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Floating offshore wind is a promising renewable energy source, as 60% of the wind resources globally are found at depths requiring floating technologies, it minimizes construction at sea, and provides opportunities for industrialization given a lower site dependency. While floating offshore wind has numerous advantages, a current obstacle is its cost in comparison to more established energy sources. One cost-reduction approach for floating wind is increasing turbine capacities, which minimizes the amount of foundations, moorings, cables, and O&M equipment. This work presents trends in mass-optimized VolturnUS hull designs as turbine capacity increases for various wave environments. To do this, a novel rapid hull optimization framework is presented that employs frequency domain modeling, estimations of statistical extreme responses, industry constructability requirements, and genetic algorithm optimization to generate preliminary mass-optimal VolturnUS hull designs for a given turbine design and set of site conditions. Using this framework, mass-optimized VolturnUS hull designs were generated for 10–30 MW turbines for wave environments of varying severities. These design studies show that scaling up turbine capacities increases the mass efficiency of substructure designs, with decreasing returns, throughout the examined turbine capacity range. Additionally, increased wave environment severity is shown to increase the required mass of a given substructure design. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution presents an upspring opportunity for the African continent to adopt technologies such as artificial intelligence, big data, internet-enabled industrial platforms, 3D printing, robotics, nanotechnology, and blockchains. This is more so because the past three industrial revolutions saw the African continent being left out of its opportunities despite its affluent population and natural resources. Africa stands to benefit from industrial development, digitalization, and greater integration, which would result in more excellent opportunities for the growing youthful populations. However, for the digital transformation strategy and other key industry 4.0 opportunities to be successful, reliable infrastructure, affordable and stable electricity, and greater awareness are critical and imperative. This review examines the possible energy options that the continent of Africa can explore and implement for the successful deployment of Industry 4.0. The impact, difficulties, and opportunities of the fourth industrial revolution technologies on African development are discussed. Also discussed are various forms of renewable energy options based on Africa's geographic location. This review will assist researchers and policymakers in implementing Industry 4.0 in Africa. [ABSTRACT FROM AUTHOR]

Current research assesses the impact of industrialization and the renewable energy sector on greenhouse gas emissions, proxied by CO2 emissions in Europe and Central Asia. We rely on a two-step system GMM estimator on a sample of 48 countries over the period 2000–2018. Empirical results show that industrialization has a positive effect on CO2 emissions: a 10% increase in industry value added as % of GDP leads to an increase of 2.6% in CO2 emissions. In contrast, renewable energy mitigates CO2 emissions. Ten percentage points increase in renewable energy consumption reduces CO2 emissions per capita by 2.2%. The interaction term between renewable energy and industry value added is negative, suggesting that renewable energy consumption compensates for the negative effect of industrialization on environmental quality. Our main results also confirm the U-shaped inverted relationship between GDP per capita and CO2 emissions. Our study has a number of policy implications and avenues for future research. [ABSTRACT FROM AUTHOR]

The current fossil fuel-based generation of energy has led to large-scale industrial development. However, the reliance on fossil fuels leads to the significant depletion of natural resources of buried combustible geologic deposits and to negative effects on the global climate with emissions of greenhouse gases. Accordingly, enormous efforts are directed to transition from fossil fuels to nonpolluting and renewable energy sources. One potential alternative is biohydrogen (H2), a clean energy carrier with high-energy yields; upon the combustion of H2, H2O is the only major by-product. In recent decades, the attractive and renewable characteristics of H2 led us to develop a variety of biological routes for the production of H2. Based on the mode of H2 generation, the biological routes for H2 production are categorized into four groups: photobiological fermentation, anaerobic fermentation, enzymatic and microbial electrolysis, and a combination of these processes. Thus, this review primarily focuses on the evaluation of the biological routes for the production of H2. In particular, we assess the efficiency and feasibility of these bioprocesses with respect to the factors that affect operations, and we delineate the limitations. Additionally, alternative options such as bioaugmentation, multiple process integration, and microbial electrolysis to improve process efficiency are discussed to address industrial-level applications. [ABSTRACT FROM AUTHOR]

This study aims to explore the relationship between industry value added, renewable energy, and CO2 emissions in a sample of 44 Sub-Saharan African countries over the period 2000–2015. This study makes several important contributions to extant research. While existing research was focused on the renewable energy-CO2 emissions nexus, the current study assesses the moderating role of the renewables sector in the industrialization-CO2 emissions relationship. In addition, this study considers whether EKC relationships will hold after accounting for structural transformations (including industrial contributions to GDPs). Moreover, we are revising the existence of the EKC framework for the Sub-Saharan African countries. Using a two-step system GMM estimator, we found that the share of industry in GDP has a significant positive impact on CO2 emissions, while renewable electricity output reduces CO2 emissions. If causal, a one percentage point increase in renewable electricity output reduces carbon emissions by 0.22%. Moreover, the renewable energy sector then mediates the positive effect of industry value added on CO2 emissions. We also find evidence for the statistical significance of the inverted U-shaped relationship between GDP per capita and CO2 emissions. [ABSTRACT FROM AUTHOR]

The demands for alternative energy resources have been increasing exponentially in the 21st century due to continuous industrial development, depletion of fossil fuels and emerging environmental consciousness. Renewable energy sources, including wind energy, hydropower energy, geothermal energy, solar energy, biomass energy and ocean power, have received increasing attention as alternative means of meeting global energy demands. After Japan's Fukushima nuclear plant disaster in March 2011, more and more countries are having doubt about the safety of nuclear plants. As a result, safe and renewable energy sources are attracting even more attention these days. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved in the past few decades from a marginal activity into a multi-billion dollar industry. In this research, a comprehensive evaluation model is constructed to select a suitable location for developing a wind farm. The model incorporates interpretive structural modeling (ISM), benefits, opportunities, costs and risks (BOCR) and fuzzy analytic network process (FANP). Experts in the field are invited to contribute their expertise in evaluating the importance of the factors and various aspects of the wind farm evaluation problem, and the most suitable wind farm can finally be generated from the model. A case study is carried out in Taiwan in evaluating the expected performance of several potential wind farms, and a recommendation is provided for selecting the most appropriate wind farm for construction. [ABSTRACT FROM AUTHOR]

This paper lays out the role of the first centre in the world for the integration into the electrical grid of electricity coming from renewable energy (the Spanish acronym for which is CECRE (Centro de Control de Energías Renovables; Control Centre for Renewable Energies)) and the industrial development of large energy suppliers and wind turbine manufacturers in Spain. These two initiatives enabled the development of one of the first integrated markets for this type of energy source. The key contributions were the development of two software programs (wind management and management of solar light incidence), their visual implementation, and centralized digital control. An economic and business history approach is used to show the rise and relative failure of the Spanish wind industry during the period 2004–2015, when Spain became the fourth country after China, the US, and Germany in terms of installed capacity of renewable energy and, in relative terms, the second country after Denmark. This study is unique in that it provides an integrated vision of the reasons for the relative fall of Spain in the world ranking of wind energy producers. The methodology of the economic analysis of industrial policies makes it possible to explain the fall in the relative importance of Spain in the international panorama of wind farms. [ABSTRACT FROM AUTHOR]

Rational decision-making requires assessing the advantages and disadvantages of options, including nonmarket effects (such as environmental effects). This also applies to strategic decision-making in the industrial sector to select alternative renewable energy source (RES). Often, a variety of criteria can be used to select a renewable energy source, whereas no ideal family of criteria for renewable energy selection for industry has been defined in the literature. It was concluded that there is a need to support the actions of industrial development based on RES, which will contribute significantly to overcoming the limitations of the negative effect on the environment in terms of greenhouse gas emissions. There is a clear need for a systematic and polyvalent multicriteria approach to planning in industry. Therefore, a method for choosing the preferred renewable source of electricity for industry has been developed, which considers key criteria of RES choice: Expert opinions, the costs of obtaining the energy and maintaining energy installations, and the volume of electricity from RES. This article offers a modified multicriteria selection method based on a fuzzy analytic hierarchy process (fuzzy AHP) and the technique for preference by similarity to an ideal solution (TOPSIS), integrated with a qualitative price analysis (ACJ). This new method was tested through a case study on selecting a preferred RES in Polish industrial conditions. The research results indicate that the proposed method of choosing the preferred renewable energy source can be used in industrial enterprises that strive to meet their energy needs in accordance with the principles of social responsibility. [ABSTRACT FROM AUTHOR]

The demands for energy in general and electrical power in particular in the process of industrialization–modernization in Vietnam are increasing. Although other renewable energy sources such as wind and solar power have been prioritized, they cannot compensate for the shortages of electricity in Vietnam; moreover, traditional energy sources in Vietnam are not endless and will soon reach exhaustion. Nowadays, the government has chosen a solution to maximize domestic energy resources, i.e., develop renewable energy combined with importing coal and gas in appropriate proportions with the construction of nuclear power plants (NPP), which may be the optimal solution to ensure energy security, environmental protection, and sustainable development. However, site selection for construction of a nuclear power plant is one of the most difficult decisions that management faces. Thus, the authors proposed multicriteria decision-making (MCDM), including a fuzzy analytic network process (FANP) and technique for order preference by similarity of an ideal solution (TOPSIS) for NPP location selection in Vietnam. In the first stages of this research, the weight of all criteria and subcriteria will be calculated by an ANP model using fuzzy logic. A TOPSIS model is proposed for ranking all potential locations in the final stage. The results reveal that Binh Thuan is the best place for building an NPP in Vietnam. The contributions of this research include a fuzzy multicriteria decision-making (F-MCDM) approach for NPP site selection in Vietnam. This research also utilizes the evolution of a new approach that is flexible and practical for the decision-maker and provides useful guidelines for NPP site selection in countries around the world. [ABSTRACT FROM AUTHOR]