Accessibility of pores in coal to methane and carbon dioxide

Fluid–solid interactions in natural and engineered porous solids underlie a variety of technological processes, including geological storage of anthropogenic greenhouse gases, enhanced coal bed methane recovery, membrane separation, and heterogeneous catalysis. The size, distribution and interconnectivity of pores, the chemical and physical properties of the solid and fluid phases collectively dictate how fluid molecules migrate into and through the micro- and meso-porous media, adsorb and ultimately react with the solid surfaces. Due to the high penetration power and relatively short wavelength of neutrons, smallangle neutron scattering (SANS) as well as ultra small-angle scattering (USANS) techniques are ideally suited for assessing the phase behavior of confined fluids under pressure as well as for evaluating the total porosity in engineered and natural porous systems including coal. Here we demonstrate that SANS and USANS can be also used for determining the fraction of the pore volume that is actually accessible to fluids as a function of pore sizes and study the fraction of inaccessible pores as a function of pore size in three coals from the Illinois Basin (USA) and Bowen Basin (Australia). Experiments were performed at CO2 and methane pressures up to 780 bar, including pressures corresponding to zero average contrast condition (ZAC), which is the pressure where no scattering from the accessible pores occurs. Scattering curves at the ZAC were compared with the scattering from same coals under vacuum and analysed using a newly developed approach that shows that the volume fraction of accessible pores in these coals varies between �90% in the macropore region to �30% in the mesopore region and the variation is distinctive for each of the examined coals. The developed methodology may be also applied for assessing the volume of accessible pores in other natural underground formations of interest for CO2 sequestration, such as saline aquifers as well as for estimating closed porosity in engineered porous solids of technological importance.

Active aging: Exploration into self-ratings of "being active," out-of-home physical activity, and participation among older Australian adults living in four different settings

We examined whether self-ratings of “being active” among older people living in four different settings (major city high and lower density suburbs, a regional city, and a rural area) were associated with out-of-home participation and outdoor physical activity. A mixed-methods approach (survey, travel diary, and GPS tracking over a one-week period) was used to gather data from 48 individuals aged over 55 years. Self-ratings of “being active” were found to be positively correlated with the number of days older people spent time away from home but unrelated to time traveled by active means (walking and biking). No significant differences in active travel were found between the four study locations, despite differences in their respective built environments.The findings suggest that additional strategies to the creation of “age-friendly” environments are needed if older people are to increase their levels of outdoor physical activity. “Active aging” promotion campaigns may need to explicitly identify the benefits of walking outdoors to ambulatory older people as a means of maintaining their overall health, functional ability, and participation within society in the long-term and also encourage the development of community-based programs in order to facilitate regular walking for this group.

Engaging communities to make the big switch

Stepping out on the streets of Townsville, where the sun shines for 300 days a year, you can feel a buzz in the air. But it’s not just the sunshine, booming development or new esplanade that has this North Queensland city excited. There’s a groundswell of green activity as residents embrace ‘Townsville Solar City’ – the only Queensland city participating in the Federal Government’s Solar Cities program. Keen to create a more sustainable future, this community is participating in a range of initiatives led by Ergon Energy and Townsville City Council. These activities aim to reduce energy use, increase solar energy capacity and cut annual greenhouse gas emissions by more than 50 000 tonnes.

An insight into real-time performance assessment of a building integrated photovoltaic (BIPV) installation in Bangalore (India)

Building integrated photovoltaic (BIPV) applications are gaining widespread popularity. The performance of any given BIPV system is dependent on prevalent meteorological factors, site conditions and system characteristics. Investigations pertaining to the performance assessment of photovoltaic (PV) systems are generally confined to either controlled environment-chambers or computer-based simulation studies. Such investigations fall short of providing a realistic insight into how a PV system actually performs real-time. Solar radiation and the PV cell temperature are amongst the most crucial parameters affecting PV output. The current paper deals with the real-time performance assessment of a recently commissioned 5.25 kW, BIPV system installed at the Center for Sustainable Technologies, Indian Institute of Science, Bangalore. The overall average system efficiency was found to be 6% for the period May 2011-April 2012. This paper provides a critical appraisal of PV system performance based on ground realities, particularly characteristic to tropical (moderate) regions such as Bangalore, India. (C) 2013 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Transport properties of CuIn1-xAlxSe2/AZnO heterostructure for low cost thin film photovoltaics

CuIn1-xAlxSe2 (CIASe) thin films were grown by a simple sol-gel route followed by annealing under vacuum. Parameters related to the spin-orbit (Delta(SO)) and crystal field (Delta(CF)) were determined using a quasi-cubic model. Highly oriented (002) aluminum doped (2%) ZnO, 100 nm thin films, were co-sputtered for CuIn1-xAlxSe2/AZnO based solar cells. Barrier height and ideality factor varied from 0.63 eV to 0.51 eV and 1.3186 to 2.095 in the dark and under 1.38 A. M 1.5 solar illumination respectively. Current-voltage characteristics carried out at 300 K were confined to a triangle, exhibiting three limiting conduction mechanisms: Ohms law, trap-filled limit curve and SCLC, with 0.2 V being the cross-over voltage, for a quadratic transition from Ohm's to Child's law. Visible photodetection was demonstrated with a CIASe/AZO photodiode configuration. Photocurrent was enhanced by one order from 3 x 10(-3) A in the dark at 1 V to 3 x 10(-2) A upon 1.38 sun illumination. The optimized photodiode exhibits an external quantum efficiency of over 32% to 10% from 350 to 1100 nm at high intensity 17.99 mW cm(-2) solar illumination. High responsivity R-lambda similar to 920 A W-1, sensitivity S similar to 9.0, specific detectivity D* similar to 3 x 10(14) Jones, make CIASe a potential absorber for enhancing the forthcoming technological applications of photodetection.

Supersolar Ni/Fe production in the Type IIP SN 2012ec

SN 2012ec is a Type IIP supernova (SN) with a progenitor detection and comprehensive photospheric phase observational coverage. Here, we present Very Large Telescope and Public ESO Spectroscopic Survey of Transient Objects observations of this SN in the nebular phase. We model the nebular [O I] lambda lambda 6300, 6364 lines and find their strength to suggest a progenitor main-sequence mass of 13-15 M-circle dot. SN2012ec is unique among hydrogen-rich SNe in showing a distinct line of stable nickel [Ni II] lambda 7378. This line is produced by Ni-58, a nuclear burning ash whose abundance is a sensitive tracer of explosive burning conditions. Using spectral synthesis modelling, we use the relative strengths of [Ni II] lambda 7378 and [Fe II] lambda 7155 (the progenitor of which is Ni-56) to derive a Ni/Fe production ratio of 0.20 +/- 0.07 (by mass), which is a factor 3.4 +/- 1.2 times the solar value. High production of stable nickel is confirmed by a strong [Ni II] 1.939 mu m line. This is the third reported case of a core-collapse SN producing a Ni/Fe ratio far above the solar value, which has implications for core-collapse explosion theory and galactic chemical evolution models.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

Evaluating the use of an urban consolidation centre and electric vehicles in central London

The paper focuses on the role that can be played by urban consolidation centres (UCCs) in reducing freight traffic and its environmental impacts in towns and cities. It is based on the before and after evaluation of a trial led by a major stationery and office supplies company in which urban freight deliveries in central London made from a depot in the suburbs using diesel vehicles were replaced with the use of an urban micro-consolidation centre located in the delivery area together with the use of electrically-assisted cargo tricycles and electric vans. The results show that the total distance travelled and the CO2eq emissions per parcel delivered fell by 20% and 54% respectively as a result of this delivery system. However, the evaluation has also indicated that the distance travelled per parcel rose substantially in the City of London delivery area as a result of the electric vehicles having far smaller load limits in both weight and volume compared with diesel vans. But, at the same time, the trial system was able to virtually eliminate CO2eq emissions per parcel delivered in the City of London. The trial proved successful from the company's perspective in transport, environmental and financial terms. The company therefore decided to continue the operation beyond the end of the trial with it being officially launched during 2010.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

A data-mining based methodology for wind forecasting

In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

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Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Análise do mercado de serviços de regulação de frequência secundária e terciária no sistema eléctrico português

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.