Solar Assisted Fast Pyrolysis: A Novel Approach of Renewable Energy Production

Biofuel produced by fast pyrolysis from biomass is a promising candidate. The heart of the system is a reactor which is directly or indirectly heated to approximately 500°C by exhaust gases from a combustor that burns pyrolysis gas and some of the by-product char. In most of the cases, external biomass heater is used as heating source of the system while internal electrical heating is recently implemented as source of reactor heating. However, this heating system causes biomass or other conventional forms of fuel consumption to produce renewable energy and contributes to environmental pollution. In order to overcome these, the feasibility of incorporating solar energy with fast pyrolysis has been investigated. The main advantages of solar reactor heating include renewable source of energy, comparatively simpler devices, and no environmental pollution. A lab scale pyrolysis setup has been examined along with 1.2 m diameter parabolic reflector concentrator that provides hot exhaust gas up to 162°C. The study shows that about 32.4% carbon dioxide (CO2) emissions and almost one-third portion of fuel cost are reduced by incorporating solar heating system. Successful implementation of this proposed solar assisted pyrolysis would open a prospective window of renewable energy.

Autonomous vehicle path planning for persistence monitoring under uncertainty using Gaussian based Markov decision process

One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

A framework for understanding and generating integrated solutions for residential peak energy demand

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Financially optimized scheduling of electric energy storage in presence of renewable energy resources

The increasing integration of Renewable Energy Resources (RER) and the role of Electric Energy Storage (EES) in distribution systems has created interest in using energy management strategies. EES has become a suitable resource to manage energy consumption and generation in smart grid. Optimize scheduling of EES can also maximize retailer’s profit by introducing energy time-shift opportunities. This paper proposes a new strategy for scheduling EES in order to reduce the impact of electricity market price and load uncertainty on retailers’ profit. The proposed strategy optimizes the cost of purchasing energy with the objective of minimizing surplus energy cost in hedging contract. A case study is provided to demonstrate the impact of the proposed strategy on retailers’ financial benefit.

Measuring sustainability performance within the Australian energy industry

Sustainability has become crucial for the energy industry as projects in this industry are extensively large and complex and have significant impacts on the environment, community and economy. It demands the energy industry to proactively incorporate sustainability ideas and commit to sustainable project development. This study aims to investigate how the Australian energy industry responds to sustainability requirements and in particular what indicators used to measure sustainability performance. To achieve this, content analysis of sustainability reports, vision statements and policy statements of Australian energy companies listed in the 2013 PLATTS Top 250 Global Energy Company Rankings and government reports relating to sustainability has been conducted. The findings show that the energy companies extensively discuss sustainability aspects within three dimensions, i.e. community, environment, and economy. Their primary goals in sustainability are supplying cleaner energy for future, and doing business in a way that improves outcomes for shareholders, employees, business partners and the communities. In particular, energy companies have valued the employees of the business as a one of the key area that needs to be considered. Furthermore, the energy industry has become increasingly aware of the importance of measuring sustainability performance to achieve sustainability goals. A number of sustainability indicators have been developed on the basis of the key themes beyond economic measures. It is envisaged that findings from this research will help stakeholders in the energy industry to adopt different indicators to evaluate and ultimately achieve sustainability performance.

Development of a switch mode assisted linear amplifier for use as a high fidelity voltage source

Frequency Domain Spectroscopy (FDS) is one of the major techniques used for determining the condition of the cellulose based paper and pressboard components in large oil/paper insulated power transformers. This technique typically makes use of a sinusoidal voltage source swept from 0.1 mHz to 1 kHz. The excitation test voltage source used must meet certain characteristics, such as high output voltage, high fidelity, low noise and low harmonic content. The amplifier used; in the test voltage source; must be able to drive highly capacitive loads. This paper proposes that a switch-mode assisted linear amplifier (SMALA) can be used in the test voltage source to meet these criteria. A three level SMALA prototype amplifier was built to experimentally demonstrate the effectiveness of this proposal. The developed SMALA prototype shows no discernable harmonic distortion in the output voltage waveform, or the need for output filters, and is therefore seen as a preferable option to pulse width modulated digital amplifiers. The lack of harmonic distortion and high frequency switching noise in the output voltage of this SMALA prototype demonstrates its feasibility for applications in FDS, particularly on highly capacitive test objects such as transformer insulation systems.

Polybrominated diphenyl ethers (PBDEs) in dust from primary schools in South East Queensland, Australia

PBDE concentrations are higher in children compared to adults with exposure suggested to include dust ingestion. Besides the home environment, children spend a great deal of time in school classrooms which may be a source of exposure. As part of the “Ultrafine Particles from Traffic Emissions and Children's Health (UPTECH)” project, dust samples (n=28) were obtained in 2011/12 from 10 Brisbane, Australia metropolitan schools and analysed using GC and LC–MS for polybrominated diphenyl ethers (PBDEs) -17, -28, -47, -49, -66, -85, -99, -100, -154, -183, and -209. Σ11PBDEs ranged from 11–2163 ng/g dust; with a mean and median of 600 and 469 ng/g dust, respectively. BDE-209 (range n.d. −2034 ng/g dust; mean (median) 402 (217) ng/g dust) was the dominant congener in most classrooms. Frequencies of detection were 96%, 96%, 39% and 93% for BDE-47, -99, -100 and -209, respectively. No seasonal variations were apparent and from each of the two schools where XRF measurements were carried out, only two classroom items had detectable bromine. PBDE intake for 8–11 year olds can be estimated at 0.094 ng/day BDE-47; 0.187 ng/day BDE-99 and 0.522 ng/day BDE-209 as a result of ingestion of classroom dust, based on mean PBDE concentrations. The 97.5% percentile intake is estimated to be 0.62, 1.03 and 2.14 ng/day for BDEs-47, -99 and -209, respectively. These PBDE concentrations in dust from classrooms, which are higher than in Australian homes, may explain some of the higher body burden of PBDEs in children compared to adults when taking into consideration age-dependant behaviours which increase dust ingestion.

Energy gap in the aetiology of body weight gain and obesity: A challenging concept with a complex evaluation and pitfalls

The concept of energy gap(s) is useful for understanding the consequence of a small daily, weekly, or monthly positive energy balance and the inconspicuous shift in weight gain ultimately leading to overweight and obesity. Energy gap is a dynamic concept: an initial positive energy gap incurred via an increase in energy intake (or a decrease in physical activity) is not constant, may fade out with time if the initial conditions are maintained, and depends on the 'efficiency' with which the readjustment of the energy imbalance gap occurs with time. The metabolic response to an energy imbalance gap and the magnitude of the energy gap(s) can be estimated by at least two methods, i.e. i) assessment by longitudinal overfeeding studies, imposing (by design) an initial positive energy imbalance gap; ii) retrospective assessment based on epidemiological surveys, whereby the accumulated endogenous energy storage per unit of time is calculated from the change in body weight and body composition. In order to illustrate the difficulty of accurately assessing an energy gap we have used, as an illustrative example, a recent epidemiological study which tracked changes in total energy intake (estimated by gross food availability) and body weight over 3 decades in the US, combined with total energy expenditure prediction from body weight using doubly labelled water data. At the population level, the study attempted to assess the cause of the energy gap purported to be entirely due to increased food intake. Based on an estimate of change in energy intake judged to be more reliable (i.e. in the same study population) and together with calculations of simple energetic indices, our analysis suggests that conclusions about the fundamental causes of obesity development in a population (excess intake vs. low physical activity or both) is clouded by a high level of uncertainty.

Removal of organic content from diesel exhaust particles alters cellular responses of primary human bronchial epithelial cells cultured at an air-liquid interface

Background Exposure to air pollutants, including diesel particulate matter, has been linked to adverse respiratory health effects. Inhaled diesel particulate matter contains adsorbed organic compounds. It is not clear whether the adsorbed organics or the residual components are more deleterious to airway cells. Using a physiologically relevant model, we investigated the role of diesel organic content on mediating cellular responses of primary human bronchial epithelial cells (HBECs) cultured at an air-liquid interface (ALI). Methods Primary HBECs were cultured and differentiated at ALI for at least 28 days. To determine which component is most harmful, we compared primary HBEC responses elicited by residual (with organics removed) diesel emissions (DE) to those elicited by neat (unmodified) DE for 30 and 60 minutes at ALI, with cigarette smoke condensate (CSC) as the positive control, and filtered air as negative control. Cell viability (WST-1 cell proliferation assay), inflammation (TNF-α, IL-6 and IL-8 ELISA) and changes in gene expression (qRT-PCR for HO-1, CYP1A1, TNF-α and IL-8 mRNA) were measured. Results Immunofluorescence and cytological staining confirmed the mucociliary phenotype of primary HBECs differentiated at ALI. Neat DE caused a comparable reduction in cell viability at 30 or 60 min exposures, whereas residual DE caused a greater reduction at 60 min. When corrected for cell viability, cytokine protein secretion for TNF-α, IL-6 and IL-8 were maximal with residual DE at 60 min. mRNA expression for HO-1, CYP1A1, TNF-α and IL-8 was not significantly different between exposures. Conclusion This study provides new insights into epithelial cell responses to diesel emissions using a physiologically relevant aerosol exposure model. Both the organic content and residual components of diesel emissions play an important role in determining bronchial epithelial cell response in vitro. Future studies should be directed at testing potentially useful interventions against the adverse health effects of air pollution exposure.

Characterisation, toxicity and source apportionment of atmospheric organic pollutants in urban schools

Airborne organic pollutants have significant impacts on health; however their sources, atmospheric characteristics and resulting human exposures are poorly understood. This research characterized chemical composition of atmospheric volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyls in representative number of primary schools in Brisbane Metropolitan Area, quantified their concentrations, assessed their toxicity and apportioned them to their sources. The findings expand scientific knowledge of these pollutants, and will contribute towards science based management of risks associated with pollution emissions and air quality in schools and other urban and indoor environments.

Energy-Efficient Decentralized Cooperative Routing in Wireless Networks

Wireless adhoc networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem - the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node. In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels, where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information (CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a c- - orresponding factored class of control poli.

Analysis Of The Energy Quantization Effects On Single Electron Inverter Performance Through Noise Margin Modeling

Possible integration of Single Electron Transistor (SET) with CMOS technology is making the study of semiconductor SET more important than the metallic SET and consequently, the study of energy quantization effects on semiconductor SET devices and circuits is gaining significance. In this paper, for the first time, the effects of energy quantization on SET inverter performance are examined through analytical modeling and Monte Carlo simulations. It is observed that the primary effect of energy quantization is to change the Coulomb Blockade region and drain current of SET devices and as a result affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. It is shown that SET inverter designed with CT : CG = 1/3 (where CT and CG are tunnel junction and gate capacitances respectively) offers maximum robustness against energy quantization.

LISA as a dark energy probe

Recently, it has been shown that the inclusion of higher signal harmonics in the inspiral signals of binary supermassive black holes (SMBH) leads to dramatic improvements in the parameter estimation with Laser Interferometer Space Antenna (LISA). In particular, the angular resolution becomes good enough to identify the host galaxy or galaxy cluster, in which case the redshift can be determined by electromagnetic means. The gravitational wave signal also provides the luminosity distance with high accuracy, and the relationship between this and the redshift depends sensitively on the cosmological parameters, such as the equation-of-state parameter w = p(DE)/rho(DE) of dark energy. Using binary SMBH events at z < 1 with appropriate masses and orientations, one would be able to constrain w to within a few per cent. We show that, if the measured sky location is folded into the error analysis, the uncertainty on w goes down by an additional factor of 2-3, leaving weak lensing as the only limiting factor in using LISA as a dark energy probe.