Hasil untuk "Renewable energy sources"

M. I. Khan, J. Shin, Jong Deog Kim

Microalgae have recently attracted considerable interest worldwide, due to their extensive application potential in the renewable energy, biopharmaceutical, and nutraceutical industries. Microalgae are renewable, sustainable, and economical sources of biofuels, bioactive medicinal products, and food ingredients. Several microalgae species have been investigated for their potential as value-added products with remarkable pharmacological and biological qualities. As biofuels, they are a perfect substitute to liquid fossil fuels with respect to cost, renewability, and environmental concerns. Microalgae have a significant ability to convert atmospheric CO2 to useful products such as carbohydrates, lipids, and other bioactive metabolites. Although microalgae are feasible sources for bioenergy and biopharmaceuticals in general, some limitations and challenges remain, which must be overcome to upgrade the technology from pilot-phase to industrial level. The most challenging and crucial issues are enhancing microalgae growth rate and product synthesis, dewatering algae culture for biomass production, pretreating biomass, and optimizing the fermentation process in case of algal bioethanol production. The present review describes the advantages of microalgae for the production of biofuels and various bioactive compounds and discusses culturing parameters.

D. Larcher, J. Tarascon

D. Richardson

M. Beaudin, H. Zareipour, Anthony Schellenberglabe et al.

H. Lund

Anurag Chauhan, R. Saini

N. Ghaffour, J. Bundschuh, Hacène Mahmoudi et al.

Gülden Bölük, M. Mert

Ümran Şengül, Miraç Eren, Seyedhadi Eslamian Shiraz et al.

B. Bhandari, Kyung-Tae Lee, Gil‐Yong Lee et al.

Zeineb Abdmouleh, R. Alammari, A. Gastli

Zhiyuan Fan, Tianyi Lin, Bolun Xu

This paper develops a multi-period optimization framework to design a voluntary renewable program (VRP) for an electric utility company, aiming to maximize total renewable energy deployments. In the business model of VRP, the utility must ensure it generates renewable energy up to the total amount of contract during each market episode (i.e., a year), while all the revenue collected from the VRP must either be used to invest in procuring renewable capacities or to maintain the current renewable fleet and infrastructure. We thus formulate the problem as an optimal pricing problem coupled with revenue allocation and renewable deployment decisions. We model the demand function of voluntary renewable contracts as an exponential decay function based on survey data. We analytically derive the optimal pricing policy of the VRP as a function of the current grid carbon intensity. We prove that a myopic policy is conditionally optimal, which maximizes renewable capacity in each period, attains the long-run optimum due to the utility's revenue-neutral constraint. We show different binding conditions and marginal values of decision variables correspond to different phases of the energy transition, and that the utility should strategically design its revenue-sharing decisions, balancing investments in renewable expansion and subsidizing existing renewable fleets. Finally, we show that voluntary renewable programs can only extend renewable penetration but cannot achieve net-zero emissions or a fully renewable grid. This pricing-allocation-expansion framework highlights both the potential and limitations of voluntary renewable demand, providing analytical insight into optimal policy design and the qualitative shifts occurring during the energy transition process.

K. Krishna, K. S. Kumar

Omojola Awogbemi, Dawood A. Desai

The rising global population, dwindling fossil-based energy reserves and grave environmental concerns have made the search for affordable, renewable and sustainable energy sources more compelling. Bioenergy has become one of the viable alternatives for fossil-based energy sources and a prominent part of the global energy mix. We review the application of bamboo as a feedstock for the generation of various forms of bioenergy. We give an overview of the global market size, cultivation, harvesting, pretreatment techniques, properties and characterization of bamboo as a promising lignocellulosic biomass for bioenergy production. The processes for the conversion of bamboo into pellets, briquettes, biochar, bioethanol, biooil, biobutanol, syngas, biogas and biomethane are highlighted. The deployment of bamboo as feedstock for bioenergy generation is cost-effective, sustainable, ensures high conversion efficiency and generates high bioenergy yield and quality. The limitations of deforestation, land allocation, water use concerns, scalability, lack of biomass bioenergy market and inconsistent policies can be solved through the institution and funding of more novel research and the enactment of appropriate policies and regulations. Further studies into the optimization of bamboo species, process parameters, reactor configurations, development of integrated pretreatment techniques, genetic modification of bamboo, life cycle and environmental impact assessments, and sustainability will advance bamboo bioenergy research. More innovative research and development, development of academia and industry players’ cooperation, enactment and implementation of ethical, legal, and regulatory frameworks, and incentivizing the bamboo bioenergy market are recommended to ameliorate the identified challenges limiting the development of bamboo bioenergy.

Dhanunjay Kumar Ammisetti, Satya Sai Harish Kruthiventi, Krishna Prakash Arunachalam et al.

Magnesium alloys, like AZ31, possess a desirable low weight and high specific strength, which make them favorable for aerospace and auto applications, yet their difficulty to machine limits their broader implementation for the industry. Electrical discharge machining (EDM) is an effective technology for machining difficult-to-machine materials, particularly when the materials are reinforced with ceramic and graphene-based fillers. This study examines the impact of reinforcement percentage (R) and different electrical discharge machining (EDM) parameters such as current (I), pulse on time (T_on) and pulse off time (T_off) on the material removal rate (MRR) and surface roughness (SR) of AZ31/B₄C/GNPs composites. The combined reinforcement range varies from 2 wt.% to 4 wt.%. The Taguchi design (L27) is utilized to conduct the experiments in this study. ANOVA of the experimental data indicated that current (I) significantly affects MRR and SR, exhibiting the greatest contribution of 44.93% and 51.39% on MRR and SR, respectively, among the variables analyzed. The surface integrity properties of EDMed surfaces are examined using SEM under both higher and lower material removal rate settings. Diverse machine learning techniques, including linear regression (LR), polynomial regression (PR), Random Forest (RF), and Gradient Boost Regression (GBR), are employed to construct an efficient predictive model for outcome estimation. The built models are trained and evaluated using 80% and 20% of the total data points, respectively. Statistical measures (MSE, RMSE, and R²) are utilized to evaluate the performance of the models. Among all the developed models, GBR exhibited superior performance in predicting MRR and SR, achieving high accuracy (exceeding 92%) and lower error rates compared to the other models evaluated in this work. This work demonstrated the synergy between techniques in optimizing EDM performance for hybrid composites using a statistical design and machine learning strategies that will facilitate greater use of hybrid composites in high-precision engineering applications and advanced manufacturing sectors.

YU Su, ZHOU Zexin, WANG Xingguo

Differential protection is a primary protection scheme commonly deployed for high-voltage AC outgoing lines connecting renewable energy power plants. To holistically evaluate its adaptability in such scenarios， this paper proposes an adaptability analysis method for power-frequency differential protection based on the current complex plane. By leveraging the characteristics of the current complex plane， the method decouples the influence of fault current magnitude， phase angle， and restraint coefficient from both line terminals on protection adaptability. It quantitatively analyzes how the current magnitude and controlled phase characteristics of renewable energy sources affect protection adaptability. Based on this analysis， requirements for selecting the restraint coefficient of differential protection are established， offering practical guidance for setting the protection restraint coefficient in renewable energy grid integration projects.

Shristi Tandukar, Tek Maraseni, Tapan Sarker

Abstract Accelerating climate change has harmed food and water security and affected both terrestrial and aquatic systems, hindering efforts to meet many Sustainable Development Goals [SDGs]. Climate finance can help mobilize financial resources and tackle the effects of climate change. This study analyzes existing literature on climate finance more broadly from its beginning to its current status. It reviewed 311 relevant articles from 2005 to 2023 using qualitative content analysis [QCA] and meta-analysis to identify common themes and their classification based on pre-determined article criteria. We also identify research gaps within each theme and suggest priority finance areas. Our result suggests that the periodic publications have drastically increased in the past few years, especially after the Paris Agreement in 2015. With content analysis of prior research, most of the research used quantitative and econometric approaches. With the review of papers, it can be concluded that climate finance is mostly constrained in vulnerable regions in which the risk of climate change and its adverse impacts are delicate, including low-lying coastal areas, SIDS, deserts, mountains, and Polar Regions. Innovative climate finance funding should focus on renewable energy, energy efficiency, and infrastructure that aids adaptation in vulnerable communities. Emphasis should be placed on initiatives that provide both mitigation and adaptation advantages, ensuring a resilient and sustainable future. While research primarily focuses on adaptation and mitigation, the interplay between these two areas requires further exploration. We highlight the knowledge gap in this research domain examining the financing sources for mitigation of adverse climate change from private and public sectors.

Thanuja Gelanigama Mesthrige, Prasad Kaparaju

Most nations are shifting towards renewable energy sources to reduce energy-related emissions and achieve their net zero emissions targets by mid-century. Consequently, many attempts have been made to invest in clean, accessible, inexpensive, sustainable and reliable renewable energy sources while reducing dependency on fossil fuels. Recently, the production of biogas and upgrading it to produce biomethane is considered a sustainable way to reduce emissions from natural gas consumption. However, uncertainties in the biomass supply chain and less attention to decarbonising the natural gas grid have led to fewer investors in biomethane injection projects. Thus, researchers have applied Geographic Information System (GIS) as the best decision-making tool with spatial analytical and optimisation capabilities to address this issue. This study aims to review GIS-based applications on planning and optimising the biomass supply chain. Accordingly, this review covers different GIS-based biomass assessment methods with the evaluation of feedstock types, GIS-based approaches on selecting and optimising bioenergy plant locations and GIS-based applications on facilitating biomethane injection projects. This review identified four major biomass assessment approaches: Administrative division-based, location-based, cluster-based and grid-based. Sustainability criteria involved in site selection were also discussed, along with suitability and optimality techniques. Most of the optimising studies investigated cost optimisation based on a single objective. However, optimising the whole supply chain, including all operational components of the biomass supply chain, is still seldom investigated. Furthermore, it was found that most studies focus on site selection and logistics, neglecting biomethane process optimisation.

Sydney Erickson, Martin Millon, Padmavathi Venkatraman et al.

Strongly lensed Active Galactic Nuclei (AGN) with an observable time delay can be used to constrain the expansion history of the Universe through time-delay cosmography (TDC). As the sample of time-delay lenses grows to statistical size, with $\mathcal{O}$(1000) lensed AGN forecast to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), there is an emerging opportunity to use TDC as an independent probe of dark energy. To take advantage of this statistical sample, we implement a scalable hierarchical inference tool which computes the cosmological likelihood for hundreds of strong lenses simultaneously. With this new technique, we investigate the cosmological constraining power from a simulation of the full LSST sample. We start from individual lenses, and emulate the full joint hierarchical TDC analysis, including image-based modeling, time-delay measurement, velocity dispersion measurement, and external convergence prediction. We fully account for the mass-sheet and mass-anisotropy degeneracies. We assume a sample of 800 lenses, with varying levels of follow-up fidelity based on existing campaigns. With our baseline assumptions, within a flexible $w_0w_a$CDM cosmology, we simultaneously forecast a $\sim$2.5% constraint on H0 and a dark energy figure of merit (DE FOM) of 6.7. We show that by expanding the sample from 50 lenses to include an additional 750 lenses with plausible LSST time-delay measurements, we improve the forecasted DE FOM by nearly a factor of 3, demonstrating the value of incorporating this portion of the sample. We also investigate different follow-up campaign strategies, and find significant improvements in the DE FOM with additional stellar kinematics measurements and higher-precision time-delay measurements. We also demonstrate how the redshift configuration of time-delay lenses impacts constraining power in $w_0w_a$CDM.

Allison L. Swiecki-Sikora, Mariel V. Becker, Laura M. Harbin et al.

Climate change is a complex, global issue that is impacting human health in various ways, with healthcare being a significant contributor to carbon emissions in the United States. This review discusses the environmental impact of important aspects of gynecologic oncology care, including surgery, anesthesia care, radiology, chemotherapy, and radiation oncology. Operating room energy and material use is highlighted, with a focus on the environmental impact of robotic surgery. The contribution of certain anesthetic gases in increasing greenhouse gas emissions is addressed. Additionally, the environmental impacts of radiologic imaging, chemotherapy, and radiation oncology are also discussed. Despite the complexity of climate change, there are multiple strategies on the individual and institutional level that can help mitigate the environmental impact of gynecologic oncology care. Individual efforts include practicing red bag stewardship, limiting single use-supplies, decreasing the use of potentially deleterious anesthetics, and supporting research into alternative dosing for chemotherapy and radiation which requires less patient travel. Institutional strategies include investing in efficient HVAC systems, utilizing reusable and reprocessed materials and devices, and purchasing renewable energy sources. Both individuals and institutions can advocate with industry and government at all levels for practices and policies that support lower carbon emissions. By recognizing our role in reducing carbon emissions, we can work towards improving the well-being of our patients and the larger community.