Τα φυσικά ανάλογα έχουν αποδειχθεί, στο παρελθόν, ιδιαίτερα υποσχόμενα για την κατανόηση της συμπεριφοράς των σύνθετων προσαρμοστικών συστημάτων, συμπεριλαμβανομένων της μακροοικονομίας, των βιολογικών συστημάτων και των κοινωνικών δικτύων, καθώς πολλά από τα σημερινά τεχνικά ερωτήματα μπορούν να μετατραπούν σε ένα πρόβλημα κατανεμημένου οικονομικού ελέγχου. Σκοπός της παρούσας διπλωματικής εργασίας είναι η κατασκευή κι αξιοποίηση ενός τέτοιου ανάλογου με τη θερμοδυναμική, ατομική και στατιστική φυσική για τη μελέτη της συμπεριφοράς των απελευθερωμένων αγορών ηλεκτρικής ενέργειας. Αρχικά, επιχειρείται η συστημική ανάλυση όλων των συντελεστών, παραγόντων και λειτουργιών μίας αγοράς ηλεκτρισμού, με εκτενή αναφορά στην ελληνική πραγματικότητα, και, στη συνέχεια, αυτή μοντελοποιείται μαθηματικά, μέσω της οικονομικής ανάλυσης των αγορών και της προσέγγισης εκείνων των οικονομικών μοντέλων αγορών που ανταποκρίνονται στα δίκτυα ηλεκτρικής ενέργειας. Έπειτα, πραγματοποιείται μία εισαγωγή στην εφαρμοσμένη, κατά τον ίδιο τρόπο, στατιστική μηχανική, με τη συνοπτική περιγραφή αντίστοιχων προσεγγίσεων σε γνωστά μοντέλα του χρήματος, του χρέους και της ενεργειακής κατανάλωσης, ενώ τελικά κατασκευάζεται το ζητούμενο μοντέλο που διέπεται από τους κανόνες της στατιστικής μηχανικής, τους περιορισμούς και τις ιδιότητες της ελεύθερης αγοράς ηλεκτρισμού. / Physical analogs have previously proved to be quite promising for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems and social networks, since many of today’s challenging technical questions and problems can be reduced to a distributed economic control problem. The purpose of this thesis is the derivation and development of such an analog to thermal, atomic and statistical physics, in order to study the behavior of free power markets. At first, a systemic approach of all agents, factors and functions of an electric power market is being attempted, with an extended reference to the greek power system and market, and, later, markets are being mathematically modeled, through the economic analysis of markets in general and the approach in those models which can be or have been adopted for electic power transactions. Then, an introduction to respectively applied statistical mechanics is being made, along with a summarized description of previous analogs invented for analyzing the models of money, debt and energy consumption, and, finally, the required model, ruled by the laws of statistical physics and the constraints and properties of free electric power markets, is being developed.

Of the findings, the European Commission established in its report on Energy Sector Inquiry, market manipulation constituted a major concern for the functioning and integrity of EU energy sectors. The Commission argued that the responsibility for high prices in wholesale energy markets could be attributed to manipulative practices of energy incumbents and the trust in the operation of operation of sector was largely compromised, due to these practices. Remedies, EU competition law provided, were considered as insufficient to resolve these shortcomings and thus should be supplemented with regulatory-based tools. The findings of the Energy Sector Inquiry and subsequent consultation documents by multiple EU institutions paved the way for the adoption of the Regulation on wholesale energy market integrity and transparency, REMIT, which incorporated into an anti-manipulation rule, specifically designed to prohibit and prosecute manipulative practices in EU wholesale energy markets. Nevertheless, as EU case law on market manipulation has yet to develop and there are uncertainties with respect to the concept of market manipulation. Furthermore REMIT does not preclude the jurisdiction of EU competition law, questions arise as to the scope and the extent of the application of this prohibition. Throughout its chapters, this book explores the scope of and the case law on market manipulation to determine what types of market practices are regarded as manipulative and thus prohibited under anti-manipulation rules. It also focuses on the interplay between REMIT and EU competition law and evaluates factors and circumstances that determine when and what market misconduct can be subject to enforcement proceedings under both anti-manipulation and antitrust rules. As the development of a single, coherent, rulebook that can be relied upon by market participant is fundamental for the functioning of EU wholesale energy markets, the book, finally, provides proposals and measures that can mitigate and resolve the legal uncertainties regarding the regulatory framework REMIT established.

The Autonomic Power System (APS) grand challenge was a multi-disciplinary EPSRC-funded research project that examined novel techniques that would enable the transition between today's and 2050's highly uncertain and complex energy network. Being part of the APS, this thesis reports on the sub-project 'RR2: Avoiding High-Impact Low Probability events'. The goal of RR2 is to develop new algorithms for controlling risk exposure to high-impact low probability (Hi-Lo) events through the provision of appropriate risk-sensitive control strategies. Additionally, RR2 is concerned with new techniques for identifying and modelling risk in future energy networks, in particular, the risk of Hi-Lo events. In this context, this thesis investigates two distinct problems arising from energy risk management. On the one hand, we examine the problem of finding managerial strategies for exercising the operational flexibility of energy assets. We look at this problem from a risk perspective taking into account non-linear risk preferences of energy asset managers. Our main contribution is the development of a risk-sensitive approach to the class of optimal switching problems. By recasting the problem as an iterative optimal stopping problem, we are able to characterise the optimal risk-sensitive switching strategies. As byproduct, we obtain a multiplicative dynamic programming equation for the value function, upon which we propose a numerical algorithm based on least squares Monte Carlo regression. On the other hand, we develop tools to identify and model the risk factors faced by energy asset managers. For this, we consider a class of models consisting of superposition of Gaussian and non-Gaussian Ornstein-Uhlenbeck processes. Our main contribution is the development of a Bayesian methodology based on Markov chain Monte Carlo (MCMC) algorithms to make inference into this class of models. On extensive simulations, we demonstrate the robustness and efficiency of the algorithms to different data features. Furthermore, we construct a diagnostic tool based on Bayesian p-values to check goodness-of-fit of the models on a Bayesian framework. We apply this tool to MCMC results from fitting historical electricity and gas spot price data- sets corresponding to the UK and German energy markets. Our analysis demonstrates that the MCMC-estimated models are able to capture not only long- and short-lived positive price spikes, but also short-lived negative price spikes which are typical of UK gas prices and German electricity prices. Combining together the solutions to the two problems above, we strive to capture the interplay between risk, uncertainty, flexibility and performance in various applications to energy systems. In these applications, which include power stations, energy storage and district energy systems, we consistently show that our risk management methodology offers a tradeoff between maximising average performance and minimising risk, while accounting for the jump dynamics of energy prices. Moreover, the tradeoff is achieved in such way that the benefits in terms of risk reduction outweigh the loss in average performance.

E’ stato estesamente appurato che i mercati dell'elettricità mostrano mean-reversion e elevata volatilità dei prezzi. Questo lavoro utilizza un modello VAR-MGARCH al fine di cogliere queste caratteristiche presenti sul mercato dell'energia elettrica italiana (IPEX) e analizzare le interrelazioni esistenti tra le diverse regioni in cui il mercato è suddiviso. L’analisi è condotta sui prezzi giornalieri dal 1 ° gennaio 2006 al 31 dicembre 2008. I coefficienti stimati dalle equazioni condizionali indicano che i mercati regionali sono abbastanza integrati e i prezzi regionali dell'energia elettrica possono essere adeguatamente previsti impiegando i prezzi passati di ciascun mercato zonale. La volatilità e la cross-volatility sono significative per tutti i mercati, indicando la presenza di forti componenti ARCH e GARCH e la sostanziale inefficienza dei mercati. E’ inoltre evidente un’elevata persistenza della volatilità e della cross-volatility in tutti i mercati. I risultati indicano inoltre che gli shock rilevati, sia nella volatilità, sia nei vari mercati, persistono nel tempo e che in ogni mercato la persistenza è più marcata quando è causata da innovazioni stimate sulle stesso mercato rispetto a shock stimati su altre aree. Questa persistenza descrive la tendenza delle variazioni dei prezzi a raggrupparsi nel tempo. / It is commonly known that spot electricity markets show mean-reversion and high price volatility. This work employs a VAR-MGARCH model to capture these features in the Italian electricity market (IPEX) and analyze the interrelation existing among the different regions in which the market is divided. Daily spot prices from 1 January 2006 to 31 December 2008 are employed. The estimated coefficients from the conditional mean equations indicate that the regional markets are quite integrated and regional electricity prices could be usefully forecasted using lagged prices from either the same market or from the other areal markets. Volatility and cross-volatility spill-overs are significant for all markets, indicating the presence of strong ARCH and GARCH effects and market inefficiency. Strong persistence of volatility and cross-volatility are also evident in all local markets. The results also indicate that volatility innovations or shocks in all markets persist over time and that in every market this persistence is more marked for own-innovations or shocks than cross-innovations or shocks. This persistence captures the propensity of price changes of similar magnitude to cluster in time.

This dissertation details regulation's impact in networked markets, notably in deregulated electricity and internet service markets. These markets represent basic infrastructure in the modern economy; their innate networked structures make for rich fields of economic research on regulatory impact. The first chapter models deregulated electricity industries with a focus on the Texas market. Optimal economic benchmarks are considered for markets with regulated delivery and interrelated network costs. Using a model of regulator, consumer, and firm interaction, I determine the efficiency of the current rate formalization compared to Ramsey-Boiteux prices and two-part tariffs. I find within Texas's market increases to generator surplus up to 55% of subsidies could be achieved under Ramsey-Boiteux pricing or two-part tariffs, respectively. The second chapter presents a framework to analyze dynamic processes and long-run outcomes in two-sided markets, specifically dynamic platform and firm investment incentives within the internet-service platform/content provision market. I use the Ericson-Pakes framework applied within a platform that chooses fees on either side of its two-sided market. This chapter determines the impact of network neutrality on platform investment incentives, specifically whether to improve the platform. I use a parameterized calibration from engineering reports and current ISP literature to determine welfare outcomes and industry behavior under network neutral and non-neutral regimes. My final chapter explores retail firm failure within the deregulated Texas retail electricity market. This chapter investigates determinants of retail electric firm failures using duration analysis frameworks. In particular, this chapter investigates the impact of these determinants on firms with extant experience versus unsophisticated entrants. Understanding these determinants is an important component in evaluating whether deregulation achieves the impetus of competitive electricity market restructuring. Knowing which economic events decrease a market's competitiveness helps regulators to effectively evaluate policy implementations. I find that experience does benefit a firm's duration, but generally that benefit assists firm duration in an adverse macroeconomic environment rather than in response to adverse market conditions such as higher wholesale prices or increased transmission congestion. Additionally, I find evidence that within the Texas market entering earlier results in a longer likelihood of duration. / text