiro and at ocean depths that can be reached by fixed foundations. • A simplified methodology is presented to estimate offshore wind energy potential. • The energy potential is calculated in different sites in the southeast of Brazil. • The developed methodology is user-friendly and has free access tools. • The offshore wind energy can contribute to complement the energy matrix of Brazil. • This paper expands the scarce literature about offshore wind energy in Brazil. [ABSTRACT FROM AUTHOR]

Oil and gas offshore platforms present similar structural designs and include operations such as separation, compression and pumping. However, they handle large variations in the production of hydrocarbons and water over time. They may also follow different modes of operation depending on the field characteristics and fluid properties. It is therefore not possible to suggest a standard layout of an offshore platform that can be widely implemented in distinct petroleum regions. The oil and gas processing plant should be designed adequately to maximise the hydrocarbon production and minimise the power, heating and cooling demands. The utility plant should be designed appropriately to minimise the fuel consumption and cover the energy needs in all production phases. The present paper presents a generic methodology that addresses these challenges and builds on a combination of process simulation, energy analysis and optimisation routines. Possible platform layouts are sized, evaluated and ranked, based on preliminary estimates of the production profiles and petroleum properties. This methodology is applied to three case studies, derived from actual field data from Norway and Brazil, with different field conditions, fluid compositions (e.g. negligible, medium and high CO 2 contents of the well-fluids) and operational requirements (e.g. gas export, injection and lift). The results illustrate the benefits of the proposed methodology, as a comparison with the 'business-as-usual' case shows up to 25–30% energy savings and CO 2 -emissions along the field lifespan. • A novel methodology for designing and optimising energy-efficient platforms is presented. • Different petroleum compositions and production profiles are considered. • Various concepts for local power and heat generation and process design are assessed. • Energy savings and CO2-reductions can reach up to 25–30% compared to business as usual scenarios. [ABSTRACT FROM AUTHOR]

Abstract Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. Highlights • Comparison of technology representation and techno-economic parameters of 15 IAMs. • Structural differences in representing technology in IAMs are identified. • Methods of projecting techno-economic parameters differ across IAMs. • Strict harmonization of techno-economic parameters across models is difficult. • Recommendation to publish techno-economic parameters and technology representation. [ABSTRACT FROM AUTHOR]

Abstract The paper aims to discuss the adaptation of a brazilian social housing project to the Passive House standard, by defining the thermal envelope construction fabric for different climates of southern Brazil, from a base line according to the Brazilian performance standard. The study was developed in 4 steps, where a numerical model was set up and runned in a transient regime, using EnergyPlus® software. In the first step, the thermal and energy performance of the reference base model was assessed. In the second step, a sensitivity analysis was performed, varying the thermal envelope parameters of the building case study, in order to satisfy the minimum performance of the classification level A, according to the Brazilian Energy Efficiency Regulation (RTQ-R). In a third step, the external envelope of the building was optimised, through a multi-objective evolutionary algorithm. In a last step, the numerical model defined according to the Passive House standard was optimised, in order to obtain optimal solutions. Thermal and energy performance and economic viability of the solutions were analysed. Solutions attending to RTQ-R presented additional investment between 26% and 27% and solutions attending to Passive House standard presented additional costs of 39% and 42% for the three bioclimatic zones. Highlights • An optimisation methodology for Passive House design is presented. • An evolutionary multi-objective algorithm is used for thermal building simulation. • Different bioclimatic zones in Brazil are investigated. • Energy performance and thermal comfort of the buildings are significantly improved. • The Passive social interest housing is economically viable for bioclimatic zone 2. [ABSTRACT FROM AUTHOR]

Abstract Onshore wind and solar-photovoltaic-based electricity are expected to drive most of the global growth in renewable energy sources capacity until 2020. This creates a challenge for properly modelling such intermittent variable resources since: (i) their availability varies spatially and temporally and (ii) thus, their integration in power systems is determined by the configuration of transmission grids. Large energy system models usually adopt simplified approaches for modelling wind and solar photovoltaic (PV) deployment and the power grid. This paper uses the recently developed TIMES-Brazil optimisation model to study the role of transmission bottlenecks in cost-effective long-term deployment of wind and solar power in the Brazilian energy system up to 2050. The model explicitly models the grid infrastructure of 29 regions in Brazil differentiated according to existing power plants, wind and solar availabilities, future RES potentials and power demand. Three different scenarios (Free Trade, Simplified Trade and Detailed Trade), with increasingly more detail in modelling electricity transmission lines, were tested. Findings show that a more detailed transmission infrastructure significantly affects capacity deployments and electricity prices. The grid connecting the North and South of Brazil was found to be the most important bottleneck affecting the deployment of solar in the country. Highlights • This study evaluates the relevance of modelling transmission for long-term planning. • It uses the TIMES model for exploring least-cost energy pathways for Brazil. • The existence of inner sub-regional limits can impact inter-regional expansion. • Less constrained scenarios may provide an optimistic view of RES expansion. • The more constrained scenario is 77% more expensive than the unbounded one. [ABSTRACT FROM AUTHOR]

Abstract The Brazilian electricity system is an important example of a large country relying on a high renewable energy matrix with a major focus on hydropower, which has historically allowed for low carbon electricity production. However, the increase in the demand and climate change impacts on the availability of these renewable resources represent important challenges for long-term power planning. The contribution of this paper is twofold: Firstly, a first attempt to use the EnergyPLAN model for the analysis of the Brazilian electricity sector and in particular to study future scenarios is presented. Secondly, the possibility of achieving a 100% RES system is also addressed. The 100% RES scenario is found to be theoretically possible but a substantial increase in the overall installed capacity would be required, to support the grid mainly during the spring and summer season. The results underline the importance of seasonal complementarity of hydro and wind power and reveal how an increase in RES would add exportation potential, reducing also the Brazilian external energy dependency. The study identifies risk factors for these high RES scenarios and outlines several avenues for future research to address cost, environmental and technical uncertainties of the system. Highlights • The Brazilian power sector is analysed with EnergyPLAN computer model. • Renewable scenarios are compared for technical, cost, emissions and risk parameters. • The importance of seasonal complementarity of hydro and wind power is outlined. • The 100% RES scenario results in full decarbonization of the system at higher cost. • The 100% RES scenario results in higher exportation and lower importation potential. [ABSTRACT FROM AUTHOR]

Technology selection, its power and efficiency determination for electricity generation using agroforestry residues is the main goal and the novelty of this paper. It is based on the fitted efficiency vs. power curves for commercial mature technologies. The assessment of the level of maturity of biomass-based electricity generation Technologies based on Technology Readiness Levels was used as criteria to define the technologies to be considered in this study: conventional Rankine cycle, organic Rankine cycle and gasifier/internal combustion engine. Pretreatment technologies influence on generation costs is determined based on chippers and drum dryers cost and its energy consumption. We developed a coherent methodology for selecting the technology and calculation of power/efficiency of electricity generation projects considering biomass derived from plant-based lignocellulosic solid biomass residues derived from agricultural and forest activities. A case study based on eucalyptus forest residues availability in three microregions of the Minas Gerais State in Brazil allowed to define the technology to be used in each case and its power, efficiency and levelized cost of electricity, that includes pretreatment and logistic costs. Obtained LCOE values are compared with data from different publications, that is a validation of the presented methodology. Results allow concluding about the considerable influence of residues logistics on LCOE. [Display omitted] • Lowest LCOE corresponds to CRC:0,1652 USD/kWh. • Highest LCOE corresponds to G/ICE with 0,3080 USD/kWh. • Costs and power consumption data of pretreatment technologies are presented. • Fitted power-efficiency curves based on an extensive literature review are presented. • Only technologies with higher maturity, CRC, ORC and G/ICE, are considered. [ABSTRACT FROM AUTHOR]

This paper proposes a new computational tool, called SolarEnergy, which was implemented through an innovative methodology to perform technical-economic analysis of photovoltaic (PV) microgeneration in Brazil. SolarEnergy calculates energy flow and energy bill savings based on the rules of the Brazilian NEM scheme. From the maximization of the net present value, SolarEnergy provides the optimal nominal power according to the orientation and slope of PV panels and the electricity consumption profile. This functionality is crucial to avoid undersizing or oversizing, which commonly occurs in practice. In addition, the tool provides the following information: (i) electricity generation, (ii) net present value, (iii) modified internal rate of return, (iv) discounted payback time, and (v) sensitivity analysis of key parameters (e.g., nominal power, pv system cost, electricity tariff, and minimum attractive rate of return). Currently, such particularities are characterized as relevant differences in relation to other computational tools. The validation and applicability of SolarEnergy are demonstrated from case studies of PV systems installed in the state of Goiás, Brazil. • An innovative computational tool, called SolarEnergy, for PV systems is proposed. • SolarEnergy performs technical-economic analysis of PV microgeneration in Brazil. • SolarEnergy takes into account the new Brazilian Net Energy Metering (NEM) scheme. • SolarEnergy provides economic indicators such as NPV, MIRR, and Discounted Payback. • SolarEnergy provides optimal sizing of PV systems from an economic point of view. [ABSTRACT FROM AUTHOR]

This paper assesses the economic feasibility of ethanol and higher alcohols production through a thermochemical route in Brazil. This route comprises mainly sugarcane bagasse gasification, syngas cleaning, and synthesis of alcohols. Ethanol production costs and associated risks are evaluated in different scenarios. A case study of a virtual plant to be located adjacent to a sugarcane mill, in the state of São Paulo, is presented with the objective of finding the minimum ethanol selling price (MESP) that makes the plant’s project economically feasible. The analysis utilizes first the traditional discounted cash flow method and then proceeds to use a stochastic approach, which is more suitable to study economic feasibility under uncertainty conditions. In the latter approach, prices of raw materials and products are modelled through a mean reverting stochastic process, and economic feasibility is analysed with the help of Monte Carlo simulations. Results are summarized via a histogram of the MESPs obtained for different simulated price scenarios. Finally, the project’s risk is evaluated by computing the number of instances in which the MESP is greater than the ethanol market price. [ABSTRACT FROM AUTHOR]

This paper shows a novel stochastic maximum power point tracking (MPPT) control for photovoltaic (PV) generators. The PV generator is taken disconnected from the grid, i.e., it considers a direct-current (DC) microgrid supplying varying loads. In this setting, we examine how random, varying loads affect the stability and efficiency of the PV generator. The load changes its value according to a Markov chain, the main assumption of this paper. PV generators are complex nonlinear devices, a challenge from the modeling viewpoint. An alternative becomes converting the nonlinear PV generator model into a Takagi-Sugeno (T-S) fuzzy model. The resulting stochastic T-S fuzzy system has its stability characterized by a condition written in linear matrix inequalities (LMIs). The usefulness of our approach is illustrated by simulating the PV generator model fed with real-time weather data collected in Brazil. The corresponding data indicated that the MPPT efficiency was greater than 99.5 % , thereby outperforming other methods from the literature. The corresponding data confirm that the DC-DC converter circuit was able to track maximum power from the PV generator against random load variations. Comparisons with other methods indicate the potential of our approach for PV generators. • A novel MPPT control is proposed for PV generators with unpredictable load demand. • The stability of the system's operations is analyzed with stochastic aspects. • The proposed stochastic MPPT approach has been compared with P&O and INC algorithms. • The control strategy efficiency is tested under real-time climatic data. [ABSTRACT FROM AUTHOR]

Abstract: This paper discusses the complementarity between hydroelectricity and surplus electricity from sugarcane biomass-based cogeneration plants in sugarcane mills. The paper investigates opportunities and barriers in the context of governments'' initiatives, institutions and prevailing regulatory frameworks in Brazil and Nepal. The paper finds that bioelectricity from cogeneration can be a good complementary option for hydroelectric power, helping foster diversification on the generation side and enhance security of electricity supply based on local resources. Bioelectricity potential from sugarcane biomass is estimated to be in the range of 209–313 GWh for Nepal and 62–93 TWh for Brazil. In Nepal, the grid connected bioelectricity can provide power for operating industries, and support local development through rural electrification. In Brazil, the biomass potential can be further enhanced through a better utilization of the biomass in the sugar-ethanol industry to balance hydropower availability. This comparative study offers a reflection on the need for better planning and policies to address the barriers which are hindering the development of bioelectricity even in places where the potential is large. [Copyright &y& Elsevier]

Investment decisions in renewable energy sources such as small hydro, wind power, biomass and solar are frequently made in the context of enormous uncertainty surrounding both intermittent generation and the highly volatile electricity spot prices that are used for clearing of trades. This paper presents a new portfolio-based approach for selecting long-term investments in small-scale renewable energy projects and matching contracts for the sale of the resulting electricity. Using this approach, we have formulated a stochastic optimisation model that maximises a holding company's risk-averse measure of value. Using an illustrative example representative of investment decisions within the Brazilian electricity system, we investigate the sensitivity of the optimised portfolio composition and commercialisation strategy to contract prices in the free contracting environment and to the decision maker's attitude towards risk. The numerical results demonstrate it is possible to reduce significantly financial risks, such as the price-quantity risk, not only by exploiting the complementarity of the considered renewable sources generation profiles, but also by selecting the optimal mix of commercialisation contracts from different markets. We find that the multi-market strategy generally results in appreciably higher optimal value than single-market strategies and can be applied to a wide range of renewable generators and contracts. [ABSTRACT FROM AUTHOR]

Abstract: During the past decade, the Brazilian electric power sector went through similar institutional changes taken place in both developing and developed countries. The main goals for such changes were to inject competition into the generation and supply links of the sector''s production chain and to reduce public debt via privatization of state-owned utilities that dominated the pre-reform sector. This paper discusses why these changes took place in Brazil and explains why the results of the reform model implemented by the previous federal administration were unsatisfactory. The current federal administration has substantially altered the prior model, aiming to remedy insufficient private investment in new power stations that caused a serious power shortage in 2001. The paper addresses the main characteristics of the new model, which implements (a) public biddings of new power plants for all distribution utilities in the country, and (b) forward planning of optimal commissioning times and capacity of new plants. The paper ends with a discussion of the potential benefits and drawbacks of the new scheme and the role of the regulator in the early stage of the ongoing transition in the Brazilian electrical power industry. [Copyright &y& Elsevier]

Abstract: Many works have shown the potential of the Brazilian sugarcane industry as an electricity supplier. However, few studies have studied how this potential could be achieved without jeopardizing the production of sugar and ethanol. Also, the impact of modifications in the cogeneration plant on the costs of production of sugar and ethanol has not been evaluated. This paper presents an approach to the problem of exergy optimization of cogeneration systems in sugarcane mills. A general model to the sugar and ethanol production processes is developed based on data supplied by a real plant, and an exergy analysis is performed. A discussion is made about the variables that most affect the performance of the processes. Then, a procedure is presented to evaluate modifications in the cogeneration system and in the process, and their impact on the production costs of sugar, ethanol and electricity. Furthermore, a discussion on the renewability of processes is made based on an exergy index of renewability. As a general conclusion, besides adding a new revenue to the mill, the generation of excess electricity improves the exergo-environmental performance of the mill as a whole. [Copyright &y& Elsevier]

Abstract: In several countries biodiesel blending programs have been implemented looking for reduction in fossil fuel dependence and environmental benefits, including climate change mitigation. The current global biodiesel production, from different fatty raw materials, reaches about 6 billion liters per year and represents 10% of whole biofuel production. Nevertheless, in many cases the actual advantages of biodiesel production and usage are not clearly evaluated. Essentially, the feasibility of biodiesel production can be determined by its efficiency in solar energy conversion, as indicated by agro-industrial productivity and energy balance parameters, which expresses a relative demand of natural resources (land and energy) to produce biofuel. Taking into account the Brazilian conditions, in this paper an assessment of biodiesel production is presented, comparing four different productive systems. According to this evaluation, soybean and castor are limitedly feasible, whereas tallow and palm oil represent more suitable alternatives. The selection of an efficient productive system is crucial for the rationality of biodiesel production. [Copyright &y& Elsevier]

Abstract: This paper aims at analyzing particularities of the Brazilian electric system and at evaluating the potential contribution of thermal power plants targeting at its higher reliability. In special, the aim is at analyzing the insertion of thermal power production in the present context in which hydroplants start to be built in the Amazon area with small reservoir capacity. An assessment of the behavior of the energy inflows and of the regularization capacity of the Brazilian hydro power system emphazises the need for having a good quality thermal power expansion. The power production from sugarcane residues is specially considered due to the existing untapped potential (about 4 times higher than the installed capacity, considering the current availability of biomass) and the existing window opportunity due to the expansion of sugarcane industry in Brazil (mostly for ethanol production). [Copyright &y& Elsevier]

Abstract: This paper examines the dynamic relationships between pollutant emissions, energy consumption, and the output for Brazil during 1980–2007. The Grey prediction model (GM) is applied to predict three variables during 2008–2013. In the long-run equilibrium emissions appear to be both energy consumption and output inelastic, but energy is a more important determinant of emissions than output. This may be because Brazilian unsustainable land use and forestry contribute most to the country’s greenhouse gas emissions. The findings of the inverted U-shaped relationships of both emissions–income and energy consumption–income imply that both environmental damage and energy consumption firstly increase with income, then stabilize, and eventually decline. The causality results indicate that there is a bidirectional strong causality running between income, energy consumption and emissions. In order to reduce emissions and to avoid a negative effect on the economic growth, Brazil should adopt the dual strategy of increasing investment in energy infrastructure and stepping up energy conservation policies to increase energy efficiency and reduce wastage of energy. The forecasting ability of GM is compared with the autoregressive integrated moving average (ARIMA) model over the out-of-sample period between 2002 and 2007. All of the optimal GMs and ARIMAs have a strong forecasting performance with MAPEs of less than 3%. [Copyright &y& Elsevier]

Abstract: This paper addresses the impact of both economic growth and financial development on environmental degradation using a panel cointegration technique for the period between 1980 and 2007, except for Russia (1992–2007). In long-run equilibrium, CO2 emissions appear to be energy consumption elastic and FDI inelastic, and the results seem to support the Environmental Kuznets Curve (EKC) hypothesis. The causality results indicate that there exists strong bidirectional causality between emissions and FDI and unidirectional strong causality running from output to FDI. The evidence seems to support the pollution haven and both the halo and scale effects. Therefore, in attracting FDI, developing countries should strictly examine the qualifications for foreign investment or to promote environmental protection through the coordinated know-how and technological transfer with foreign companies to avoid environmental damage. Additionally, there exists strong output-emissions and output-energy consumption bidirectional causality, while there is unidirectional strong causality running from energy consumption to emissions. Overall, the method of managing both energy demand and FDI and increasing both investment in the energy supply and energy efficiency to reduce CO2 emissions and without compromising the country’s competitiveness can be adopted by energy-dependent BRIC countries. [ABSTRACT FROM AUTHOR]

Abstract: The increasing demand for energy, especially from renewable and sustainable sources, spurs the development of small hydropower plants and encourages investment in new survey studies. Preliminary hydropower survey studies usually carry huge uncertainties about the technical, economic and environmental feasibility of the undeveloped potential. This paper presents a methodology for large-scale survey of hydropower potential sites to be applied in the inception phase of hydroelectric development planning. The sequence of procedures to identify hydropower sites is based on remote sensing and regional streamflow data and was automated within a GIS-based computational program: Hydrospot. The program allows spotting more potential sites along the drainage network than it would be possible in a traditional survey study, providing different types of dam-powerhouse layouts and two types (operating modes) of projects: run-of-the-river and storage projects. Preliminary results from its applications in a hydropower-developed basin in Brazil have shown Hydrospot’s limitations and potentialities in giving support to the mid-to-long-term planning of the electricity sector. [ABSTRACT FROM AUTHOR]

Sugarcane is one of the most important industries of the Brazilian economy, and its main products are sugar and ethanol. Most of the industrial plants produce both products in an integrated process, in which the sugarcane bagasse is a by-product that can be used as a fuel in the cogeneration system. The bagasse is used as the only fuel of the plant, supplying all energy required for the process, and also producing electricity surplus that may be sold to the grid. In this paper, exergy analysis is used to assess an integrated sugar and ethanol plant with its cogeneration system. The plant was divided into eight sub-systems to evaluate the irreversibility generation in each separately. Data from typical sugarcane factories in Brazil, which produce sugar and ethanol, were used in the process simulation. The analysis has shown that the sub-systems with the highest contribution for the total irreversibility generation of the plant were co-generation, juice extraction and fermentation. Some improvements are proposed, including process thermal integration and the introduction of more efficient equipments for prime mover and steam and electricity generation. The analysis indicated that the total irreversibility could be reduced by 10% should those changes be implemented. [Copyright &y& Elsevier]

Taking Brazilian bioethanol as an example, this paper presents possible sustainability criteria for a certification scheme aimed to minimize negative socio-ecological impacts and to increase the sustainable production of biomass. We describe the methods that have led us to the identification of a first set of feasible sustainability criteria for Brazilian bioethanol and discuss issues to be considered when developing certification schemes for sustainability. General problems of a certification scheme lie in the inherent danger of introducing new non-tariff trade barriers and in the problems of including important higher scale issues like land conversion and food security. A certification system cannot replace a thorough analysis of policy impacts on sustainability issues. [Copyright &y& Elsevier]

Bioethanol as fuel oxygenator is currently being introduced in Mexico with an estimated yearly demand of 3 billion liters expected to be produced mainly from sugarcane. This paper studies how to employ some of the expertise acquired by Brazil during its transition from typical mills into advanced biorefineries to retrofit the Mexican sucroalcohol industry. A typical Mexican sugarcane factory design is retrofitted to three biorefinery designs commonly found in Brazil, which are an autonomous distillery, a biorefinery with 50:50 feedstock ratio for ethanol and sugar production and a molasses distillery. The results of a techno-economic analysis considering these four designs under Mexican conditions are presented, followed by an economic comparison of the autonomous distillery design operating under Mexican and Brazilian conditions. Sustainability analysis is then carried out to identify the advantages and drawbacks of each design. The analysis compares an environment-driven scenario promoting bioethanol production and use for phasing out fossil fuels, against a commercially focused framework considering only environmental and economic issues affecting stakeholders' profit. Results show in monetary terms the impact of each indicator of a retrofitting path from currently profitable biorefineries coproducing sugar and alcohol to sustainable distilleries using molasses and juice as feedstock to produce bioethanol. • Retrofitting the Mexican sugar industry with Brazilian expertise for ethanol production. • Techno-economic and sustainability analyses of all designs. • Calculation with same tools and bases, thus highlighting differences between countries. • Comparison of environment-driven sustainability versus current commercial practice. [ABSTRACT FROM AUTHOR]

The global electricity sector is responsible for a large share of greenhouse gas. Renewable energy (RE) is a feasible alternative to maintain sustainable growth and economic development, as it appears to be a means to reduce emissions and decarbonize economies. Renewable energy projects present some uncertainties and flexibilities that are ignored by traditional methods of evaluation, such as the net present value (NPV), which can lead to undervaluation. This paper aims to assess the switch-output option and defer option for RE projects according to their features in the Brazilian electricity market. The real options approach (ROA) for RE projects seeks to capture the value of uncertainties and flexibilities that all projects have from an investor's point of view. Then, when we adopted a more sophisticated approach that values flexibilities and uncertainties for RE projects, it was possible to conclude that there was a clear increase in value when compared to traditional investment analysis methods like the NPV. • The penetration of renewable energy in the Brazilian Electricity Market is growing. • The Real Options Approach represents an alternative to traditional methods of investments analysis. • Real options deals with the inherent characteristics of renewable energy projects. • Real Options show an increase in value when compared to traditional methods. [ABSTRACT FROM AUTHOR]

Abstract: This paper assessed the economic impact of alternative depreciation methods on the development of combined heat-and-power (CHP) systems in the Brazilian industrial sector. Alternative depreciation methods were proposed and the case study of a Brazilian chemical plant showed that the most effective depreciation method for the promotion of CHP plants in Brazil was the Matheson method with an accelerated depreciation schedule of 7 years. This alternative method was then applied to the Brazilian chemical industry as a whole, increasing its installed capacity in CHP systems by 24%. Therefore, fiscal incentives can be an interesting tool for promoting energy efficiency in the Brazilian industrial sector, promoting the expansion of CHP plants. It reduces government fiscal revenues, but it also induces the technological reposition and improves the feasibility of ventures that are not installed without this kind of incentive. [Copyright &y& Elsevier]

In recent years, agricultural commodity prices have followed trends similar to those observed in crude oil markets. A respective hypothesis to explain this finding: Agricultural production is so energy intensive that increasing energy costs drive cost of production of crops and ultimately commodity prices. This paper will provide answers to the question: What is the share of energy costs in total cost of production for agricultural commodities, including the transport of these commodities to ports? A case study-based calculation for cost of production and transport of soybeans and corn produced in Mato Grosso, Brazil reveals that energy costs play a significant role in total cost at the port. However, given the fact that this share is around 35%, at most, it does not seem likely that a strong correlation between crude oil prices and agricultural commodity prices is caused primarily by the energy costs of crop production and related transport. • Energy cost in crop production and transport is not driving crop prices. • Variance in energy cost of different tillage systems not important. • Energy cost to produce nitrogen more important than on-farm energy cost. • Transport energy cost can be decisive for total energy cost of delivery. [ABSTRACT FROM AUTHOR]

Improving the energy efficiency of emerging economies is the core of achieving efficient global development. This paper innovatively applies the slack based DEA to analyze the energy structure and energy-saving potential of BRICS countries in the past three decades. The results of empirical analysis show that, first, Brazil and Russia ranked first and last with the average efficiency of 0.5941 and 0.0921 respectively in the 30-year observation period. Second, the slack variable of each country is very large. For example, in 2018, India needs to reduce 436.17 Mtoe coal consumption, 105.65 Mtoe oil consumption, 25.39 Mtoe natural gas consumption, and 2038.05 million tons of carbon emissions to reach an effective state. Third, the reasons for inefficiency vary from country to country. Brazil, Russia, and India have low levels of energy management and lack of advanced key technologies. China and South Africa are faced with the problems of scale diseconomy and unreasonable resource allocation structure. The research results are helpful to understand the changing trend of energy efficiency and the reasons for low efficiency in BRICS, and can provide a reference for the formulation of scientific development strategy, which has important practical significance. Image 1 • Russia ranks last among the BRICS countries with an average efficiency of 0.0921. • The highest average efficiency is found in Brazil at 0.5941. • Brazil, Russia, and India lack of advanced key technologies. • China and South Africa are facing the problems of diseconomy of scale. [ABSTRACT FROM AUTHOR]

Wind energy is one of the sources which is still in development in Brazil. However, it already represents 17% of the National Interconnected System. Due to the high level of uncertainty and fluctuations in wind speed, predicting wind energy with high accuracy is challenging. In this context, this paper proposes a novel decomposition-ensemble learning approach that combines Complete Ensemble Empirical Mode Decomposition (CEEMD) and Stacking-ensemble learning (STACK) based on Machine Learning algorithms to forecast the wind energy of a turbine in a wind farm at Parazinho city, Brazil, using multi-step-ahead forecasting strategy. The approached forecasting models were k -Nearest Neighbors, Partial Least Squares Regression, Ridge Regression, Support Vector Regression, and Cubist Regression. Additionally, Box-Cox transformation, correlation matrix, and principal component analysis were used to pre-process the data. The performance of the proposed forecasting models was evaluated by using three performance metrics: mean absolute error, mean absolute percentage error, and root mean square error, and the Diebold-Mariano statistical test to evaluate the forecasting error signals. The proposed models outperform the CEEMD, STACK, and single models in all forecasting horizons, with a performance improvement that ranges 0.06%–97.53%. Indeed, the decomposition-ensemble learning model is an efficient and accurate model for wind energy forecasting. Image 1 • A novel decomposition-ensemble learning model is proposed for wind energy forecasting. • CEEMD method deal with the non-linearity and non-stationarity of the time series. • Different preprocessing approaches are employed to deal with the high-correlation of the system's inputs. • STACK approach by divide-and-conquer scheme takes advantages of the models. • Proposed model improves the accuracy of wind energy forecasting multi-step ahead. [ABSTRACT FROM AUTHOR]

The profitability of a wind power project is evaluated during its development phase through a complete site assessment. At this stage, the LCoE (Levelized Cost of Energy) is determined considering many variables, such as wind turbine model, project layout, energy production, CAPEX (Capital Expenditure), OPEX (Operational Expenditure) and financial costs. However, in recent years, the seasonality and variability of the wind farms energy production have been gaining importance in this process in some markets, due to a migration of the new wind power projects from the regulated market to the free market. In the free market, the PPAs (Power Purchase Agreements) have short-term balance payments, different from the regulated market. In Brazil, payments in the regulated market are performed monthly based on the long-term AEP (Annual Energy Production) expected values, with annual and quadrennial balance payments. This paper focuses on an extensive case study of Brazil, where the energy spot prices vary constantly between 10 USD/MWh and 100 USD/MWh, exposing the wind farms owners to very relevant financial risk when trading energy based on long-term bilateral contracts. The assumed risks can become critical in cases of periods with extreme meteorological anomalies (wind speed variations below the respective long-term expected values), especially in situations where a simultaneous drought period occurs, eventually raising the market spot price to its ceiling value. A SPE (Specific Purpose Entity) account must be properly dimensioned and maintained, similar to a working capital, in order to the wind farm to be able to operate through these low wind speed periods without any capital call to the wind farm's controllers. This represents additional financial costs in the form of trapped cash. This study analyses the wind speed variability in NE-Brazil, where most of the wind farms in the country are concentrated, and analyses how the portfolio effect contributes to the reduction of this variability. This has been performed making use of the data provided by 4 met masts that surround the NE Brazilian territory (with distances between them ranging from 459 km to 724 km) and combining the obtained values to theoretical turbine power curves of different MW platforms (2, 3, 4 and 6 MW). The total period of available measurement sums more than 29 years of data. The results showed that the variability was higher in periods of lower average wind speed and that the analyzed location with the highest variability was the one close to the coast and with higher altitude. Additionally, the combinations that provided the best portfolio effect were those that included the location in the SW, furthest from the coast and with higher altitude. The different turbine platforms did not present a relevant difference in terms of resulting variability on the energy production nor portfolio effect, but when considering the cumulative impact of the meteorological anomalies (larger periods of wind speeds above or below the long-term expected values), the larger the wind turbine, the larger was the resulting exposure. • Results cover Brazilian NE territory, the windiest in the country. • Variability and portfolio effect results analyzed in terms of wind and energy. • Variability is higher in periods of lower average wind speed. • Variability is higher in region closest to the coast and with high altitude. • Best portfolio effect was not the one with all regions included. [ABSTRACT FROM AUTHOR]

The flexibility in grid operations has become a valuable solution to respond to the several problems brought about by the growth of intermittent renewable generation. The use of Demand Response (DR) measures has emerged as a promising option to tackle these challenges. However, to the best of the authors' knowledge, the assessment of the theoretical DR potential has not yet been fully addressed in the available literature. This paper presents a first attempt to establish the theoretical load flexibility potential for the Brazilian power sector and includes two central issues: (1) a sectoral assessment across the residential, commercial and industrial sectors and (2) a regional analysis by broadly splitting up the Brazilian power system into four main subsystems. Our findings reveal that the overall maximum hourly theoretical DR potential in Brazil is expected to double, increasing from 12.8 GW in 2017 to almost 25.6 GW by 2050. Although the majority of the demand-side response potential seems to lie in the industrial sector, a lower but still substantial potential for the residential and commercial sectors has been also identified. The evidence from this study supports the hypothesis that the commercial sector will have a key role in offering the most valuable load flexibility potential (i.e. when the power system mostly needs). The high expected increase in the overall electricity DR potential for the residential sector is driven mainly by the increase in both the number of households and the number of appliances per house. However, large amounts of flexible loads in the residential sector might not be necessarily available during on-peak times. Findings of this research may be of great assistance for future analyses to identify, for example, the extent to which DR can cost-effectively compete with other supply-side options. • The theoretical DR potential is assessed for the Brazilian power system. • The majority demand-side response potential seems to lie in the industrial sector. • Lower but a still substantial potential for the residential sector has been also identified. • The maximum theoretical DR potential is expected to double between 2017 and 2050. • Residential DR potential is not available during highest demand periods. [ABSTRACT FROM AUTHOR]

Although several studies have recognized the challenges brought about the high integration of Renewable Energy Sources (RES), research has yet to systematically investigate the effects of different levels of Energy Efficiency Measures (EEMs) on power systems with a high share of RES. The primary aim of this paper is to quantitatively evaluate the economic impact of different levels of energy efficiency investments in systems with a high share of RES, based on the case of Brazil. Our review analysis revealed a lack of understanding of how to calculate the Long-term Average Cost of Saved Electricity (LACoSE). Therefore, the methodological contribution of this research also lies in the proposition of a step-by-step procedure to estimate this variable. Findings of this study suggest that EEMs may result in a reduction in the expected new installed capacity between 1.9% and 10.3%, and from 0.4% to 4.3% for the total CO 2 emissions (for reductions in the final electricity demand varying from 1% to 5% respectively). This comes with a decrease in the overall system costs between 1.9% and 7.7%. The results provide further support for the hypothesis that the economic impacts of energy efficiency investments and its cost-effectiveness are affected by the share of RES in the power system and these type of measures may provide holistic benefits including not only economic advantages but also environmental and social improvements. The proposed methodology largely extends beyond the case addressed as it may provide valuable lessons for other electricity systems. • Cost-effectiveness of energy efficiency measures is assessed for a renewable system. • A methodology is proposed to calculate the Long-term Average Cost of Saved Electricity (LACoSE). • The economic benefits are positive for the power system evaluated. • Results are not highly influenced by the estimated LACoSE. • Findings would support the development of effective energy efficiency policies. [ABSTRACT FROM AUTHOR]

The decision of the location for the installation of photovoltaic power plants is a critical issue for large-scale projects due to climatic aspects, the proximity to other facilities, and the presence of protected environmental areas. The objective of this study is to propose a model capable of indicating the best location for the implantation of large-scale photovoltaic plants. According to the proposed modeling, the relevant factors were identified to be considered in the choice of the ideal place, which were combined with the GIS-MCDM tools. The analysis of the areas was processed by the gvSIG software, using AHP methods for the weighting of the factors and TOPSIS for ranking the alternatives. In application of this model, a total of 453 areas were identified that could receive a large photovoltaic installation, equivalent to 1823.35 km2 of the study area. Among these study areas, according to our model rating, 67.23% of them are inadequate, 0.52% is good, 12.34% are very good, and only 19.91% are excellent. Since the areas considered excellent are concentrated in the extreme south of the analyzed region, a place of low index of slope and near the substation. In order to validate the quality of the solution obtained by the proposed model was applied a detailed analysis with two scenarios. In the first one are used weights equal to all the criteria and in the second, the MAUT method was applied to rank the alternatives. The modeling proposed in this paper combining with GIS-MCDM is applicable to similar investigations in other regions and also to evaluate the spatial adequacy of other renewable energy technologies. • Evaluation and classification of the best locations for the implantation of solar photovoltaic power plants. • Method applied between the combination of a geographic information system (GIS) and multicriteria decision methods (MCDM). • The AHP-TOPSIS methods are used to evaluate appropriate areas. • The sensitivity analysis is performed to test the reliability of the model. • A methodology that is easily modifiable and replicable by researchers. [ABSTRACT FROM AUTHOR]

This paper analyzes the main impacts of high penetration levels of wind power in the power system of Southern Brazil. For this, an hourly operation of the Brazilian Southern power system is simulated using an Economic Dispatch Model. Two main scenarios are explored: a baseline and a wind penetration case, both for 2030 and 2050. To create these scenarios, results from an Integrated Energy Model are used as inputs for the dispatch model. The economic dispatch modeling led to some expected outcomes, such as a reduction in the system generation cost, a reduction in greenhouse-gas emissions, and a greater need for transmission expansion in the wind-power scenarios. Results also show that, even for a power system as flexible as the one in Southern Brazil, wind power penetration impacts can be observed. Moreover, results show that setting thermal power plants to provide secondary reserve can potentially improve the balancing management in hydropower-based systems. Finally, results from linking the Economic Dispatch Model and the Integrated Energy Model showed the need for better combining energy expansion models with power dispatch models that consider both the operation and the transmission system restrictions, in order to have stable and feasible unit commitment schedules. • Different levels of wind power penetration impact hydropower systems differently. • High wind penetration systems require detailed power transmission models. • Greater insights can be gained by combining the strengths of various modeling tools. • Secondary reserve provided by thermal plants can improve balancing management. [ABSTRACT FROM AUTHOR]