Logo EEM11
 
 
Session
Session 09: Structure of Electricity, Gas and Oil Markets
Time: Thursday, 26/May/2011: 11:30am - 1:00pm
Session Chair: Wladyslaw Mielczarski
Location: Casino

Presentations

Analyzing Market Power in a Multistage and Multiarea Electricity and Natural Gas System

Stephan Spiecker

University of Duisburg-Essen, Germany

Strategic behavior by gas traders is likely to affect future gas prices. Within this article a computational game theoretic model is presented which allows assessing market power on the natural gas market and its influence on the electricity market. This model uses typical time segments to represent both seasonal load fluctuations on the natural gas market and hourly load fluctuations on the electricity market. An application is presented covering 40 regions and simultaneously optimizing dispatch and utilization of transmission lines on the power market as well as supply, transmission and storage on the natural gas market. The model is used to evaluate the influence of trader market power in the natural gas market on the electricity market. We compute price changes, sales volume and power plant utilization for three different market power specifications.


Development of a Model for Short-Term Load Forecasting with Neural Network and its Application to the Electrical Spanish Market

Miguel Lopez1, Sergio Valero1, Carolina Senabre1, Juan Aparicio2, Antonio Gabaldon3

1Dpto. de Ingenieria de Sistemas Industriales. Area de Ing. Eléctrica Universidad Miguel Hernandez de Elche, Spain; 2Centro de Investigación Operativa; 3Universidad Politécnica de Cartagena

The study presented in this paper used Kohonen’s Self-Organized Maps, which is one of the more uncommon techniques based on neural networks in load forecasting. The aim of this study is not only to show that this technique is capable of producing accurate short-term load forecasting results which should not be neglected, but also to provide a deep and thorough analysis of these results in order to extract solid conclusions about the inner design of the network, the selection of variables and also about the training periods. In addition, an application for the Spanish electricity market is developed.


A Medium-Term Operation Model for a Natural Gas System

Pablo Dueñas, Javier Reneses, Julián Barquín

Institute for Research in Technology (IIT), Advanced Technical Engineering School (ICAI), Comillas Pontifical University, Spain

During last decades, consumption of natural gas has been continuously increasing worldwide. Hence, infrastructure has been developed to transport the natural gas from the well to the final consumer. Natural gas chain value can be segmented in upstream and downstream sectors. The organization of the upstream sector is similar to that of the oil sector, whereas the organization of the downstream sector resembles much that of the electricity sector. The frontier between both sectors is usually placed in the international borders. Specifically, the operation model focuses on the downstream sector. The supply activity and the utilization of the different infrastructure such as the liquefied natural gas terminal or the storage facilities are considered. The upstream sector is not completely ignored as it is characterized in the supply activity. The operation model can be a support for taking decisions in the medium term on behalf of involved companies in the gas market as illustrated by the case study.


European Balancing Markets

Enrique Israel Rivero, Julián Barquín, Luis Rouco

Institute for Research in Technology, Spain

Balancing markets are critical for the operation of power systems. TSOs use these markets for the acquisition of the resources needed for the balance between generation and demand on real-time (minute-to-minute operation). Balancing markets, since their beginning, were conceived to cope with real-time operation issues such as forecast errors on generation/demand and unplanned power outages due to a fault on generation units or transmission facility. Today, balancing markets are facing new challenges. One of them is the incorporation of a considerable amount of intermittent renewable generation on the generation mix, which could impose an increase on the volumes traded on balancing markets in order to ensure the correct performance of the system. Another issue is the tendency of displacing national energy markets by regional markets within which multi-area Day-Ahead trading is managed. This article presents the current designs of several European balancing markets, i.e. The Belgian, Swiss, German, Danish, Spanish, French, Italian and Dutch balancing markets. Since control reserves vary from one system to another, this article first presents a classification of the control reserves used within the surveyed systems. From the classification we proceed to the comparison of the assessment, remuneration (methods and structure), and cost recovery for secondary and tertiary reserves applied by each TSO.


The Puzzle of Asymmetric Effects of Oil: New Results from International Stock Markets

Sofia Ramos1, Helena Veiga2

1ISCTE-Lisbon University Institute; 2Universidad Carlos III de Madrid

Previous work has documented that oil price changes have nonlinear effects in the economy and in stock market returns. We show that the nonlinear effects are different depending on whether countries are energy dependent or not. While price soars seem to have a negative effect on the stock markets of oil energy dependent countries, they have a positive effect on the stock markets of oil exporting countries. Stock market returns are negatively affected by oil price volatility in energy dependent countries and positively in oil exporting countries. The asymmetric effects found in oil dependent and oil exporting countries seem to fit into the offset mechanism proposed in the literature where oil price shocks interact both with oil price volatility and the economy. The results are also consistent with the finding that oil exporting countries benefit economically from oil price hikes.


Gas Network Topology Optimization for Upcoming Market Requirements

Armin Fügenschuh, Benjamin Hiller, Jesco Humpola, Thorsten Koch, Robert Schwarz, Thomas Lehmann, Jonas Schweiger, Jacint Szabo

Zuse Institut Berlin, Germany

Gas distribution networks are complex structures that consist of passive pipes, and active, controllable elements such as valves and compressors. Controlling such network means to find a suitable setting for all active components such that a nominated amount of gas can be transmitted from entries to exits through the network, without violating physical or operational constraints. The control of a large-scale gas network is a challenging task from a practical point of view. In most companies the actual controlling process is supported by means of computer software that is able to simulate the flow of the gas. However, the active settings have to be set manually within such simulation software. The solution quality thus depends on the experience of a human planner. When the gas network is insufficient for the transport then topology extensions come into play. Here a set of new pipes or active elements is determined such that the extended network admits a feasible control again. The question again is how to select these extensions and where to place them such that the total extension costs are minimal. Industrial practice is again to use the same simulation software, determine extensions by experience, add them to the virtual network, and then try to find a feasible control of the active elements. The validity of this approach now depends even more on the human planner. Another weakness of this manual simulation-based approach is that it cannot establish infeasibility of a certain gas nomination, unless all settings of the active elements are tried. Moreover, it is impossible to find a cost-optimal network extension in this way. In order to overcome these shortcomings of the manual planning approach we present a new approach, rigorously based on mathematical optimization. Hereto we describe a model for finding feasible controls and then extend this model such that topology extensions can additionally and simultaneously be covered. Numerical results for real-world instances are presented and discussed.