‘Redstone is like electricity’: Children's performative representations in and around Minecraft

In this article, we investigate eight and nine year old girls’ school and home use of the popular game Minecraft and the ways in which the girls ‘bring themselves into being’ through talk and digital production in the social spaces of the classroom and within the game’s multiplayer online world. This work was conducted as part of a broader digital games in education project involving primary and secondary school-aged students in Australia and focuses specifically on data collected from an all-girls primary school in Brisbane. We investigate the processes of identity construction that occur as the girls undertake practices of curatorship (Potter, 2012) to display their knowledge of Minecraft through discussion of the game, both ‘in world’ and in face-to-face interactions, and as they assemble resources within and around the game to design, build and display their creations and share stories about their game play. The article begins with a consideration of recent scholarship focussing on children, learning and digital culture and literacy practices before explaining how Minecraft is, in many ways, an exemplary instance of a digital game that promotes and enables complex practices of digital participation. We then introduce the concepts of performativity and recognition (Butler 1990, 2004, 2005) which, we argue, provide productive ways to theorise identity work within affinity groups. The article then outlines some background to the research project and our methodology before providing analysis of the data in the second half of the article. We conclude by outlining the implications of our investigation for the conceptualisation of learning spaces as affinity groups and for considering digital participation as curatorship.

Moving from outsider to insider : peer status and partnerships between electricity utilities and residential consumers

An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Regulatory reforms and productivity : an empirical analysis of the Japanese electricity industry

The Japanese electricity industry has experienced regulatory reforms since the mid-1990s. This article measures productivity in Japan's steam power-generation sector and examines the effect of reforms on the productivity of this industry over the period 1978-2003. We estimate the Luenberger productivity indicator, which is a generalization of the commonly used Malmquist productivity index, using a data envelopment analysis approach. Factors associated with productivity change are investigated through dynamic generalized method of moments (GMM) estimation of panel data. Our empirical analysis shows that the regulatory reforms have contributed to productivity growth in the steam power-generation sector in Japan.

Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

Impact of technology uptake on an Australian electricity distribution network

This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.

Optimal electricity distribution framework for public space: Assessing renewable energy proposals for Freshkills Park, New York City

Integrating renewable energy into public space is becoming more common as a climate change solution. However, this approach is often guided by the environmental pillar of sustainability, with less focus on the economic and social pillars. The purpose of this paper is to examine this issue in the speculative renewable energy propositions for Freshkills Park in New York City submitted for the 2012 Land Art Generator Initiative (LAGI) competition. This paper first proposes an optimal electricity distribution (OED) framework in and around public spaces based on relevant ecology and energy theory (Odum’s fourth and fifth law of thermodynamics). This framework addresses social engagement related to public interaction, and economic engagement related to the estimated quantity of electricity produced, in conjunction with environmental engagement related to the embodied energy required to construct the renewable energy infrastructure. Next, the study uses the OED framework to analyse the top twenty-five projects submitted for the LAGI 2012 competition. The findings reveal an electricity distribution imbalance and suggest a lack of in-depth understanding about sustainable electricity distribution within public space design. The paper concludes with suggestions for future research.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

A smooth transition logit model of the effects of deregulation in the electricity market

This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland.

Improved residential electricity demand management through analysis of the customer perspective

Peak electricity demand requires substantial investment to update transmission, distribution and generation infrastructure. A successful community peak demand reduction project was examined to identify residential consumer motivational and contextual factors involved in their decision to adopt/not adopt interventions. Energy professionals actively worked to achieve community 'peer' membership and by becoming a trusted information source, facilitated voluntary home energy assessment requests from over 80% of the residential community. By combining and tailoring interventions to the specific needs and motivations of individual householders and the community, interventions promoting energy conservation and efficiency can be effective in achieving sustained reduction in peak demand.

Modelling interregional links in electricity price spikes

Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to dealwith spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account.