Types Of Energy Generation Research Articles

Organic Rankin and Brayton-Joule, a Comprehensive Library for Integrating Conventional and Renewable Energy Generation

The thermodynamic cycles for energy generation are the baseline for development in different types of energy generation, and they are the primary principle for the mix of fossil and renewable energy. In this paper, a detailed description of the organic Rankine and Brayton-Joule cycles has been presented as a comprehensive reference library for linking renewable energy and fossil energy, and an explanation of the governing and basic equations that formulate When developed to be flexible in the use of the research methodology used in this field. This paper provides a comprehensive reference library for linking renewable energy and fossil energy by presenting a detailed description of the organic Rankine and Brayton-Joule cycles. It includes an explanation of the governing equations and basic formulations, as well as a flexible research methodology for use in this field.

KONTROL FREKUENSI BEBAN MENGGUNAKAN METODE ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) PADA SISTEM HYBRID WIND MIKROHIDRO DAN DIESEL

This study aims to analyze and compare the performance of three frequency load controller methods in a hybrid generator consisting of three types of energy generation, namely microhydro, diesel and wind. The controller methods being compared are the PID (Proportional Integral Derivative) method, ANFIS (Adaptive Neuro-Fuzzy Inference System), and Fuzzy. This analysis was carried out to improve the efficiency and stability of the hybrid generating system by optimizing the frequency load controller. Frequency instability can occur due to load fluctuations, changes in environmental conditions, or system disturbances. Therefore, the use of an effective and adaptive controller method is very important in maintaining the stability and reliability of the hybrid generator system. The analytical method used in this study involved data collection and computer modeling. The required data includes information on load variations, energy production, and environmental conditions. Furthermore, the PID, ANFIS, and Fuzzy methods are applied to the data to build a frequency load controller model. The results of the analysis show that the three controller methods have different performance in maintaining frequency stability in the hybrid generator system. The PID method provides a fast and accurate response to load fluctuations, but is less adaptive to environmental changes. While the ANFIS method is able to adapt well to changes in system conditions, it requires time for model training. Fuzzy methods can provide control that is more adaptive and tolerant to disturbances, but may require more complex tuning. However, in general, the use of intelligent controller methods such as ANFIS and Fuzzy can improve the performance of hybrid generators by producing more adaptive and stable controls. This research has important implications for the development of more efficient and reliable hybrid power systems. By choosing the right controller method, hybrid power plants can provide energy in a more stable and environmentally friendly manner, and reduce dependence on limited fossil resources. Therefore, this research can make a significant contribution to the development of renewable energy and sustainable development in the future.

Economic Efficiency of the Implementation of Digital Technologies in Energy Power

The present research prioritized the most important direction of energy power transformation—energy sector digitalization—and its contribution to the achievement of the sustainable development goals focused on climate change mitigation and responsible consumption and production. The authors evaluated the economic efficiency of the implementation of digital tools due to the decrease in energy production costs. The evaluation was performed using the energy cost calculation method before and after the implementation of digital technology, and the digital technology cost calculation method based on the technology readiness level, introduced for the first time. The study demonstrates the advantages of energy power digitalization worldwide, including the achievement of the declared goals of sustainable development and the transition to low-carbon energy. The scientific results obtained are valuable for scholars who carry out research in the area of the efficiency of economic digitalization, since they hold for all countries and types of energy generation. The directions of further research include the development of an analytical notation to show that the digital technology cost also depends on the speed and volume of its distribution, as well as the level of technological development of material and technical resources in the industry and in the country, and also the labor and capital availability.

How shareholders react to sustainable narratives about leading European energy companies? An event study using sentiment data from the global database for events, language and tone (GDELT)

ABSTRACT This study aims to investigate how the shareholders of leading European energy companies value sustainability narratives. It uses news from the Global Database of Events, Location, Language, and Tone (GDELT) and analyses the cumulative average abnormal returns (CAAR) and abnormal volatilities (AV), incorporating the event study methodology. A total of 279,546 big news items were used, and 4,026 event studies were conducted. The extensive analysis of data and the segmentation of the news by tone, type of energy generation and environmental consequences helps to understand shareholders’ investment decisions. This study found that the sustainability narrative significantly impacts shareholder value; however, this narrative’s interpretation has no consensus. The sustainability news about these companies moves the stock market upwards for some shareholders, while others do the contrary. These results are observed by comparing CAAR and AV. The results found by this article are crucial for regulators to push forward an effective ecological transition. It should be legislated so that there is a common shareholders’ narrative, discouraging highly polluting investments.

Synthesis of unused-wood-derived C-Fe-N catalysts for oxygen reduction reaction by heteroatom doping during hydrothermal carbonization and subsequent carbonization in nitrogen atmosphere.

There is an urgent need to develop renewable sources of energy and use existing resources in an efficient manner. In this study, in order to improve the utilization of unused biomass and develop green processes and sustainable technologies for energy production and storage, unused Douglas fir sawdust (SD) was transformed into catalysts for the oxygen reduction reaction. Fe and N were doped into SD during hydrothermal carbonization, and the N- and Fe-doped wood-derived carbon (Fe/N/SD) was carbonized in a nitrogen atmosphere. After the catalyst had been calcined at 800°C, its showed the highest current density (-5.86 mAcm-2 at 0.5 V versus reversible hydrogen electrode or RHE) and Eonset value (0.913 V versus RHE). Furthermore, its current density was higher than that of Pt/C (20 wt% Pt) (-5.66 mA cm-2 @0.5 V versus RHE). Finally, after 50 000 s, the current density of sample Fe/N/SD (2 : 10 : 10) remained at 79.3% of the initial value. Thus, the synthesized catalysts, which can be produced readily at a low cost, are suitable for use in various types of energy generation and storage devices, such as fuel cells and air batteries. This article is part of the theme issue 'Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 2)'.

Zoning for exploration of wind energy in Ceará with the use of geographic information systems (GIS) and multicriteria analysis

Wind energy has many advantages compared to traditional energies, from the ability to reduce the use of fossil fuels as well as the possibility of creating jobs in the areas where the projects are installed. The growth of this type of generation in Brazil has been driven by strong investor interest due to the characteristics of the country's winds, mainly from the Northeast. The winds are strong, stable and most of the time follow the same direction, characteristics that make windfarms in the Northeast region have high levels of capacity factor. By evaluating the data from the wind farms installed in Ceará, it can be observed that they present one of the best capacity factors in Brazil and have values above the world average. This indicates and reinforces the viability of implementing this type of energy generation in the area. It was verified that there are studies about wind conditions but there are no studies that correlate this information with the infrastructure conditions of the State. Therefore, the objective of the present work is to identify the appropriate areas for the allocation and use of wind energy in the State of Ceará through the integration of Geographic Information Systems (GIS) tools and multicriteria analysis for decision making.

Support scheme for electricity output from renewables in Ukraine, starting in 2030

Ukraine has an officially adopted target for energy from renewables of 25% by 2035. Renewable energy producers in Ukraine enjoy a feed-in tariff, valid until 2030. In Ukraine, a debate has begun on whether the feed-in tariff should be prolonged. This paper focuses on the projected cost of electricity from renewables, nuclear and fossil fuels in Ukraine in 2030, based on a levelized cost of energy (LCOE) approach. Results indicate that prolongation of the feed-in tariff is necessary for most types of energy generation from renewables. The existing rate of the CO2 emissions tax is too low to affect the LCOE of fossil fuel-based electricity. Coupled with the projected low price for coal and natural gas, this will make renewables less competitive in Ukraine in 2030 if there is no feed-in tariff.

Coupled Carbon, Sulfur, and Nitrogen Cycles Mediated by Microorganisms in the Water Column of a Shallow-Water Hydrothermal Ecosystem.

Shallow-water hydrothermal vent ecosystems are distinctly different from deep-sea vents, as other than geothermal, sunlight is one of their primary sources of energy, so their resulting microbial communities differ to some extent. Yet compared with deep-sea systems, less is known about the active microbial community in shallow-water ecosystems. Thus, we studied the community compositions, their metabolic pathways, and possible coupling of microbially driven biogeochemical cycles in a shallow-water hydrothermal vent system off Kueishantao Islet, Taiwan, using high-throughput 16S rRNA sequences and metatranscriptome analyses. Gammaproteobacteria and Epsilonbacteraeota were the major active bacterial groups in the 16S rRNA libraries and the metatranscriptomes, and involved in the carbon, sulfur, and nitrogen metabolic pathways. As core players, Thiomicrospira, Thiomicrorhabdus, Thiothrix, Sulfurovum, and Arcobacter derived energy from the oxidation of reduced sulfur compounds and fixed dissolved inorganic carbon (DIC) by the Calvin-Benson-Bassham (CBB) or reverse tricarboxylic acid cycles. Sox-dependent and reverse sulfate reduction were the main pathways of energy generation, and probably coupled to denitrification by providing electrons to nitrate and nitrite. Sulfur-reducing Nautiliaceae members, accounting for a small proportion in the community, obtained energy by the oxidation of hydrogen, which also supplies metabolic energy for some sulfur-oxidizing bacteria. In addition, ammonia and nitrite oxidation is another type of energy generation in this hydrothermal system, with marker gene sequences belonging to Thaumarchaeota/Crenarchaeota and Nitrospina, respectively, and ammonia and nitrite oxidation was likely coupled to denitrification by providing substrate for nitrate and nitrite reduction to nitric oxide. Moreover, unlike the deep-sea systems, cyanobacteria may also actively participate in major metabolic pathways. This study helps us to better understand biogeochemical processes mediated by microorganisms and possible coupling of the carbon, sulfur, and nitrogen cycles in these unique ecosystems.

Optimization Strategies for Sustainable Energy Development in Angola A Multi-Stage Stochastic Approach

This article presents a mathematical model to support the decision making process related to the planning of capacity and operation of hybrid electrical energy systems. The model was developed considering case studies of small villages, in rural areas in Angola. Depending of the local conditions, the system considers the following types of energy generation: photovoltaic, wind energy, thermal and mini hydro. The minimum production capacity in each locality was assessed and the load duration curve was also evaluated. For each type of source, the costs of construction and operation were estimated. The optimization problem is solved as a multi-stage stochastic programming problem, in which the levels of the load duration curve are modelled as stochastic processes. The objective is to define the hybrid combination that minimizes the expected cost of energy. The results illustrate that the multi-stage modelling contributes to the reduction of the risk associated with the decision making process because it incorporates the flexibility to adapt the means of production in accordance to the evolution of the demand.

Impact of wind turbine sound on general health, sleep disturbance and annoyance of workers: a pilot- study in Manjil wind farm, Iran.

BackgroundThe wind turbine’s sound seems to have a proportional effect on health of people living near to wind farms. This study aimed to investigate the effect of noise emitted from wind turbines on general health, sleep and annoyance among workers of manjil wind farm, Iran.Materials and methodsA total number of 53 workers took part in this study. Based on the type of job, they were categorized into three groups of maintenance, security and office staff. The persons’ exposure at each job-related group was measured by eight-hour equivalent sound level (LAeq, 8 h). A Noise annoyance scale, Epworth sleepiness scale and 28-item general health questionnaire was used for gathering data from workers. The data were analyzed through Multivariate Analysis of variance (MANOVA) test, Pillai’s Trace test, Paired comparisons analysis and Multivariate regression test were used in the R software.Results and discussionThe results showed that, response variables (annoyance, sleep disturbance and health) were significantly different between job groups. The results also indicated that sleep disturbance as well as noise exposure had a significant effect on general health. Noise annoyance and distance from wind turbines could significantly explain about 44.5 and 34.2 % of the variance in sleep disturbance and worker’s general health, respectively. General health was significantly different in different age groups while age had no significant impact on sleep disturbance. The results were reverse for distance because it had no significant impact on health, but sleep disturbance was significantly affected.ConclusionsWe came to this conclusion that wind turbines noise can directly impact on annoyance, sleep and health. This type of energy generation can have potential health risks for wind farm workers. However, further research is needed to confirm the results of this study.

Modeling and optimization of building mix and energy supply technology for urban districts

Reducing the energy consumption and associated greenhouse gas emissions of urban areas is paramount in research and practice, encompassing strategies to both reduce energy consumption and carbon intensity in both energy supply and demand. Most methods focus on one of these two approaches but few integrate decisions for supply and demand simultaneously. This paper presents a novel model that endogenously simulates energy supply and demand at a district scale on an hourly time scale. Demand is specified for a variety of building uses, and losses and municipal loads are calculated from the number of buildings in the district. Energy supply is modeled using technology-specific classes, allowing easy addition of specific equipment or types of energy generation. Standard interfaces allow expansion of the model to include new types of energy supply and demand. The model can be used for analysis of a single design alternative or optimization over a large design space, allowing exploration of various densities, mixes of uses, and energy supply technologies. An example optimization is provided for a community near San Francisco, California. This example uses 21 building types, 32 combined heat and power engines, and 16 chillers. The results demonstrate the ability to compare performance trade-offs and optimize for three objectives: life cycle cost, annual carbon dioxide emissions, and overall system efficiency.

LCA of a newsprint paper machine: a case study of capital equipment

The environmental aspects of paper as a consumer good have been extensively studied. However, the paper machine has been mostly neglected in the literature. The purpose of this article is to present a LCA case study that explicitly focuses on the system of a newsprint paper machine and its environmental impacts and not on the system of the consumer good paper. The relevance of the paper machine as capital equipment is analyzed, and conclusions for the environmental improvement of paper machines are drawn based on identified hotspots. The article hereby answers the more general research questions of whether capital equipment has rightly been neglected in other studies regarding pulp and paper and which impact categories are important for analyzing the environmental burdens of a paper machine. The study has been executed in collaboration with Voith Paper, an original equipment manufacturer. Hence, in distinction to literature-based studies, primary data on the paper machine was available resulting in a high overall data quality. Based on the ISO 14040 (2006) and 14044 (2006) standards, this article pursues a cradle-to-grave approach for the paper machine. It assesses the environmental impacts in the impact categories defined by the ReCiPe impact assessment methodology. Different types of energy generation are examined in a scenario analysis with combined heat and power generation (CHP) as the baseline case. For interpretation, a normalization and a sectoral analysis are performed. The normalized results indicate fossil resource depletion and global warming as the most important impact categories. Global warming impacts are highly dependent on the energy processes and result to 432.7 kg CO2e per production of 1 t of paper for CHP and to 701.7 kg CO2e for EU25 grid mix. The sectoral analysis shows that the machinery's operations/use phase is clearly dominating most impact categories due to its long lifetime. An exception is the metal depletion, for which the materials and manufacturing processes are most important. These findings prove that for most categories, the operations/use phase of the paper machine is the most important life cycle stage. In systems focusing on the consumer good paper, it is therefore sufficient to model the operation of the paper machine, whereas the manufacturing, transport, and end-of-life processes regarding the paper machine equipment can be neglected, unless metal depletion is important to the study.

Comparing the ecological footprint with the biodiversity footprint of products

Abstract This study compares the ecological footprints with the biodiversity footprints of products that result from land use and carbon dioxide emissions. The biodiversity footprints were quantified using mean species abundance statistics, whereas the ecological footprint refers to the impacts on bioproductivity. We used a data set of 1340 product systems subdivided into 13 product groups, which included various types of energy generation and material production. We found that the importance of direct land use vs. carbon dioxide emissions is different for biodiversity footprints compared to ecological footprints. This difference is particularly relevant if the environmental impact of bio-based products (dominated by direct land use) is compared with the environmental impact of fossil-based products (dominated by CO 2 emissions). Our results also show that the relative importance of different drivers can change over time within the biodiversity footprint and that the relative importance of climate change significantly increased for longer time horizons. As the interpretation of the biodiversity footprint can differ from the ecological footprint, the inclusion of impacts on biodiversity should be considered in the footprint calculation of products.