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French version available in IDRC Digital Library: Kimaki jiko

The South African electricity supply industry (ESI) is dominated by a state-owned and vertically integrated utility, Eskom, which ranks seventh in the world in terms of size and electricity sales; 92% of electricity is generated from coal. Data is presented to provide a snapshot of the current situation (2002). The paper examines the rationale for reform and restructuring of the South African ESI.

This deliverable includes the methodology in EnergyPROSPECTS for an in-depth study of energy citizenship. It features the criteria used for selecting the cases for indepth study, the list of cases selected for in-depth study as well as key research foci and empirical research questions.

Owing to their high luminous efficiency and tunable emission in both red light and far-red light regions, Mn4+ ion-activated phosphors have appealed significant interest in photoelectric and energy conversion devices such as white light emitting diode (W-LED), plant cultivation LED, and temperature thermometer. Up to now, Mn4+ has been widely introduced into the lattices of various inorganic hosts for brightly red-emitting phosphors. However, how to correlate the structure-activity relationship between host framework, luminescence property, and photoelectric device is urgently demanded. In this review, we thoroughly summarize the recent advances of Mn4+ doped phosphors. Meanwhile, several strategies like co-doping and defect passivation for improving Mn4+ emission are also discussed. Most importantly, the relationship between the protocols for tailoring the structures of Mn4+ doped phosphors, increased luminescence performance, and the targeted devices with efficient photoelectric and energy conversion efficiency is deeply correlated. Finally, the challenges and perspectives of Mn4+ doped phosphors for practical applications are anticipated. We cordially anticipate that this review can deliver a deep comprehension of not only Mn4+ luminescence mechanism but also the crystal structure tailoring strategy of phosphors, so as to spur innovative thoughts in designing advanced phosphors and deepening the applications.

A comprehensive model was developed to simulate gasification of pine sawdust in the presence of both air and steam. The proposed model was built upon the premise of an existing Aspen Plus-based biomass gasification model with select improvements. These include the addition of a temperature-dependent pyrolysis model, an updated hydrodynamic model, more extensive gasification kinetics and the inclusion of tar formation and reaction kinetics. The Aspen Plus process simulator was used in combination with a more extensive Fortran subroutine to appropriately model a Bubbling Fluidized Bed (“BFB”) gasifier. The validity of the model was compared on two fronts: Firstly, the accuracy of the model’s predictions in comparison with the actual experimental results; and secondly, the relative accuracy of the model prediction in comparison to the original base-model.

With an ever-growing population, global energy demand increases, thereby contributing to the depletion of fossil resources and their limited reserves. Thereby, to lessen the environmental damage caused by fossil fuels, there has been a surge of interest in developing and producing biofuels from renewable feedstocks, such as microbial lipids. Typically, they are derived via a biochemical process using liquid hydrolysates obtained from forestry residues as a substrate. However, microbial lipid production using hydrolysates presents numerous challenges, including the need for a strain that can accumulate high lipid titers, consume five-carbon sugars (C5), and tolerate inhibitory compounds (e.g., furans, phenols, and organic acids), among others. Out of several microorganisms, Rhodosporidium toruloides, an oleaginous yeast, could be a potential alternative to produce lipids. It is known to accumulate lipids up to 70% of its dry cell weight, use different carbon sources, and tolerate several inhibitory compounds. In this sense, the current thesis explores the ability of Rhodosporidium toruloides as a bio-factory to produce microbial lipids using C5 and C6 wood hydrolysates as a culture media. Different R. toruloides strains were screened, and R. toruloides-1588 was determined to have the highest lipid accumulation of 35%. Following the culture media, carbon to nitrogen ratio, use of lipid inducers, and sugar concentration optimization, the lipid accumulation increased from 35% to 57.14%, with 95% and 80% of glucose and xylose utilization in hydrolysates, respectively. Likewise, palmitic, stearic, and oleic fatty acids were the most prominently on the produced lipids. Finally, R. toruloides-1588 demonstrates the capacity to grow, accumulate lipids, and transform furfural into furfuryl alcohol and 2-furoic acid. The strain was also assessed for its ability to tolerate inhibitory compounds, such as 5-hydroxymethyl furfural, vanillin, syringaldehyde, levulinic acid, ferulic acid, acetic acid, vanillic acid, and ...

"A report prepared to review the wind power potential of Eastern Africa and assess its applicability for waterpumping" ; Photocopy ; The viability of wind power as a means of pumping water in Eastern Africa and Botswana is studied. Discusses the activities of several research groups and evaluates projects in terms of feasibility and implementation. Includes a brief state-of-the-art review of wind development programmes in Europe.

Résumé. Il existe un consensus scientifique sur le fait que la région méditerranéenne (MEDR) se réchauffe et que, à mesure que la température continue d'augmenter, les événements extrêmes tels que les sécheresses et les vagues de chaleur deviennent plus fréquents, plus graves et plus répandus. Compte tenu des effets néfastes des sécheresses, il est crucial d'accélérer le développement de systèmes de prévision et d'alerte précoce afin de minimiser leur impact négatif. Cet article examine l'état actuel des connaissances en matière de modélisation et de prévision de la sécheresse à l'aide de modèles statistiques, dynamiques et hybrides statistiques-dynamiques, et suggère certaines perspectives de recherche pour améliorer davantage la prévision de la sécheresse dans cette région. L'examen révèle que, bien que toutes les méthodes aient leurs forces et leurs faiblesses, les méthodes statistiques et dynamiques hybrides peuvent effectuer la prédiction la plus habile avec un long délai. Cependant, l'application de ces méthodes reste difficile en raison du manque de données d'observation de haute qualité et des ressources informatiques limitées. Enfin, l'article conclut en discutant de l'importance d'utiliser une combinaison de méthodes sophistiquées telles que les techniques d'assimilation de données, les modèles d'apprentissage automatique et les modèles de copules et d'intégrer des données provenant de différentes sources (par exemple, les données de télédétection, les mesures in situ et la réanalyse) pour améliorer la précision et l'efficacité des prévisions de sécheresse. Resumen. Existe un consenso científico de que la región mediterránea (MEDR) se está calentando y, a medida que la temperatura continúa aumentando, los eventos extremos como las sequías y las olas de calor se están volviendo más frecuentes, severos y generalizados. Dados los efectos perjudiciales de las sequías, es crucial acelerar el desarrollo de sistemas de pronóstico y alerta temprana para minimizar su impacto negativo. Este documento examina el estado actual del conocimiento en el modelado y la predicción de la sequía utilizando modelos estadísticos, dinámicos e híbridos estadístico-dinámicos, y sugiere algunas perspectivas de investigación para mejorar aún más la predicción de la sequía en esta región. La revisión encuentra que, si bien todos los métodos tienen sus fortalezas y deficiencias, los métodos estadístico-dinámicos híbridos pueden realizar la predicción más hábil con un largo tiempo de espera. Sin embargo, la aplicación de estos métodos sigue siendo un desafío debido a la falta de datos observacionales de alta calidad y a los limitados recursos computacionales. Finalmente, el documento concluye discutiendo la importancia de usar una combinación de métodos sofisticados como técnicas de asimilación de datos, modelos de aprendizaje automático y modelos de cópula e integrar datos de diferentes fuentes (por ejemplo, datos de teledetección, mediciones in situ y reanálisis) para mejorar la precisión y eficiencia del pronóstico de sequías. Abstract. There is a scientific consensus that the Mediterranean region (MEDR) is warming and as the temperature continues to rise, extreme events such as droughts and heat waves are becoming more frequent, severe, and widespread. Given the detrimental effects of droughts, it is crucial to accelerate the development of forecasting and early warning systems to minimize their negative impact. This paper examines the current state of knowledge in drought modeling and prediction using statistical, dynamical, and hybrid statistical-dynamical models, and suggests some research prospects to further improve drought prediction in this region. The review finds that while all methods have their strengths and shortcomings, hybrid statistical-dynamical methods can perform the most skillful prediction with a long lead time. However, the application of these methods is still challenging due to the lack of high-quality observational data and the limited computational resources. Finally, the paper concludes by discussing the importance of using a combination of sophisticated methods such as data assimilation techniques, machine learning models, and copula models and integrating data from different sources (e.g., remote sensing data, in-situ measurements, and reanalysis) to improve the accuracy and efficiency of drought forecasting. الخلاصة. هناك إجماع علمي على أن منطقة البحر الأبيض المتوسط (MEDR) ترتفع درجة حرارتها ومع استمرار ارتفاع درجة الحرارة، أصبحت الأحداث المتطرفة مثل الجفاف وموجات الحرارة أكثر تكرارًا وشدة وانتشارًا. بالنظر إلى الآثار الضارة للجفاف، من الأهمية بمكان تسريع تطوير أنظمة التنبؤ والإنذار المبكر لتقليل تأثيرها السلبي. تبحث هذه الورقة في الحالة الراهنة للمعرفة في نمذجة الجفاف والتنبؤ به باستخدام النماذج الإحصائية والديناميكية والهجينة، وتقترح بعض آفاق البحث لزيادة تحسين التنبؤ بالجفاف في هذه المنطقة. وجدت المراجعة أنه في حين أن جميع الأساليب لها نقاط قوتها وعيوبها، فإن الأساليب الإحصائية الديناميكية الهجينة يمكن أن تؤدي التنبؤ الأكثر مهارة مع مهلة زمنية طويلة. ومع ذلك، لا يزال تطبيق هذه الأساليب يمثل تحديًا بسبب نقص بيانات المراقبة عالية الجودة ومحدودية الموارد الحسابية. أخيرًا، تختتم الورقة بمناقشة أهمية استخدام مجموعة من الأساليب المتطورة مثل تقنيات استيعاب البيانات ونماذج التعلم الآلي ونماذج الكوبولا ودمج البيانات من مصادر مختلفة (على سبيل المثال، بيانات الاستشعار عن بعد والقياسات في الموقع وإعادة التحليل) لتحسين دقة وكفاءة التنبؤ بالجفاف.

The recent trend of increasing share of renewable energy sources (RES) in the generation mix has necessitated new operational and planning studies because of the high degree of uncertainty and variability of these sources. RES such as solar photovoltaic and wind generation are not dispatchable, and when there is excess energy supply during off-peak hours, RES curtailment is required to maintain the demand-supply balance. Furthermore, RES are intermittent resources which have introduced new challenges to the provision of ancillary services that are critical to maintaining the operational reliability of power systems. Energy storage systems (ESS) play a pivotal role in facilitating the integration of RES to mitigate the aforementioned issues. Therefore, there is a growing interest in recent years to examine the potential of ESS in the future electricity grids. This research focuses on developing market participation and investment planning frameworks for ESS considering different ownership structures. First, a novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and year of installation in an isolated microgrid using a novel representation of the BESS energy diagram. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value of total expected costs over a multi-year horizon considering optimal BESS operation using a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed integer linear programming (MILP) problems; the optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed approach. The thesis further studies the ...

Introduction: Wind turbines are a source of renewable energy that has become more common in Canada in the past decades. Concerns have been raised over potential adverse health effects from exposure to wind turbines, particularly wind turbine noise. A disagreement exists over the potential harm from exposure to wind turbines to human health, where many public health organizations state that there are no direct human health impacts from wind turbine exposure, while many community groups state that wind turbines are harmful to human health. Objectives: 1. Determine the types of evidence cited by community group websites, and by public health organization websites, to support their respective positions on the potential health effects of wind turbines; and 2. Assess the pattern of citations or links to the evidence used by community groups and public health organizations to characterize and interpret these patterns of evidence citation and to see whether and how these patterns differ between the two groups. Methods: Websites of Canadian community groups, public health organizations, environmental non-governmental organizations (eNGOs) and academic organizations were identified using an Internet search strategy. The identified websites with content on wind turbines and human health that met the inclusion criteria were characterised with a data collection tool to gather information about the webpage structure and its links to evidence sources and other organizations’ websites. Descriptive statistical analysis was performed on the website characteristics and evidence and organization citation data. Testing for significant differences between community groups and public health organizations was done using t-tests and chi-squared tests. Adjacency matrices were created to represent the presence of ties between organization websites and between organization websites and evidence sources. Graphs (sociograms) were created based on the adjacency matrices to visualise the relationship between the different types of ...