Egységes kockázatkezelési módszertan kialakítása a villamosenergia-ipari átviteli rendszerirányító társaságnál (Development of an integrated risk management methodology for an electricity transmission system operator (TSO) company)

A felelős vállalatirányítás egyik stratégiai jelentőségű tényezője a vállalati szintű kockázatkezelés, mely napjaink egyik legnagyobb kihívást jelentő területe a vállalatvezetés számára. A hatékony vállalati kockázatkezelés nem valósulhat meg kizárólag az általános, nemzetközi és hazai szakirodalomban megfogalmazott kockázatkezelési alapelvek követése mentén, a kockázatkezelési rendszer kialakítása során figyelembe kell venni mind az iparági, mind az adott vállalatra jellemző sajátosságokat. Mindez különösen fontos egy olyan speciális tevékenységet folytató vállalatnál, mint a villamosenergia-ipari átviteli rendszerirányító társaság (transmission system operator, TSO). A cikkben a magyar villamosenergia-ipari átviteli rendszerirányító társasággal együttműködésben készített kutatás keretében előálló olyan komplex elméleti és gyakorlati keretrendszert mutatnak be a szerzők, mely alapján az átviteli rendszerirányító társaság számára kialakítottak egy új, területenként egységes kockázatkezelési módszertant (fókuszban a kockázatok azonosításának és számszerűsítésének módszertani lépéseivel), mely alkalmas a vállalati szintű kockázati kitettség meghatározására. _______ This study handles one of today’s most challenging areas of enterprise management: the development and introduction of an integrated and efficient risk management system. For companies operating in specific network industries with a dominant market share and a key role in the national economy, such as electricity TSO’s, risk management is of stressed importance. The study introduces an innovative, mathematically and statistically grounded as well as economically reasoned management approach for the identification, individual effect calculation and summation of risk factors. Every building block is customized for the organizational structure and operating environment of the TSO. While the identification phase guarantees all-inclusivity, the calculation phase incorporates expert techniques and Monte Carlo simulation and the summation phase presents an expected combined distribution and value effect of risks on the company’s profit lines based on the previously undiscovered correlations between individual risk factors.

Essays on market design and regulation in electricity systems

This thesis discusses market design and regulation in electricity systems, focusing on the information exchange of the regulated grid firm and the generation firms as well as the regulation of the grid firm. In the first chapter, an economic framework is developed to consistently analyze different market designs and the information exchange between the grid firm and the generation firms. Perfect competition between the generation firms and perfect regulation of the grid firm is assumed. A numerical algorithm is developed and its feasibility demonstrated on a large-scale problem. The effects of different market designs for the Central Western European (CWE) region until 2030 are analyzed. In the second chapter, the consequences of restricted grid expansion within the current market design in the CWE region until 2030 are analyzed. In the third chapter the assumption of efficient markets is modified. The focus of the analysis is then, whether and how inefficiencies in information availability and processing affect different market designs. For different parameter settings, nodal and zonal pricing are compared regarding their welfare in the spot and forward market. In the fourth chapter, information asymmetries between the regulator and the regulated firm are analyzed. The optimal regulatory strategy for a firm, providing one output with two substitutable inputs, is defined. Thereby, one input and the absolute quantity of inputs is not observable for the regulator. The result is then compared to current regulatory approaches.

Essays on the effect of renewable energy production in the spanish electricity market.

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Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

Rethinking genre studies through distribution analysis : issues in international horror movie circuits

The existence of any film genre depends on the effective operation of distribution networks. Contingencies of distribution play an important role in determining the content of individual texts and the characteristics of film genres; they enable new genres to emerge at the same time as they impose limits on generic change. This article sets out an alternative way of doing genre studies, based on an analysis of distributive circuits rather than film texts or generic categories. Our objective is to provide a conceptual framework that can account for the multiple ways in which distribution networks leave their traces on film texts and audience expectations, with specific reference to international horror networks, and to offer some preliminary suggestions as to how distribution analysis can be integrated into existing genre studies methodologies.

Green energy : sustainable energy sources and alternative technologies

Despite the general evolution and broadening of the scope of the concept of infrastructure in many other sectors, the energy sector has maintained the same narrow boundaries for over 80 years. Energy infrastructure is still generally restricted in meaning to the transmission and distribution networks of electricity and, to some extent, gas. This is especially true in the urban development context. This early 20th century system is struggling to meet community expectations that the industry itself created and fostered for many decades. The relentless growth in demand and changing political, economic and environmental challenges require a shift from the traditional ‘predict and provide’ approach to infrastructure which is no longer economically or environmentally viable. Market deregulation and a raft of demand and supply side management strategies have failed to curb society’s addiction to the commodity of electricity. None of these responses has addressed the fundamental problem. This chapter presents an argument for the need for a new paradigm. Going beyond peripheral energy efficiency measures and the substitution of fossil fuels with renewables, it outlines a new approach to the provision of energy services in the context of 21st century urban environments.

Digital dawn : a revolution in movie distribution?

How will the digital technology revolution impact the movie business? Hollywood developed a highly successful industrial system that has functioned well for almost a century in the sense that it enabled the Major film studios to largely control and dominate the industry. However, the new digital technology may now be propelling Hollywood toward the biggest technological transition since the creation of the studio system almost a century ago. For example, Major Hollywood studios are already beginning to provide video-on-demand (VOD) digital distribution of movies over the Internet. This article examines what is happening, and why. It sets out the background and the incipient changes already occurring. It makes an argument regarding the fundamental strategic dynamics, that acetate film was the key to the control of the Hollywood system, and speculates about how a shift away from acetate film to digital video may transform that system. The focus is on the impact on how the Major studios release and market their movies, and how new market and marketing opportunities for the low-budget independent filmmaking sector may arise.

Analysing the effect of digital technology on channel strategy, power and disintermediation in the home video market : the demise of the video store?

The antecedents of channel power (e.g. El-Ansary and Stern, 1972) and the impact of channel structure ( e.g. Anderson and Narus,1984) on channel dynamics have long been important topics within the channel literature. In addition to the theoretical and methodological contributions, research in these areas has helped channel managers to understand how power is generated and used in coordinating distribution strategies in different contexts. The study presented in this paper builds upon these previous literatures, which are first briefly reviewed below.

The role of law in responding to climate change : emerging regulatory, liability and market approaches

Climate change presents as the archetypal environmental problem with short-term economic self-interest operating to the detriment of the long-term sustainability of our society. The scientific reports of the Intergovernmental Panel on Climate Change strongly assert that the stabilisation of emissions in the atmosphere, to avoid the adverse impacts of climate change, requires significant and rapid reductions in ‘business as usual’ global greenhouse gas emissions. The sheer magnitude of emissions reductions required, within this urgent timeframe, will necessitate an unprecedented level of international, multi-national and intra-national cooperation and will challenge conventional approaches to the creation and implementation of international and domestic legal regimes. To meet this challenge, existing international, national and local legal systems must harmoniously implement a strong international climate change regime through a portfolio of traditional and innovative legal mechanisms that swiftly transform current behavioural practices in emitting greenhouse gases. These include the imposition of strict duties to reduce emissions through the establishment of strong command and control regulation (the regulatory approach); mechanisms for the creation and distribution of liabilities for greenhouse gas emissions and climaterelated harm (the liability approach) and the use of innovative regulatory tools in the form of the carbon trading scheme (the market approach). The legal relations between these various regulatory, liability and market approaches must be managed to achieve a consistent, compatible and optimally effective legal regime to respond to the threat of climate change. The purpose of this thesis is to analyse and evaluate the emerging legal rules and frameworks, both international and Australian, required for the effective regulation of greenhouse gas emissions to address climate change in the context of the urgent and deep emissions reductions required to minimise the adverse impacts of climate change. In doing so, this thesis will examine critically the existing and potential role of law in effectively responding to climate change and will provide recommendations on the necessary reforms to achieve a more effective legal response to this global phenomenon in the future.

Costco and the Aussie shopper : a case study of the market entry of an international retailer

Retailing is a globalized industry yet retailers must respond to local shopping habits if they are to be perceived as legitimate by the host country customers. However, some retailers may be unable or unwilling to respond to all customer requirements. Costco, the membership warehouse club retailer, has been successful in its international expansion efforts, establishing its first Australian store in Melbourne in 2009. In the first twelve months of operation, the store became one of Costco’s top five stores in the world. We investigate this success focussing on the customer, and use institutional theory to analyze what concessions were made by the customer and the company. Data were collected from consumer interviews, site visits and secondary media and industry sources. Analysis revealed negotiations based on the rejection, acceptance or adaptation of the regulative, normative and cultural cognitive aspects of the Australian shopper and the Costco business model. Customers made concessions to accommodate the new business model, and Costco responded to entrenched Australian shopping habits. This case is the first to explore the outcome of retail internationalization from the customers’ perspective, revealing the concept of mutual concessions. The interaction and subsequent adaptation by both customer and retailer have resulted in the institutionalization of new shopping norms in the host country and success for the international retailer.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.