Evaluating the Information Efficiency of Australian Electricity Spot Markets: Multiple Variance Ratio Tests of Random Walks

This paper examines whether Australian electricity spot prices follow a random walk. Daily peak and off-peak (base load) prices for New South Wales, Victoria, Queensland and South Australia are sampled over the period July 1999 to June 2001 and analysed using multiple variance ratio tests. The results indicate that the null hypothesis of a random walk can be rejected in all peak period and most off-period markets because of the autocorrelation of returns. For the Victorian market, the off-peak period electricity spot price follows a random walk. One implication of the study is that in most instances, stochastic autoregressive modelling techniques may be adequate for forecasting electricity prices

Auction-based Bandwidth Allocation Mechanisms for Wireless Future Internet

An important aspect of the Future Internet is the efficient utilization of (wireless) network resources. In order for the - demanding in terms of QoS - Future Internet services to be provided, the current trend is evolving towards an "integrated" wireless network access model that enables users to enjoy mobility, seamless access and high quality of service in an all-IP network on an "Anytime, Anywhere" basis. The term "integrated" is used to denote that the Future Internet wireless "last mile" is expected to comprise multiple heterogeneous geographically coexisting wireless networks, each having different capacity and coverage radius. The efficient management of the wireless access network resources is crucial due to their scarcity that renders wireless access a potential bottleneck for the provision of high quality services. In this paper we propose an auction mechanism for allocating the bandwidth of such a network so that efficiency is attained, i.e. social welfare is maximized. In particular, we propose an incentive-compatible, efficient auction-based mechanism of low computational complexity. We define a repeated game to address user utilities and incentives issues. Subsequently, we extend this mechanism so that it can also accommodate multicast sessions. We also analyze the computational complexity and message overhead of the proposed mechanism. We then show how user bids can be replaced from weights generated by the network and transform the auction to a cooperative mechanism capable of prioritizing certain classes of services and emulating DiffServ and time-of-day pricing schemes. The theoretical analysis is complemented by simulations that assess the proposed mechanisms properties and performance. We finally provide some concluding remarks and directions for future research

Tests of the Random Walk Hypothesis for Australian Electricity Spot Prices: An Application Employing Multiple Variance Ratio Tests

This paper examines whether Australian electricity spot prices follow a random walk. Daily peak and off-peak (base load) prices for New South Wales, Victoria, Queensland and South Australia are sampled over the period July 1999 to June 2001 and analysed using multiple variance ratio tests. The results indicate that the null hypothesis of a random walk can be rejected in all peak period and most off-period markets because of the autocorrelation of returns. For the Victorian market, the off-peak period electricity spot price follows a random walk. One implication of the study is that in most instances, stochastic autoregressive modelling techniques may be adequate for forecasting electricity prices.

UC Berkeley's Cory Hall: Evaluation of Challenges and Potential Applications of Building-to-Grid Implementation

From September 2009 through June 2010, a team of researchers developed, installed, and tested instrumentation on the energy flows in Cory Hall on the UC Berkeley campus to create a Building-to-Grid testbed. The UC Berkeley team was headed by Professor David Culler, and assisted by members from EnerNex, Lawrence Berkeley National Laboratory, California State University Sacramento, and the California Institute for Energy & Environment. While the Berkeley team mapped the load tree of the building, EnerNex researched types of meters, submeters, monitors, and sensors to be used (Task 1). Next the UC Berkeley team analyzed building needs and designed the network of metering components and data storage/visualization software (Task 2). After meeting with vendors in January, the UCB team procured and installed the components starting in late March (Task 3). Next, the UCB team tested and demonstrated the system (Task 4). Meanwhile, the CSUS team documented the methodology and steps necessary to implement a testbed (Task 5) and Harold Galicer developed a roadmap for the CSUS Smart Grid Center with results from the testbed (Task 5a) and evaluated the Cory Hall implementation process (Task 5b). The CSUS team also worked with local utilities to develop an approach to the energy information communication link between buildings and the utility (Task 6). The UC Berkeley team then prepared a roadmap to outline necessary technology development for Building-to-Grid, and presented the results of the project in early July (Task 7). Finally, CIEE evaluated the implementation, noting challenges and potential applications of Building-to-Grid (Task 8). These deliverables are available at the i4Energy site: http://i4energy.org/

Contingency Management in Power Systems and Demand Response Market for Ancillary Services in Smart Grids with High Renewable Energy Penetration.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Transmission of prices and price volatility in Australian electricity spot markets: A multivariate GARCH analysis

This paper examines the transmission of spot electricity prices and price volatility among the five Australian electricity markets in the National Electricity Market (NEM): namely, New South Wales (NSW), Queensland (QLD), South Australia (SA), the Snowy Mountains Hydroelectric Scheme (SNO) and Victoria (VIC). A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of spillovers. The results indicate the presence of positive own mean spillovers in only a small number of markets and no mean spillovers between any of the markets. This appears to be directly related to the limitations of the present system of regional interconnectors. Nevertheless, the large number of significant ownvolatility and cross-volatility spillovers in all five markets indicates the presence of strong ARCH and GARCH effects. Contrary to evidence from studies in North American electricity markets, the results also indicate that Australian electricity spot prices are stationary.spot electricity price markets; mean and volatility spillovers; multivariate GARCH

Optimal Participation of Power Generating Companies in a Deregulated Electricity Market

The function of an electric utility is to make stable electric power available to consumers in an efficient manner. This would include power generation, transmission, distribution and retail sales. Since the early nineties however, many utilities have had to change from the vertically integrated structure to a deregulated system where the services were unbundled due to a rapid demand growth and need for better economic benefits. With the unbundling of services came competition which pushed innovation and led to the improvement of efficiency. In a deregulated power system, power generators submit offers to sell energy and operating reserve in the electricity market. The market can be described more as oligopolistic with a System Operator in-charge of the power grid, matching the offers to supply with the bid in demands to determine the market clearing price for each interval. This price is what is paid to all generators. Energy is sold in the day-ahead market where offers are submitted hours prior to when it is needed. The spot energy market caters to unforeseen rise in load demand and thus commands a higher price for electrical energy than the day-ahead market. A generating company can improve its profit by using an appropriate bidding strategy. This improvement is affected by the nature of bids from competitors and uncertainty in demand. In a sealed bid auction, bids are submitted simultaneously within a timeframe and are confidential, thus a generator has no information on rivals’ bids. There have been studies on methods used by generators to build optimal offers considering competition. However, many of these studies base estimations of rivals’ behaviour on analysis with sufficient bidding history data from the market. Historical data on bidding behaviour may not be readily available in practical systems. The work reported in this thesis explores ways a generator can make security-constrained offers in different markets considering incomplete market information. It also incorporates possible uncertainty in load forecasts. The research methodology used in this thesis is based on forecasting and optimization. Forecasts of market clearing price for each market interval are calculated and used in the objective function of profit maximization to get maximum benefit at the interval. Making these forecasts includes competition into the bid process. Results show that with information on historical data available, a generator can make adequate short-term analysis on market behaviour and thus optimize its benefits for the period. This thesis provides new insights into power generators’ approach in making optimal bids to maximize market benefits

The Relationship Between Energy Spot and Futures Prices: Evidence from the Australian Electricity Market

This paper examines the relationship between futures and spot electricity prices for two of the Australian electricity regions in the National Electricity Market (NEM): namely, New South Wales and Victoria. A generalised autoregressive conditional heteroskedasticity (GARCH) model is used to identify the magnitude and significance of mean and volatility spillovers from the futures market to the spot market. The results indicate the presence of positive mean spillovers in the NSW market for peak and off-peak (base load) futures contracts and mean spillovers for the offpeak Victorian futures market. The large number of significant innovation and volatility spillovers between the futures and spot markets indicates the presence of strong ARCH and GARCH effects. Contrary to evidence from studies in North American electricity markets, the results also indicate that Australian electricity spot and futures prices are stationary.

Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems

We consider the real-time scheduling of full truckload transportation orders with time windows that arrive during schedule execution. Because a fast scheduling method is required, look-ahead heuristics are traditionally used to solve these kinds of problems. As an alternative, we introduce an agent-based approach where intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. This approach offers several advantages: it is fast, requires relatively little information and facilitates easy schedule adjustments in reaction to information updates. We compare the agent-based approach to more traditional hierarchical heuristics in an extensive simulation experiment. We find that a properly designed multiagent approach performs as good as or even better than traditional methods. Particularly, the multi-agent approach yields less empty miles and a more stable service level