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In developing countries, residual biomass usage by means of anaerobic digestion offers several benefits and opportunities, such as a sustainable energy source, production of organic fertilizers and new agrobusiness models. In Latin America, Colombia is one of the most promising markets for the implementation of this technology in terms of availability of biomass and economic growth, as recently reported by local government organizations. In this paper, special attention is given to Antioquia, a department of Colombia with the largest farms of cattle and pigs, according to information reported in 2018 by the Ministry of Agriculture and Rural Development. It is estimated that manure from the porcine subsector in Antioquia has an approximate technical-energy potential of 1,896 TJ year-1, varying from 1,611 to 2,186 TJ year-1, corresponding to the 95% confidence interval. In the case of manure generated by the livestock subsector in Antioquia, it is estimated a theoretical energy potential of 8,566 TJ year-1. However, traditional extensive production systems disseminate manure through the pastures turning centralization of the available residual biomass a difficult task and not senseful. Based on the local practices of the specialized dairy subsector, it is estimated that manure collected during the milking process could reached up to 25% of the total available. Biochemical conversion of this amount of biomass has an estimated technical-energy potential of 187 TJ year-1, varying from 156 and 236 TJ year-1, corresponding to the 95% confidence. The aim of this article is to estimate the technical-energy potential for the livestock and porcine subsectors in the Department of Antioquia, based on the available residual biomass according to local farming practices. [ABSTRACT FROM AUTHOR]

The vulnerability of electric potential generation from water resources has been evidenced due to uncertainties of climatic origin and energy planning. Changes in rainfall regimes are multifactorial phenomena difficult to model. Rainfall is the main natural way of restoring the reservoir levels of hydroelectric power plants. The reduction in rainfall levels may increase in the coming years, resulting in a probable change of the energy matrix configuration of the state of Minas Gerais (MG). This could reduce the share of renewable sources increasing dependence on the importance of energy from fossil fuels, which are the immediate primary sources of energy available. Prior examinations have portrayed the depletion of hydroelectricity in Brazil, or its macro-regions, however this work tries to supply a more focused look at the effects on the electricity and social sectors of the state of Minas Gerais. The study developed in this paper aims to investigate the hydrological potential alteration impacts and consequences on the energy matrix of the state, the greenhouse gas emissions and the social reflexes of these changes due to scenarios motivated by climate change. The investigation intends to show the importance of the water-energy-emissions nexus for energy planning and decision-making, in order to evaluate the best options for dealing with adverse and potentially destabilizing conditions. The results of the analyses show that while hydropower demand was 5.24 Mtoe in 2015, in 2030 the supply of hydropower will be 5.81 Mtoe and 4.72 Mtoe, for the conservative and severe scenarios, respectively. In addition, the effect of climate change may require an increase in the share of non-renewable sources in the energy matrix, which could increase CO 2 e emissions from 4.2% to 7.4% by 2030, compared to the levels in 2016. • Reduction in rainfall levels will change the energy matrix configuration of MG state. • Population growth will boost demand for energy. • It is shown the importance of the water-energy-emissions nexus for energy planning and decision-making. • The energy matrix may considerably increase the CO 2 e emissions by 2030, compared with 2016 levels in the MG state. [ABSTRACT FROM AUTHOR]

The energy sector is an important factor that influences life quality and economic prosperity. Differences in infrastructure, technology and even in culture of each country make it imperative to include their own characteristics into energy analyses, making it necessary to identify the different types of sources of CO2 emissions and their magnitudes. The aim of this paper is to present a foresight analysis of the productive and energy matrices dynamics in Ecuador for the period 2016-2030 and to propose public policy that contributes to sustainable development. In a first stage, the research has an explanatory character, referring to construction of a model, which uses an extended variation of the Kaya Identity where the volume of CO2 emissions may be examined quantifying contributions of productive sectors activity, sectorial energy intensity, energy matrix, and CO2 emission features. Subsequently, the research acquires a predictive-experimental nature, using exploratory scenarios. That allows linking historic and present events with hypothetical futures. In consequence, driving forces of the scenario can be explained and analysed using quantitative modelling based on the Kaya Identity and qualitative narratives. Within this study two scenarios were built. The Business as Usual scenario, without modifying the structure of productive and energy matrices, and the Alternative scenario that seeks to reduce the consumption of oil derivatives in land transport, which consumes 50% of the country's energy demand. The Alternative scenario, which promotes the use of biofuels, projects to reduce the CO2 emissions from 45.58 to 43.41 Mt of CO2 equivalent for 2030. The policy on biofuels in Ecuador is at an early stage. So, biofuels offer important opportunities: i) diversification of the energy matrix, ii) contribution to energy security, iii) promotion of the growth of the industrial sector, and iv) substitution of fossil fuels and mitigation of the greenhouse gas effects. [ABSTRACT FROM AUTHOR]

The energy matrix is a useful tool for understanding the trends of production and consumption in a country and for evaluating long-term energy policies. This paper presents a behavioral simulation model of the evolution of Chile’s energy matrix. The model is developed and calibrated by considering a dynamic substitution of energy sources. Chile’s stated policy is to become less dependent on imported fossil fuels, to increase security of supply and improve the environment. The simulation experiments show that the energy matrix is very robust with regards to external fuel prices and changes in investment cost. Thus, in order to be able to observe changes in the composition of the energy matrix, there is a need for strong intervention by the regulator, or the government, to provide incentives for renewables. [ABSTRACT FROM AUTHOR]

In this paper we report, first, the Brazilian energy situation from the major oil crisis in the 1970s. Next, we discuss the period from the 1980s until 2005. Finally, it is projected scenarios from recent past (2005-2013), to the future that begins today and runs until 2030. This is a work for educational purposes, in which we provide compiled data for school research in all levels. [ABSTRACT FROM AUTHOR]

In this paper we report, first, the Brazilian energy situation from the major oil crisis in the 1970s. Next, we discuss the period from the 1980s until 2005.Finally, it is projected scenarios from recent past (2005-2013), to the future that begins today and runs until 2030.This is a work for educational purposes, in which we provide compiled data for school research in all levels. [ABSTRACT FROM AUTHOR]

This paper explores the relation between business sustainability, both linked to financial profit as well as to relations with local organizations, and the environment, in a context of an internationalized economy such as the Chilean economy. Likewise, it analyzes recent conflicts originated in Chile for energy supply and the difficulties in defining an energy matrix. Finally, the article analyzes the influence of ecological ethics in the preservation of the high diversity ecosystems in the South of Chile, facing the business development and the specific energy projects. [ABSTRACT FROM AUTHOR]

• Proposed an intelligent approach for transmission line fault analysis based on capsule network. • An unsupervised model is developed which requires no manual labeling of the data. • The performance against line parameter variation and high impedance faults is assessed. • Noises are considered to justify the robustness of the proposed approach. • The performance is compared with the baseline capsule network and existing approaches. Detection and classification of transmission line (TL) faults are key factors for the fault root cause analysis and rapid restoration of the power network. Deep learning can extract representative features automatically from big data, thus becoming an important breakthrough in fault analysis. Existing deep learning-based fault diagnosis models rely on a large number of data obtained from a variety of fault conditions to be generalized. Indeed, in the TL domain, it is difficult to define and, therefore to collect the fault incepted features of all possible fault scenarios. This paper proposes an unsupervised framework for fault detection and classification (FDC) of TL based on a capsule network (CN). Instead of using the baseline CN, an extension to this with a sparse filtering technique is adopted in this work. The capsule network with sparse filtering (CNSF) voluntarily learns the expensive fault features and significantly improves the model performance without involving a large number of data. The proposed scheme receives 1 / 2 cycle post-fault three-phase signals and encodes them into a single image that is defined as the input for the proposed CNSF model. The effectiveness of the proposed CNSF model is corroborated by four different TL topology confirming the model's adaptability to a topology change in response to intended control action or the switching actions due to cascading faults. Further assessment of the model's performance against noise, high impedance faults (HIF), and line parameter variations are also carried out in order to confirm the high reliability of the proposed model. In addition, a rigorous comparative study is conducted to guarantee the state-of-the-art performance of the proposed model. [ABSTRACT FROM AUTHOR]

This paper is a compact version of the 2005 São Luís/ABN AMRO Bank winning monograph that aimed at studying the economic viability of building bioreactors in firms to produce biogas. Firms responsible for generating high volumes of waste can benefit enormously from this implement both to produce their own energy and to discard residues. The latter can also become a rich fertilizer at the end of a process called biodigestion. The article brings studies of bioreactors located in developing and developed nations, as well as a pilot project which has been specially designed by the author for the citrus industry. [ABSTRACT FROM AUTHOR]