12 de diciembre de 2022
Resumen:
Gas Fired Units (GFUs), especially Combined Cycle Gas Turbines (CCGTs), will play an essential role in the transition to the decarbonization of the power industry. One of the fundamental problems faced by a Generation Company (GenCo) with GFUs is known as the Unit Commitment (UC) problem, and as it affects its own generation, this problem is also known in the literature as self Unit Commitment (self-UC). The UC is one of the most studied problems in the power systems literature, consisting in deciding the commitment status of the generation units. The UC is critical because the units take a minimum time to start up and shut down so that the commitment state in a given hour is linked to the surrounding periods, whereas with a unit already connected, varying the load level from one hour to another is more flexible. In particular, the correct modeling of GFUs is vital in deregulated market environments organized as marginal markets since, in most situations, this type of units is decisive for the resulting market cleared price.
The GFUs have an added complexity not applicable to other thermal units such as coal or nuclear, that is receiving their fuel supply through a gas network. This gas network is in some ways analogous to the electricity network, but it has its own characteristics that need to be considered for the GFUs operation. The gas network has a Transmission System Operator (TSO) in charge of its operation. This operation entails associated costs that the TSO passes on to the gas network users through the so-called Third Party Access (TPA) tariffs. From the point of view of a GenCo that owns GFUs and participates in the electricity market, two fundamental issues must be considered concerning the fuel supply for its units: the TPA tariffs that must be paid to extract gas from the network at the power plants where the GFUs are located, and the available options to acquire the gas. Regarding gas procurement, there are mainly two options, bilateral contracts with suppliers and purchases in gas spot markets. Irrespective of whether the company has bilateral agreements with suppliers, if it operates in an area with a sufficiently liquid gas spot market, the price of that market will be its supply cost. On the one hand, if the GenCo buys on the gas spot market directly, that price is the cost for the GFUs. On the other hand, if it has bilateral contracts, the market price becomes the opportunity cost of using the gas already acquired for electricity generation as an alternative to selling that gas to the spot market.
Another aspect to consider that is usually simplified is the tax scheme to which the generation units are subject. Taxes are part of the generation units operating costs. A careful review of current taxation systems shows different tax types. For instance, taxes charge concepts such as the energy generation [e/MWh], the market revenue [market price percentage] or greenhouse gas emissions [e/ton]. Additionally, these taxes can differ depending on the technology used to generate electricity (coal, gas, hydro, nuclear, etc.), and even they can depend on geographical areas belonging to the same market. These possible differences make it essential to model them in detail to take them into account correctly.
Finally, as in any other market, agents are expected to try to maximize their expected profits. In an environment with perfect competition, this situation requires no additional consideration. However, when the number of GenCos is reduced, there are specific regulations aiming to limit possible strategic behaviors of dominant players. In the case of the power sector, those rules have widely been implemented; therefore, agents participating in the electricity market need to account for such regulation in their own planning.
Considering the vital role that GFUs will continue to play in the future, the need to solve the lack of state-of-the-art models to address issues that significantly affect the real operation of these units in the market becomes essential. Therefore, this thesis begins by explaining in detail the problems briefly presented in this summary, starting with a detailed review of how the gas system works, focusing on TPA tariffs in the European Union. In addition, it also reviews the different taxes applied to the electricity generation activity and how these problems are tackled in the optimization modeling literature.
These issues were not found in the literature on the short-term self-UC optimization models, which are the tools GenCos use in their day-to-day operation planning. Additionally, the relevance of the TPA consideration, that accounts for more than 10% of the total operation cost, has been confirmed by our own experience in collaborations with the industry. Therefore, several modeling improvements have been developed and are proposed in this document. The different chapters present several models with their respective case studies to demonstrate their usefulness in the subjects they address. They are not specific models for each one of the issues but instead represent the different improvements that would have to be implemented to cover each of the concepts discussed, and they could, in fact, be integrated. Chapter 3 proposes modeling TPA tariffs and gas purchases at the portfolio level. Chapter 4 offers a model that represents the individual revenues of each unit to correctly consider its taxes and the possibility that different agents share the ownership of generation assets. Lastly, Chapter 5 presents two different approaches to limit the strategic behaviors that could result from applying the models found in the literature.
The thesis’s objective is general, and therefore, the developments presented are not only valid for a GenCo operating CCGTs in a specific country. The improvements in the representation of gas are based on European regulation (whose objective is similar to that of other countries), and those related to income modeling are extensible to other generation technologies. In fact, the correct tax representation gains importance when the portfolio has several technologies subject to different levies. Finally, regarding the potential users of the proposed models, it is clear that GenCos find a direct application in planning their own operation. In addition, they are also helpful tools for regulators or System Operator (SO), providing them with the means to simulate and study the expected behavior of the agents participating in the market.
Finally, three appendices are presented with the objective of providing all the necessary tools to optimize the self-UC with GFUs. The first appendix is dedicated to the UC modeling and how to take uncertainty into account by using stochastic programming. The second appendix presents the formulation changes that should be implemented in case of having CCGTs with multiple configurations of gas and steam turbines. Such consideration is thought to be valuable since this type of unit is very common in the industry. Finally, the third appendix presents an example of how to run a self-UC optimization model in a cloud computing environment, a standard that is gaining traction in the industry.
Resumen divulgativo:
Mejora modelos de self-UC desde el punto de vista de una GenCo propietaria de CCGTs: acceso a red de gas, compra de gas considerando impacto en precio, esquemas impositivos, unidades con propiedad compartida entre agentes, y reducción de comportamiento estratégico para agentes con poder de mercado.
Descriptores: Ingeniería y Tecnología Eléctricas
Palabras clave: ciclo combinado (CCGT), mercado eléctrico, mercado de gas, maximización de beneficio, comportamiento estratégico, esquema impositivo, propiedad compartida, acceso de terceros a la red (ATR), unit commitment (UC)
Cita:
P. Otaola-Arca (2022), Optimal self-unit commitment of combined cycle power plants. Bridging the gap between the state of the art and current regulation of electricity and natural gas markets. Madrid (España).
