Ariel Liebman

Partial Carbon Permits Allocation of Potential Emission Trading Scheme in Australian Electricity Market

Emission trading is widely considered to be the most effective policy to minimize the overall costs for CO2 abatement. However, the political feasibility of an emission trading scheme may crucially depend on the free initial allocation of emission permits to carbon-intensive industries in order to offset the reduction in profits. This paper aims to analyze these potential profit impacts and the possible compensation to affected generation companies through modeling the Australian National Electricity Market under a potential emission trading scheme. Historical emission-based and historical generation-based allocation approaches are used in this paper to calculate and compare the percentages of carbon permits that should be freely allocated. Two carbon permit price scenarios are used to analyze the sensitivity of the optimal percentage of free allocation to carbon permit price.

Single-mode resonator incorporating an internal multimode optical fiber and a phase-conjugate reflector

Phase-conjugate mirrors (PCM’s) can be used to correct for phase distortion introduced by optical elements included within laser resonators, enabling diffraction-limited output beams to be produced. A severe example of a phase-distorting medium that could be included within a resonator is a multimode optical fiber. We describe the operation of a resonator that contains such a fiber and uses a PCM to restrict the output from the fiber to the lowest-order transverse mode. The system thereby enables the output from a laser to be transported to a remote location through the multimode fiber without loss of mode quality. The PCM was a high-gain passive PCM made from a barium titanate crystal pumped by a 60-mW single-mode argon-ion laser.

Power generation investment opportunities evaluation: a comparison between net present value and real options approach

To evaluate an investment project in the competitive electricity market, there are several key factors that affects the projects value: the present value that the project could bring to investor, the possible future course of actions that investor has and the projects management flexibility. The traditional net present value (NPV) criteria has the ability to capture the present value of the projects future cash flow, but it fails to assess the value brought by market uncertainty and management flexibility. By contrast with NPV, the real options approach (ROA) method has the advantage to combining the uncertainty and flexibility in evaluation process. In this paper, a framework for using ROA to evaluate the generation investment opportunity has been proposed. By given a detailed case study, the proposed framework is compared with NPV and showing a different results

Quantum noise limits to terabaud communications

From a general model of fiber optics, we investigate the physical limits of soliton-based terabaud communication systems. In particular we consider Raman and initial quantum noise effects which are often neglected in fiber communications. Simulations of the position diffusion in dark and bright solitons show that these effects become increasingly important at short pulse durations, even over kilometer-scale distances. We also obtain an approximate analytic theory in agreement with numerical simulations, which shows that the Raman effects exceed the Gordon-Haus jitter for sub-picosecond pulses

Australian electricity market power analysis under potential emission trading scheme

Existence of market power in electricity markets has been revealed by extensive studies, however, the understanding of how environmental policies, e.g. emission trading scheme, impacts on the change of market power of generation companies (GENCOs) is at the inchoate stage. This paper, targeted at the study of Australia National Electricity Market, presents the Cournot market equilibrium model incorporating an emission trading model to study the potential changes of market power due to the introduction of the proposed Australian National Emission Trading Scheme (NETS) and further analyse the sensitivity of market power with increasing carbon price.

Potential impact of emission trading schemes on the Australian National Electricity Market

Power industry worldwide has been identified as a major source of greenhouse gas emissions. Consequently, many countries have started the implementation of emission trading schemes aimed at reducing greenhouse gas emissions by power stations. The Australian government aims to implement an emission trading schemes from 2010/2011. This scheme will greatly change the market perspective of the Australian National Electricity Market (NEM). A thorough understanding of the potential impact of emission trading is essential for market participants as well as energy market policy makers. In this paper, a targeted study of the NEM is presented to illustrate the impact on generation companies of different design choices regarding the free allocation of permits aspect of the proposed emission trading scheme. A recommendation is proposed to best promote reduction of emissions while minimizing the adverse impact on the electricity system, particularly on the generation companies.

Customer information systems for deregulated ASEAN countries

In similar fashion to western countries, ASEAN countries are also gearing up towards deregulation. Despite potentially different motivating drivers, the ultimate objectives are free market competition leading to efficient pricing signals as well as providing customers with the freedom to choose their electricity provider and benefit from competitive prices. This paper provides an ASEAN electricity market analysis and describes the development of electricity deregulation in ASEAN countries. By way of background it also highlights the objectives of deregulation, the potential challenges and also the impact areas focusing on existing customer information systems (CIS) that have been developed by other utilities. In addition, this paper proposes a new framework for improving CIS for ASEAN utilities facing deregulation. The framework outlines a CIS, which has intelligent features enabling the utility to estimate and predict customer behaviour with respect to consumption patterns. It describes how these features can assist the utility companies to retain their existing customers as well as attract more customers

Visual Encoding of Dissimilarity Data via Topology-Preserving Map Deformation

We present an efficient technique for topology-preserving map deformation and apply it to the visualization of dissimilarity data in a geographic context. Map deformation techniques such as value-by-area cartograms are well studied. However, using deformation to highlight (dis)similarity between locations on a map in terms of their underlying data attributes is novel. We also identify an alternative way to represent dissimilarities on a map through the use of visual overlays. These overlays are complementary to deformation techniques and enable us to assess the quality of the deformation as well as to explore the design space of blending the two methods. Finally, we demonstrate how these techniques can be useful in several-quite different-applied contexts: travel-time visualization, social demographics research and understanding energy flowing in a wide-area power-grid.

A Fast and Scalable Algorithm for Scheduling Large Numbers of Devices Under Real-Time Pricing

Real-time pricing (RTP) is a financial incentive mechanism designed to encourage demand response (DR) to reduce peak demand in medium and low voltage distribution networks but also impacting the generation and transmission system. Though RTP is believed to be an effective mechanism, challenges exist in implementing RTP for residential consumers wherein manually responding to a changing price is difficult and uncoordinated responses can lead to undesired peak demand at what are normally off-peak times. Previous research has proposed various algorithms to address these challenges, however, they rarely consider algorithms that manage very large numbers of houses and devices with discrete consumption levels. To optimise conflicting objectives under RTP prices in a fast and highly scalable manner is very challenging. We address these issues by proposing a fast and highly scalable algorithm that optimally schedules devices for large numbers of households in a distributed but non-cooperative manner under RTP. The results show that this algorithm minimises the total cost and discomfort for 10,000 households in a second and has a constant computational complexity.