A typology of community opportunity and vulnerability in metropolitan Australia

A multivariate model using hierarchical clustering and discriminant analysis is used to identify clusters of community opportunity and community vulnerability across Australia's mega metropolitan regions, Variables used in the model measure aspects of structural economic change, occupational change, human capital, income, unemployment, family/household disadvantage, and housing stress. A nine-cluster solution is used to categorise communities across metropolitan space. Significant between-city variations in the incidence of these clusters of opportunity and vulnerability are apparent, suggesting the emergence of marked differentiation between Australia's mega metropolitan regions in their adjustments to changing economic and social conditions. JEL classification: C49, R11, R12.

Globalization and women in southeast Asian higher education management

This paper draws on data from a group case study of women in higher education management in Hong Kong, Singapore, Malaysia, and Thailand. I investigate culture-specific dimensions of what the Western literature has conceptualized as glass ceiling impediments to women's career advancement in higher education. I frame my argument within recent debates about globalization and glocalization to show how the push-pull and disjunctive dynamics of globalization are experienced in local sites by social actors who traverse global flows and yet remain tethered to local discourses, values, and practices. All of the women in this study were trained in Western universities and are fluent English speakers, world-class experts in their fields, well versed with equity discourses, and globally connected on international nongovernment organization (NGO) and academic circuits. They are indeed global cosmopolitans. And yet their testimonies indicate that so-called Asian values and religious-cultural ideologies demand the enactment of a specific construct of Asian femininity that militates against meritocratic equality and academic career aspirations to senior management levels. Despite the global nature of the University and increasing global flows of academics, students, and knowledge, the politics of academic glass ceilings are not universal but always locally inflected with cultural values and norms. As such, the politics of disadvantage for women in higher education require local and situated analyses in the context of global patterns of the educational status Of women and the changing nature of higher education.

Production of the baculovirus-expressed dengue virus glycoprotein NS1 can be improved dramatically with optimised regimes for fed-batch cultures and the addition of the insect moulting hormone, 20-Hydroxyecdysone

A perennial problem in recombinant protein expression is low yield of the product of interest. A strategy which has been shown to increase the production of baculovirus-expressed proteins is to utilise fed-batch cultures. One disadvantage of this approach is the time-consuming task of optimising the feeding strategy. Previously, a statistical optimisation routine was applied to develop a feeding strategy that increased the yield of beta-Galactosidase (beta-Gal) by 2.4-fold (Biotechnol. Bioeng, 59 (1998) 178). This involves the single addition of nutrient concentrates (amino acids, lipids. glucose and yeastolate ultrafiltrate) into Sf9 cell cultures grown in SF900II medium. In this study, it is demonstrated that this optimised fed-batch strategy developed for a high-yielding intracellular product beta-Gal could be applied successfully to a relatively low-yielding glycosylated and secreted product such as the dengue virus glycoprotein NS1. Optimised batch infections yielded 4 mug/ml of NS1 at a peak cell density of 4.2 x 10(6) cells/ml. In contrast. optimised fed-batch infections exhibited a 3-fold improvement in yield, with 12 mug ml of NS1 produced at a peak cell density of 11.3 x 10(6) cells/ml. No further improvements in yield were recorded when the feed volumes were doubled and the peak cell density was increased to 23 x 10(6) cells/ml, unless the cultures were stimulated by the addition of 4 mug/ml of 20-Hydroxyecdysone (an insect moulting hormone). In this case, the NS1 yield was increased to 20 mug/ml. which was nearly 5-fold higher than optimised batch cultures. (C) 2002 Elsevier Science B.V. All rights reserved.

Dinoflagellate symbiosis: strategies and adaptations for the aquisition and fixation of inorganic carbon

Dinoflagellates exist in symbiosis with a number of marine invertebrates including giant clams, which are the largest of these symbiotic organisms. The dinoflagellates (Symbiodinium sp.) live intercellularly within tubules in the mantle of the host clam. The transport of inorganic carbon (Ci) from seawater to Symbiodinium (=zooxanthellae) is an essential function of hosts that derive the majority of their respiratory energy from the photosynthate exported by the zooxanthellae. Immunolocalisation studies show that the host has adapted its physiology to acquire, rather than remove CO2, from the haemolymph and clam tissues. Two carbonic anhydrase (CA) isoforms (32 and 70 kDa) play an essential part in this process. These have been localised to the mantle and gill tissues where they catalyse the interconversion of HCO3- to CO2, which then diffuses into the host tissues. The zooxanthellae exhibit a number of strategies to maximise Ci acquisition and utilisation. This is necessary as they express a form II Rubisco that has poor discrimination between CO2 and O-2. Evidence is presented for a carbon concentrating mechanism (CCM) to overcome. this disadvantage. The CCM incorporates the presence of a light-activated CA activity, a capacity to take up both HCO3- and CO2, an ability to accumulate an elevated concentration of Ci within the algal cell, and localisation of Rubisco to the pyrenoid. These algae also express both external and intracellular CAs, with the intracellular isoforms being localised to the thylakoid lumen and pyrenoid. These results have been incorporated into a model that explains the transport of Ci from seawater through the clam to the zooxanthellae.

The JK three-product cyclone - performance and potential applications

In spite of their wide application in comminution circuits, hydrocyclones have at least one significant disadvantage in that their operation inherently tends to return the fine denser liberated minerals to the grinding mill. This results in unnecessary overgrinding which adds to the milling cost and can adversely affect the efficiency of downstream processes. In an attempt to solve this problem, a three-product cyclone has been developed at the Julius Kruttschnitt Mineral Research Centre (JKMRC) to generate a second overflow in which the fine dense liberated minerals can be selectively concentrated for further treatment. In this paper, the design and operation of the three-product cyclone are described. The influence of the length of the second vortex finder on the performance of a 150-mm unit treating a mixture of magnetite and silica is investigated. Conventional cyclone tests were also conducted under similar conditions. Using the operational performance data of the three-product and conventional cyclones, it is shown that by optimising the length of the second vortex finder, the amount of fine dense mineral particles that reports to the three-product cyclone underflow can be reduced. In addition, the three-product cyclone can be used to generate middlings stream that may be more suitable for flash flotation than the conventional cyclone underflow, or alternatively, could be classified with a microscreen to separate the valuables from the gangue. At the same time, a fines stream having similar properties to those of the conventional overflow can be obtained. Hence, if the middlings stream was used as feed for flash flotation or microscreening, the fines stream could be used in lieu of the conventional overflow without compromising the feed requirements for the conventional flotation circuit. Some of the other potential applications of the new cyclone are described. (C) 2003 Elsevier Science B.V. All rights reserved.

Model-based analysis of anaerobic acetate uptake by a mixed culture of polyphosphate-accumulating and glycogen-accumulating organisms

An increasing number of studies shows that the glycogen-accumulating organisms (GAOs) can survive and may indeed proliferate under the alternating anaerobic/aerobic conditions found in EBPR systems, thus forming a strong competitor of the polyphosphate-accumulating organisms (PAOs). Understanding their behaviors in a mixed PAO and GAO culture under various operational conditions is essential for developing operating strategies that disadvantage the growth of this group of unwanted organisms. A model-based data analysis method is developed in this paper for the study of the anaerobic PAO and GAO activities in a mixed PAO and GAO culture. The method primarily makes use of the hydrogen ion production rate and the carbon dioxide transfer rate resulting from the acetate uptake processes by PAOs and GAOs, measured with a recently developed titration and off-gas analysis (TOGA) sensor. The method is demonstrated using the data from a laboratory-scale sequencing batch reactor (SBR) operated under alternating anaerobic and aerobic conditions. The data analysis using the proposed method strongly indicates a coexistence of PAOs and GAOs in the system, which was independently confirmed by fluorescent in situ hybridization (FISH) measurement. The model-based analysis also allowed the identification of the respective acetate uptake rates by PAOs and GAOs, along with a number of kinetic and stoichiometric parameters involved in the PAO and GAO models. The excellent fit between the model predictions and the experimental data not involved in parameter identification shows that the parameter values found are reliable and accurate. It also demonstrates that the current anaerobic PAO and GAO models are able to accurately characterize the PAO/GAO mixed culture obtained in this study. This is of major importance as no pure culture of either PAOs or GAOs has been reported to date, and hence the current PAO and GAO models were developed for the interpretation of experimental results of mixed cultures. The proposed method is readily applicable for detailed investigations of the competition between PAOs and GAOs in enriched cultures. However, the fermentation of organic substrates carried out by ordinary heterotrophs needs to be accounted for when the method is applied to the study of PAO and GAO competition in full-scale sludges. (C) 2003 Wiley Periodicals, Inc.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

LMP based bid formation for virtual power players operating in smart grids

Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Transmission tariffs in competitive electricity markets

In context of electricity market, the transmission price is an important tool to an efficient development of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for that reason evaluate tariff must have strict criterions. This paper explains several methodologies to tariff the use of transmission network by transmission network users. The methods presented are: Post-Stamp Method; MW-Mile Method; Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.