Essays in econometrics and energy markets

Cette thèse est organisée en trois chapitres où sont développées des méthodes d’analyse économique et économétrique des marchés de l’énergie. Le Chapitre 1 propose une étude des incitations à la manipulation de marché générées par des opportunités de revenir sur ses engagements. Un modèle théorique est développé pour analyser le comportement d’un monopole face à une frange compétitive en présence d’une demande incertaine, de contraintes de capacité, et de possibilités de trahir ses engagements. Les entreprises se concurrencent avec des fonctions d’offre étant donnés leurs engagements. Le monopole revient sur ses engagements lorsqu’il retire sa production engagée en observant la réalisation de l’incertitude. Il peut ainsi exacerber son pouvoir de marché, réduire l’incertitude autour de la demande, et accroitre sa probabilité de devenir un offreur pivot. À l’équilibre, les stratégies d’offre dépendent du volume de production engagée et du coût d’opportunité de la retirer stratégiquement. En particulier, le monopole peut trouver profitable d’offrir sa production à des prix plus élevés lorsqu’il sait qu’il pourra revenir sur ses engagements si la demande est élevée. Finalement, cette stratégie est présentée comme un comportement de manipulation par perte, et des applications aux marchés de l’électricité sont discutées. Dans le Chapitre 2, nous développons de nouveaux résultats pour les régressions fonctionnelles où le prédicteur Z(t) et la réponse Y (t) sont des fonctions d’espaces de Hilbert, indexés par le temps ou l’espace. Le modèle peut être compris comme une généralisation de la régression multivariée où le coefficient de régression est maintenant un opérateur inconnu Π. Nous proposons d’estimer l’opérateur Π par régularisation de Tikhonov, ce qui revient à appliquer une pénalité sur sa norme L2. Nous dérivons le taux de convergence de l’erreur quadratique moyenne, la distribution asymptotique de l’estimateur, et développons des tests sur Π. Comme les trajectoires ne sont généralement pas complètement observables, nous considérons une situation où les données deviennent de plus en plus fréquentes (asymptotique de remplissage). Nous traitons aussi le cas où Z est endogène et des variables instrumentales sont utilisées afin d’estimer Π. Une application à la consommation d’électricité complète l’article. Le Chapitre 3 propose une nouvelle approche pour l’analyse empirique des enchères à unités multiples, dans lesquelles les participants choisissent des fonctions d’offre ou de demande. Cette approche permet d’évaluer le pouvoir de marché des entreprises dans une cadre d’information privée, en évitant d’avoir à modéliser le mécanisme du marché. Elle repose sur des méthodes économétriques qui traitent les fonctions de mise comme des éléments aléatoires à valeurs fonctionnelles. Notamment, un estimateur fonctionnel à variable instrumentale est développé. La méthode est appliquée au marché de l’électricité de l’état de New York sur des données micro-économiques de mises et de coûts à l’échelle des entreprises pour 2013-2015. J’estime le pouvoir de marché unilatéral des entreprises et compare les comportements observés aux comportements maximisant les profits sous information privée. Je trouve un faisceau d’indices sérieux de comportement optimal, qui suggère que les entreprises sont au courant de leur pouvoir de marché et se comportent en conséquence.This thesis is organized in three chapters which develop economic and econometric methods for the analysis of energy markets. In Chapter 1, we study the incentives for market manipulations created by opportunities to renege on prior commitments. We develop a theoretical framework to analyze the behavior of a monopolist facing a competitive fringe in the presence of demand uncertainty, capacity constraints and reneging opportunities. The firms are assumed to compete in supply functions taking their commitments as sunk decisions. Reneging occurs when the monopolist withdraws its committed output upon observing the realization of demand. By doing so, it can exacerbate its market power, alleviate demand uncertainty, and be more likely to be pivotal. At equilibrium, supply strategies depend on the volume of committed output and the opportunity cost of reneging. In particular, the monopolist may find profitable to offer some of its market output at higher prices in the presence of reneging opportunities. Finally, we present strategic reneging as a loss-based manipulative conduct in a general framework and discuss applications to electricity markets. In Chapter 2, we develop new estimation results for functional regressions where both the regressor Z(t) and the response Y (t) are functions of Hilbert spaces, indexed by the time or a spatial location. The model can be thought as a generalization of the multivariate regression where the regression coefficient is now an unknown operator Π. We propose to estimate the operator Π by Tikhonov regularization, which amounts to apply a penalty on the L2 norm of Π. We derive the rate of convergence of the mean-square error, the asymptotic distribution of the estimator, and develop tests on Π. As trajectories are often not fully observed, we consider the scenario where the data become more and more frequent (infill asymptotics). We also address the case where Z is endogenous and instrumental variables are used to estimate Π. An application to the electricity consumption completes the paper. Chapter 3 proposes a novel approach for the empirical analysis of multiunit auctions, to which participants submit supply or demand functions observable by the researcher. The approach allows for the evaluation of firmlevel market power in a private information setting, and avoids having to model the market mechanism. It relies on econometric methods that treat the observed bid functions as function-valued random elements. Notably, a functional instrumental variable estimator is developed. The method is applied to the New York electricity market using rich data on firm-level bids and marginal costs for 2013-2015. In this market, daily bids are disclosed three months later in order to limit strategic behaviors. I estimate firm-level market power and compare actual bidding behavior to profit-maximizing behavior under private information. I find consistent evidence of optimal bidding, suggesting that firms are well aware of their own market power and behave accordingly. Therefore, the late disclosure of bids is not sufficient to preclude firms from acting strategically, most likely due to the repeated nature of those auctions

An Analytical Methodology To Security Constraints Management In Power System Operation

In a deregulated electricity market, Independent System Operators (ISOs) are responsible for dispatching power to the load securely, efficiently, and economically. ISO performs Security Constrained Unit Commitment (SCUC) to guarantee sufficient generation commitment, maximized social welfare and facilitating market-driven economics. A large number of security constraints would render the model impossible to solve under time requirements. Developing a method to identify the minimum set of security constraints without overcommitting is necessary to reduce Mixed Integer Linear Programming (MILP) solution time. To overcome this challenge, we developed a powerful tool called security constraint screening. The proposed approach effectively filters out non-dominating constraints by integrating virtual transactions and capturing changes online in real-time or look-ahead markets. The security-constraint screening takes advantage of both deterministic and statistical methods, which leverages mathematical modeling and historical data. Effectiveness is verified using Midcontinent Independent System Operator (MISO) data. The research also presented a data-driven approach to forecast congestion patterns in real-time utilizing machine learning applications. Studies have been conducted using real-world data. The potential benefit is to provide the day-ahead operators with a tool for supporting decision-making regarding modeling constraints

Design and analysis of competitive electricity markets

This thesis focuses on the study of allocation mechanisms and pricing schemes for the design and analysis of competitive electricity markets. Motivated by the increasing demand-side participation in high- and low-voltage power grids, we consider two-sided competition models where a finite group of producers and consumers compete through scalar-parameterized supply offers and demand bids. Acting as a smooth approximation to supply offers used in practice, scalar-parameterized offers greatly facilitate mathematical analysis while preserving the primary determinants and mechanisms by which market power is exercised in electricity markets. In the framework of a pool-based market, characterized by a central dispatch and pricing mechanism, when strategic, capacity-constrained suppliers face strategic, price- responsive consumers, we show that market allocative efficiency loss and price markup at the Nash equilibrium are bounded. We demonstrate analogous efficiency bounds in the study of inter-area electricity markets where we exploit scalar-parameterized offers to model budget-constrained price arbitrageurs that compete against affine inter-area price spreads. Our analysis provides important insights on the type of behavior that may occur at the equilibrium including the pivotal role assumed by certain players, the impacts of aggregate liquidity and uncertainty as well financial positions in other electricity markets. Through the application of reinforcement learn- ing algorithms we demonstrate that players can discover their equilibrium actions even when they know little to nothing about the game setting. The simplicity of scalar-parameterized supply offers that grant market ac- tors’ one-dimensional action spaces while properly constraining their strategic flexibility, render such offer/bid structures an attractive candidate for the expansion of electricity markets to distribution grids. Motivated by the rapid proliferation of distributed energy resources that increasingly hold value for the grid either as power suppliers or flexible demand, we leverage scalar-parameterized supply offers together with appropriate pricing schemes to design a pool-based market for the retail sector. Our goal is complicated by the underlying physics of distribution grids that render the central dispatch problem, in its full generality, non-linear and non-convex. To get around this difficulty, we exploit semidefinite relaxations of the optimal power flow problem and leverage duality theory to define prices for electricity as the optimal Lagrange multipliers of nodal real and reactive power balance constraints. We demonstrate that such prices stand on sound economic principles that together with scalar-parameterized offers/bids, constitute a comprehensive mechanism for the expansion of markets to the low-voltage side of the electric power grid

Decision-making under uncertainty in short-term electricity markets

In the course of the energy transition, the share of electricity generation from renewable energy sources in Germany has increased significantly in recent years and will continue to rise. Particularly fluctuating renewables like wind and solar bring more uncertainty and volatility to the electricity system. As markets determine the unit commitment in systems with self-dispatch, many changes have been made to the design of electricity markets to meet the new challenges. Thereby, a trend towards real-time can be observed. Short-term electricity markets are becoming more important and are seen as suitable for efficient resource allocation. Therefore, it is inevitable for market participants to develop strategies for trading electricity and flexibility in these segments. The research conducted in this thesis aims to enable better decisions in short-term electricity markets. To achieve this, a multitude of quantitative methods is developed and applied: (a) forecasting methods based on econometrics and machine learning, (b) methods for stochastic modeling of time series, (c) scenario generation and reduction methods, as well as (d) stochastic programming methods. Most significantly, two- and three-stage stochastic optimization problems are formulated to derive optimal trading decisions and unit commitment in the context of short-term electricity markets. The problem formulations adequately account for the sequential structure, the characteristics and the technical requirements of the different market segments, as well as the available information regarding uncertain generation volumes and prices. The thesis contains three case studies focusing on the German electricity markets. Results confirm that, based on appropriate representations of the uncertainty of market prices and renewable generation, the optimization approaches allow to derive sound trading strategies across multiple revenue streams, with which market participants can effectively balance the inevitable trade-off between expected profit and associated risk. By considering coherent risk metrics and flexibly adaptable risk attitudes, the trading strategies allow to substantially reduce risk with only moderate expected profit losses. These results are significant, as improving trading decisions that determine the allocation of resources in the electricity system plays a key role in coping with the uncertainty from renewables and hence contributes to the ultimate success of the energy transition

System Architecture for Distributed Control Systems and Electricity Market Infrastructures.

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Liberalisation of European energy markets: challenges and policy options

The European electricity and gas markets have been going through a process of liberalisation since the early 1990s. This process has changed the sector from a regulated structure of, predominantly, publicly owned monopolists controlling the entire supply chain, into a market where private and public generators and retailers compete on a regulated and unbundled system of transport infrastructure. This report assesses the evidence of the effects of liberalisation on efficiency, security of energy supply and environmental sustainability.