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[en] Highlights: • Smart energy systems are investigated to address major energy issues in a sustainable manner. • Evaluation criteria are efficiencies, environmental performance, and energy and material sources. • Energy sources are fossil fuels, renewables, biomass, and nuclear. - Abstract: In this study, smart energy systems are investigated and comparatively assessed to solve major global energy-related issues in a sustainable manner. In order to be considered as smart and sustainable, the energy systems should use technologies and resources that are adequate, affordable, clean, and reliable. Therefore, selected smart energy systems are evaluated based on their efficiencies, environmental performance, and energy and material sources. Our results show that increasing the number of products from the same energy source decreases emissions per unit product and increases efficiencies. Also, among the identified sources, geothermal has the most potential in terms of using cleaner technologies with energy conservation, renewability and the possibility of multiple desired products from the same source. Solar, hydro, and biomass are also beneficial. Even with carbon capture technologies, fossil fuels are not very desirable in smart energy systems because of their emissions and non-renewability.
[en] Highlights: • A big proportion of the population uses biomass instead of cleaner fuels for cooking. • We use a structural model to estimate household demand and choices for cooking fuels. • Higher incomes and lower differences in prices increase the use of cleaner options. - Abstract: Access to cleaning cooking fuels and stoves is an important indicator of well-being, as this enables several improvements in quality of life. In many developing countries, a big proportion of the population still depends on biomass for cooking, and the adoption of clean cooking fuels is still limited. Here, we propose a structural model to estimate household demand and choices for cooking fuel using micro-datasets from nationally representative surveys for a subset of developing countries. We test the model by estimating the demand response to simulated changes in fuel prices and income. We find that the model provides a close approximation to the observed patterns in the data from the surveys. We also find that as long as incomes rise and the relative difference between the prices of biomass and cleaner fuels decreases, households will transition to cleaner cooking fuels. We discuss potential applications of the method for constructing and analyzing future scenarios of cooking energy transitions.
[en] Highlights: • No need to generate scenarios and to solve complex LP problems. • Test the effectiveness of the strategy with real world data. • Utilize advanced forecasting techniques. • Incorporate valuable market information to help WPPs bid to the short-term market. - Abstract: This paper presents an analytical trading electricity model for wind power producers (WPPs) in the short-term electricity market in the U.S. This model addresses four specific uncertainties: real-time (RT) wind power generation, day-ahead (DA) locational marginal prices (LMPs), RT LMPs, and deviation penalty rates. The model is designed to find the optimal bidding strategy to maximize the expected revenue under these uncertainties. In addition, this paper shows that advanced forecasting techniques could be used with the proposed bidding strategy to help WPPs trade energy in short-term markets. A case study is presented to illustrate the effectiveness of this proposed bidding strategy and advanced forecasting techniques using a set of real data taken from a wind farm in the PJM electricity market.
[en] This preliminary study investigated data mining-based methods to assess and predict the performance of geothermal heat pump(GHP) system. Data mining is a key process of the knowledge discovery in database (KDD), which includes five steps: 1) Selection; 2) Pre-processing; 3) Transformation; 4) Analysis(data mining); and 5) Interpretation/Evaluation. We used two analysis models, categorical and numerical decision tree models to ascertain the patterns of performance(COP) and electrical consumption of the GHP system. Prior to applying the decision tree models, we statistically analyzed measurement database to determine the effect of sampling intervals on the system performance. Analysis results showed that 10-min sampling data for the performance analysis had highest accuracy of 97.7% over the actual dataset of the GHP system.
[en] The pattern shown by dasometric variables was analyzed with tree biomass to estimate it by using data from two tropical forests in Costa Rica. Four possible models that estimate biomass in tropical forests were identified through a bibliographic review. 907 trees with diameter at breast height (dbh) greater than 10 cm were evaluated. Dasometric variables (wood density, total height and dbh) were used to analyze their relationship with biomass in order to finding a model that could predict it. The dbh and density were used as independent variables in the final model. A segmented regression technique (due to the relationship between the dap and the total height with the transformed biomass variable) and weighted mean squares to solve the heterocedasticity problem were used to estimate this model. The statistical assumptions of a general linear regression were evaluated by the behavior of the residuals and other parametric tests. A coefficient of determination of 0.992 was obtained. A methodological approach was proposed to estimate biomass at a general level in forests
[es]Un analisis del comportamiento de las variables dasometricas facilmente medibles fue realizado para predecir biomasa arborea con datos de dos bosques tropicales de Costa Rica. Cuatro posibles modelos que estiman biomasa en bosques tropicales fueron determinados mediante una revision bibliografica. 907 arboles con diametro a la altura de pecho (dap) mayor a 10 cm fueron evaluados. Un analisis de las variables de los arboles (densidad especifica de la madera, altura total y dap) y su biomasa fue realizado con el fin de desarrollar el modelo que facilitara la prediccion de esta. El dap y la densidad fueron utilizados como variables independientes en el modelo final. Una regresion segmentada (por la relacion que tienen el dap y la altura total con la variable biomasa transformada) y cuadrados medios ponderados para resolver el problema de heterocedasticidad fueron utilizados para la estimacion de este modelo. Los supuestos estadisticos de una regresion lineal general fueron evaluados por el comportamiento de los residuos y otras pruebas parametricas. Un coeficiente de determinacion de 0,992 fue obtenido. Un enfoque metodologico fue propuesto para estimar la biomasa a nivel general en los bosques
[en] Agarwood is the resinous product of several tree species of family Thymelaeaceae such as Aquilaria spp. Unsustainable harvesting has threatened the existence of agarwood producing species in their natural habitat. Therefore, the present study was developed to facilitate an effective and efficient method to produce Aquilaria malaccensis seedlings by In vitro culture. Here, we optimized the aeration rate in the bubble column reactor and the immersion time on the temporary immersion system (TIS)-RITA® bioreactor and compare the growth rate of A. malaccensis with both systems. A. malaccensis shoot cultures were propagated in Murashige and Skoog (MS) semisolid medium and then pre-conditioned in thin layer culture before bioreactor cultivation. A. malaccensis shoots in the bubble column reactor were subjected to variable aeration rates of 0.05 and 0.1 vvm, while the immersion variation within the TIS-RITA® bioreactor was 5 and 15 min for every 4 h. The results showed that 15 min immersion for every 4 h increased the number of A. malaccensis shoot regeneration. Nonetheless, no significance difference was observed on biomass acquisition in both bubble column bioreactor and TIS-RITA® bioreactor. Therefore, our findings indicate that immersion period was more critical than aeration rate for A. malaccensis shoot cultivation. (author)
[en] India faces a major challenge in providing a long-term energy security needed for meeting the aspirations of her growing population and, at the same time, in fulfilling her commitments for preventing generation of greenhouse gases. Use of non-fossil energy sources is the solution. There is a need for making a right balance of generation of energy from sources such as solar and wind which are, by nature, distributed and intermittent and from nuclear which is concentrated and continuous. It will be highlighted in this presentation how the solar and nuclear energy – the two primary energy sources can complement each other in supplying energy in a sustainable manner
[en] Aim of the study: The aim of the study was to assess the seasonal dynamics of microbial biomass and its contribution to soil system along a fragment size gradient in subtropical humid forest of Meghalaya. Area of study: The study was conducted in forest fragments located at Jarain and adjoining areas in Jaintia Hills of Meghalaya, northeast India. Material and Methods: Forest fragments of sizes ranging from 3.8 to 105 ha were selected for the study and grouped into Small (< 5 ha), Medium (> 5 and < 15 ha), Large (>15 and < 50 ha) and Very Large (105 ha) classes. Three experimental plots each of 20 x 20 m were established at the forest edge and at 50 m distance assigned as ‘interior’ microsite in each of the fragments for sampling of soil. Soil samples (0-10 cm depth) from each of the experimental plots were collected in replicates on seasonal interval and microbial biomass was estimated by the fumigation extraction method. Important findings: Microbial biomass- C, -N and -P varied significantly (p< 0.05) between the fragment sizes, microsites and seasons. The microbial biomass was higher in the interior as compared to the edge. It was also high during the winter season. Overall, soil microbial biomass -C, -N and -P ranged from 260 to 969; 25 to 95 and 8 to 67 µg g-1 respectively. The contribution of microbial biomass -C, -N and -P to soil organic carbon, total Kjeldahl nitrogen and phosphorus ranged from 1.48 to 1.81 %, 2.54 to 4.54 % and 3.41 to 5.22 % respectively. Fragmentation alters the microenvironmental conditions and soil properties that in turn affect the microbial biomass. Highlights: This interaction of plant, soil and microbial community would gradually degrade in the fragments due to change in vegetation composition and structure, microclimatic conditions and soil physical and chemical properties. Our results suggests that microbial mediated ecosystem processes such as nutrient cycling are more susceptible to variation at the edge which may become unstable and unpredictable in forest fragments exposed to various human disturbances.
[en] Nitrogen concentration is an essential parameter in cyanobacterial cultures to produce enriched biomass with biotechnological purposes. Growth and biochemical composition of Nostoc LAUN0015, Nostoc UAM206, Anabaenasp.1 and Anabaena sp.2 were compared at 0, 4.25, 8.5 and 17 mM NaNO3. Cultures under laboratory conditions were maintained for 30 days at a volume of 500 mL. Anabaena sp.1 yielded the highest value of dry mass of 0.26 ± 2.49 mg mL-1 at 8.5 mM NaNO3. For chlorophyll, phycocyanin and phycoerythrins, maximum values were achieved at 17 mm NaNO3 with 18.09 ± 1.74, 102.90 ± 6.73 and 53.47 ± 2.40 ?g mL-1, respectively. Nostoc LAUN0015 produced its maximum value of protein 644.86 ± 19.77 mug mL-1, and 890 mg mL-1 of carbohydrates in the absence of nitrogen. This comparative study shows that the most efficient strain for the production of protein, carbohydrates and lipids in diazotrophic conditions corresponded to Nostoc LAUN0015. However, Anabaena sp.1 and Anabaena sp.2 required high nitrogen concentrations to achieve higher values of metabolites, comparing with Nostoc strains. Nitrogen dependence for the production of pigments and high protein production in strains of Anabaena and in diazotrophic conditions for Nostoc was demonstrated. Nostoc can be cultured under nitrogen deficiency and Anabaena in sufficiency, for biomass production enriched with proteins and carbohydrates.