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Due to growing worldwide energy demand, the search for diversification of the energy matrix stands out as an important research topic. Bioethanol represents a notable alternative of renewable and environmental-friendly energy sources extracted from biomass, the bioenergy. Thus, the assurance of optimal growth conditions in the fermenter through operational variables manipulation is cardinal for the maximization of the ethanol production process yield. The current work focuses in the determination of optimal control scheme for the fermenter feed rate and batch end-time, evaluating different parametrization profiles, and comparing evolutionary computation techniques, the genetic algorithm (GA) and differential evolution (DE), using a dynamic real-time optimization (DRTO) approach for the in silico ethanol production optimization. The DRTO was able to optimize the reactor feed rate considering disturbances in the process input. Open-loop tests results obtained for the algorithms were superior to several works presented in the literature. The results indicate that the interaction between the intervals of DRTO cycles and parametrization profile is more significant for the GA, both in terms of ethanol productivity and batch time. In general lines, the present work presents a methodology for control and optimization studies applicable to other bioenergy generation systems.

The modern paradigm of sustainable development is based on concepts and theories in which the needs of individuals and society, the limits of economic growth and the balance of industrial and natural systems are close to consistency [...]

The use of fossil fuels as the main source of energy for most countries has caused several negative environmental impacts, such as global warming and air pollution. Air pollution causes many health problems, causing social and economic negative effects. Worldwide efforts are being made to avoid global warming consequences through the establishment of international agreements that then lead to local policies adapted to the development of each signing nation. In addition, there is a depletion of nonrenewable resources which may be scarce or nonexistent in future generations. The preservation of resources, which is a common goal of the Circular Economy strategy and of sustainable development, is not being accomplished nowadays. In this work, the calculation of indicators and mathematical and statistical analysis were applied to clarify and evidence the trends, provide information for the decision-making process, and increase public awareness. The fact that European countries do not possess abundant reserves of fossil fuels will not change, but the results of this analysis can evolve in the future. In this work, fossil fuel energy consumption, fossil fuel depletion, and their relationship with other variables, such as energy dependence and share of renewable energy in gross final energy consumption, were analyzed for 29 European countries. Furthermore, it was possible to conclude that many European countries still depend heavily on fossil fuels. Significant differences were not found in what concerns gross inland consumption per capita when the Kruskal–Wallis test was applied. It was possible to estimate that by 2050 (considering Jazz scenario) it will only remain approximately 14% of oil proven reserves, 72% of coal proven reserves and 18% of gas proven reserves. Given the small reserves of European countries on fossil fuels, if they need to use them, they will fast disappear.

The scale of waste formation from coal-fired generation is significant and tends to grow steadily in the context of the global use of coal for power production. This paper covers the problems and current opportunities for recycling coal fly ash waste from coal generation from the position of a stakeholder approach, namely, identification of the main participants and determination of the effects for economic agents in coal fly ash recycling projects. Based on the method of economic modeling and the empirical assessment of project efficiency, this paper presents alternative patterns of stakeholder interaction in the process of implementing coal fly ash recycling projects, estimates the effects of using coal fly ash, and identifies conflicting interests between stakeholders. It is shown that the reason behind the low interest of the Russian private sector in the processing of coal fly ash is the lack of stimulating market mechanisms for manufacturers and consumers of ash products, the high risks of implementing recycling projects based on clean coal technologies, and low environmental payments for commercial companies.

A model has been developed for the optimization of the share structure of an investment portfolio in high-tech projects supported by the leaders of the leading industry companies in Russia. Several indicators (financial leverage, integrated rating of companies, industry rating) were applied in the decision support system for the shared distribution of investments. High-tech production is based on innovative technologies for saving resources, the resiliency of systems for transporting and transferring raw materials and finished products within Russia, so the main income will remain within the country. It is possible to export high-tech products, rather than raw materials, which will increase export revenues. Investors will invest in high-tech projects of Russian companies, taking into account the targeting of investment development. The guarantee is the stable financial position of the companies and the competitiveness rating. Methods: The authors propose a new approach that does not contradict modern rating scales, based on a hierarchical rating procedure and fuzzy logical rules that allow you to build an integral rating in the form of portfolio shares from the whole. A higher share shows an indicator of the higher investment attractiveness of companies. The industry rating is obtained based on the principle of the company’s first affiliation to the highest rating indicator. The final minimax portfolio is based on the initial ratings in a circular convolution and is then adjusted by industry. A software package has been compiled that allows the testing of the method of capital allocation between investment projects for the largest companies’ leaders of high-tech industries in Russia. This software uses the author’s method of multi-stage analysis, the evaluation of financial coefficients, the integral ranking and the correction of the solution taking into account the industry attributes. Results: The results are presented with computer-aided design (CAD) in the form of an algorithmized decision support system (DSS). The CAD system is based on a hierarchical algorithm, based on the use of a multi-level redistribution of investment shares of high-tech companies, taking into account the adaptation to the requirements of the return on investment portfolio. When compiling the portfolio, the minimax optimality criterion is applied, which allows the stabilization of the risk by purposefully redistributing funds between the companies involved in the analysis. The authors of the article have compiled an algorithm for the software implementation of the model. Features of the rating approach: the use of the author’s mathematical apparatus, which includes a hierarchical analysis of the ranked indicators of the financial and economic activity of companies, taking into account their priority, and the use of a minimax approach to obtain a rating assessment of companies, taking into account the industry attributes. Development: The proposed approach should be used for targeted financing of large industry companies engaged in the implementation of high-tech projects.

Government regulation with respect to the reduction of greenhouse gas emissions has been actively developing in the world in the past three decades, mainly in form of carbon taxation and emission trading systems with a carbon price as their basic representation. With more than 50 countries already applying such regulation and many others looking in that direction due to their obligations under the Paris Agreement, the question of suitable carbon price is still open. The aim of this paper is to form groups of countries according to the chosen economic, environmental and regulation factors to facilitate decision-making regarding the formation of energy transition regulation policies. Clustering analysis was carried out to identify countries with similar features in the research area. Five clusters with average carbon price ranging from USD 5.3 to 49.2 per t were obtained. The hypothesis of the study regarding direct connection between the level of economic development and state regulation was partially confirmed. It was revealed that most of the countries with active carbon regulation depend on the external supply of fossil energy sources. The results of the clustering could serve as a benchmark for the countries with similar indicators.

Renewable energy has become a crucial factor for circular economies, sustainable development, and the environment given the limited non-renewable energy reserves and global environmental degradation mainly resulting from non-renewable energy use. This study explores the effect of educational attainment and economic growth on renewable energy use in a sample of selected emerging markets over the 2000–2018 period through causality and cointegration analyses. Causality analysis points out a significant unidirectional causality from indicators of educational attainment and economic growth to renewable energy use. In other words, educational attainment indicators and economic growth are significant determinants of renewable energy in the short run. Furthermore, the cointegration analysis ascertains a positive influence of indicators of educational attainment and economic growth on renewable energy use in the long run. The findings of both analyses indicate that educational attainment and economic growth have a significant impact on renewable energy use in the short and long term. Therefore, the policies fostering educational attainment can be used as instruments to increase the share of renewable energy use in total energy consumption.