• Energy Research
• 2016-2025close
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This edited volume examines the opportunities to think, do, and/or create jointly afforded by digital storytelling. The contributors discuss digital storytelling in the context of educational programs, teaching anthropology, and ethnographic research involving a variety of populations and subjects that will appeal to researchers and practitioners engaged with qualitative methods and pedagogies that rely on media technology.

Localisation of humanitarian aid has emerged as a major issue after the World Humanitarian Summit in 2016 which emphasised the importance of locally-led response as a corrective to power imbalances in the humanitarian system. However, the practical complexities of localised humanitarian aid are yet to be fully discussed. This paper aims to examine the concept of localisation in humanitarian aid through a case study of a local non-governmental organisation, the Cambodian Children's Trust (CCT), in Cambodia. Drawing on the framework of localisation proposed by Baguios et al., (2021), we analyse the application of localisation of child protection programs run by CCT. We provide a holistic understanding of how localisation is conducted in practice, and the impacts it has on the wider humanitarian sector. Our study illustrates that power can be effectively developed to local entities and localisation with empowerment could be achieved despite highly challenging conditions.

Abstract The effect of the thermal environment on performance and productivity has been a focus of interest among indoor environmental researchers for nearly a century, but most of that work has been conducted in relative isolation from the cognate disciplines of human performance evaluation. The present review examines thermal environmental effects on cognitive performance research conducted across multiple disciplines. After differentiating performance from productivity, we compare the two dominant conceptual models linking thermal stress to performance; (1) the inverted-U concept and (2) the extended-U relationship. The inverted-U specifies a single optimum temperature (or its corresponding subjective thermal sensation) at which performance is maximised. In contrast, the extended-U model posits a broad central plateau across which there is no discernible thermal effect on cognitive performance. This performance plateau is bounded by regions of progressive performance decrements in more extreme thermal conditions. The contradictions between these opposing conceptual models might derive from various confounding factors at play in their underlying research bases. These include, inter alia, environment-related, task-related, and performer-related factors, as well as their associated two-way and three-way interaction effects. Methodological discrepancies that might also contribute to the divergence of these conceptual models are evaluated, along with the proposed causal mechanisms underlying the two models. The weight of research evidence reviewed in this paper suggests that the extended-U hypothesis fits the relationship between moderate thermal environments and cognitive performance. In contrast to the inverted-U relationship, implemention of the extended-U in indoor climate control implies substantial reductions in building energy demand, since it permits the heating and cooling setpoint deadband to expand across the full width of the thermal comfort zone, or even slightly further during emergencies such as peak demand events on the electricity grid. Use of personal comfort systems can further extend the thermostat setpoint range beyond the comfort zone.

In this study, levulinic acid (LA) was produced from rice straw biomass in co-solvent biphasic reactor system consisting of hydrochloric acid and dichloromethane organic solvent. The modified protocol achieved a 15% wt LA yield through the synergistic effect of acid and acidic products (auto-catalysis) and the designed system allowed facile recovery of LA to the organic phase. Further purification of the resulting extractant was achieved through traditional column chromatography, which yielded a high purity LA product while recovering ∼85% wt. Upon charcoal treatment of the resultant fraction generated an industrial grade target molecule of ∼99% purity with ∼95% wt recovery. The system allows the solvent to be easily recovered, in excess of 90%, which was shown to be able to be recycled up to 5 runs without significant loss of final product concentrations. Overall, this system points to a method to significantly reduce manufacturing cost during large-scale LA preparation.

Abstract Newer generation sources and loads are posing new challenges to the conventional power system protection schemes. Adaptive and intelligent protection methodology, based on advanced measurement techniques and intelligent fault diagnosis such as machine learning (ML), is found to be useful to meet these challenges. A large number of research works are reported on ML-based power system fault diagnosis. However, ML techniques are evolving at a very fast pace, and an inclusive, as well as state-of-the-art review on ML-based power system fault diagnosis, is not available in the literature. Given this need and growing trend towards ML, the study presented in this paper aims to provide a comprehensive review of ML-based power system fault diagnosis. At first, efforts have been made to enlist the issues present in conventional fault diagnosis which led to the popularity of ML techniques. Also, a baseline framework and workflow for ML-based fault diagnosis are presented. Next, various unsupervised and supervised learning techniques have been discussed separately which have been used by several researchers for fault diagnosis. The discussion throughout is supported with tabulated facts for fault detection, classification and localization works with techniques used, different simulation tools used, and their application system. The advantages and disadvantages of all the techniques of fault diagnosis have also been discussed which will help the readers in the selection of techniques for their research. A brief review of reinforcement learning and transfer learning is also given as they are gaining popularity in power system-related studies and have the potential to be used for fault diagnosis. Finally, the research trends, some key issues, and directions for future research have been highlighted.

Abstract Fractures along interfaces between host rock and wellbore cement have long been identified as potential CO2 leakage pathways from subsurface CO2 storage sites. As a consequence, cement alteration due to exposure to CO2 has been studied extensively to assess wellbore integrity. Previous studies have focused on the changes to either chemical or mechanical properties of cement upon exposure to CO2-enriched brine, but not on the effects of loading conditions. This paper aims to correct this deficit by considering the combined effects of the fracture pathway and changing effective stress on chemical and mechanical degradation at conditions relevant to geologic carbon storage. Flow-through experiments on fractured cores composed of cement and tight sandstone caprock halves were conducted to study the alteration of cement due to exposure to CO2-enriched brine at 3, 7, 9, and 12 MPa effective stress. We characterized relevant reactions via solution chemistry; fracture permeability via changes to differential pressure; mechanical changes via micro-hardness testing, and pore structure changes via x-ray tomography. This study showed that the nature and the rates of the chemical reactions between cement and CO2 were not affected by the effective stress. The differences in the permeability responses of the fractures were attributed to interactions among the geometry of the flow path, the porosity increase of the reacted cement, and the mechanical deformation of reacted asperities. The suite of observed chemical reactions contributed to change in cement mechanical properties. Compared to the unreacted cement, the average hardness of the amorphous silica and depleted layers was decreased while the hardness of the calcite layer was increased. Tomographic imaging showed that preferential flow paths formed in some of the core-flood experiments, which had a significant impact on the permeability response of the fractured samples. We interpreted the observed permeability responses in terms of competition between dissolution of cement phases (leading to enhanced permeability) and mechanical deformation of reacted regions (leading to reduced permeability).

Abstract The main hindrances to the large-scale development of renewable-energy projects are the lack of bankability and the inability to align investments and investors with suitable financial instruments or robust policy measures. To illustrate a bankable project, this paper presents a research-based case study on the installation of solar photovoltaic panels on the rooftops of 195 trains of the Indian Railways. Detailed information on the annual running hours, exposure to sunlight, efficiency of solar photovoltaic generation and electrical power demands of each rail coach is considered to conduct a quantitative measure of the tentative amount of fossil fuel savings. The purpose is to provide insight into the types of renewable-energy projects that can be highly attractive to financial institutions and promoters due to their lucrative internal return on investment. As seen in this case study, there are annual savings in diesel of 12 323 088 litres and a CO2 reduction of 32 755 tonnes, with return on investment of 1.3 years. Furthermore, this study conducts a comprehensive analysis of the limitations of existing renewable-energy project financing mechanisms in India. Subsequently, three policy measures are recommended to develop a robust financial mechanism that can effectively meet the needs of investors and investors. These measures include increasing equity injection through a buy-and-hold strategy, providing direct tax benefits to promoters and financing through real-estate investment trusts. The findings are highly relevant to address the challenges associated with bridging the financial gap between access to finance and capital investment in the renewable-energy sector, especially for Asian countries.