Models and methods for electricity and gas markets in a low-carbon economy

Human activity is overloading the atmosphere with carbon dioxide and other greenhouse gas emissions, which trap heat and drive up the planet temperature, resulting in a negative impact on our health, environment, and climate. Governments are considering actions to curb climate change that will significantly change both electricity and gas markets. This thesis detects these issues and proposes models and methods to analyze how electricity and gas markets can contribute to the achievement of the decarbonization targets. Among the actions carried out to reduce carbon emissions, renewable energy penetration is the most effective one. However, the integration of wind and solar power plants in electric energy systems is extremely challenging because of the uncertainty and variability that characterize their electricity production. To accommodate the stochasticity of the renewable energy production, power systems need to be more flexible. This flexibility is provided by backup capacity in the form of reserves, which are provided by dispatchable units such as thermal plants, or batteries and storage devices, which represent an environmentally friendly solution. Considering this framework, in the first part of this thesis, two expansion planning models to efficiently integrate renewable power plants, storage units, and electric vehicles in electric energy systems are proposed. We first want to detect which are the investment choices that have to be taken by a Market Operator to deeply decarbonize electric power system. To this aim, we propose a two-stage stochastic programming model to determine the optimal mix of generation and transmission capacity to build, taking into account both technical constraints and climate-related considerations. The model uses a mix of ac and high-voltage dc transmission lines, conventional and renewable generation, and energy-storage units to meet these objectives. Short- and long-term uncertainties are modeled using operating conditions and scenarios, respectively. Secondly, we take the view of a Distribution System Operator and we propose a stochastic adaptive robust optimization approach for the expansion of a small size electricity system problem. This involves the construction of candidate renewable generating units, storage units, and charging stations for electric vehicles. In this case, long-term uncertainty is modeled using confidence bounds, while short-term uncertainty is represented through a number of operating conditions. Gas-fired power plants represent the energy choice that can help to achieve a secure, competitive, and decarbonized power systems since they can significantly contribute to emissions reduction by replacing high carbon fuels in electricity generation. In addition, these units are the ideal partner for variable renewable energy, providing backup to wind and solar. In the last years, Europe has taken the lead in the decarbonization policies and has imposed a strict carbon reduction target that has to be achieved by 2050. For all these reasons, in the second part of the thesis, we focus our attention on the European gas market and we detect two important issues that can affect its stability. The first one regards the re-negotiation of the long-term gas contracts invoked by European mid-streamers and the second one concerns the security of external supply. The need of re-negotiation arises from the fact that, in Europe, gas is sold according to two main methods: oil-indexed long-term contract and hub pricing. The fall of the European gas demand combined with the increase of the US shale gas exports and the rise of liquefied natural gas availability on international markets have led to a reduction of the European gas hub prices. Since oil-indexed long-term contracts have failed to promptly adjust their positions, European gas mid-streamers asked for a re-negotiation of their existing contracts to obtain new contracts linked to hub spot prices. In this thesis, we tackle this problem by estimating the dependence risk and the optimal resource allocation of the underlying assets of a gas long-term contract through pair-vine copulas and portfolio optimization methods, using different risk measures. We also investigate the risk of external supply because Europe mainly relies on imports from economically or politically unstable countries to cover it gas demand since the local production is very limited. The analysis of the external supply risk is focused on the Italian gas market whose demand is covered by 90% by imports from foreign countries. An optimization problem that describes the equilibrium state of a gas supply chain, where producers, mid-streamers, and final consumers exchange natural gas and liquefied natural gas both with long-term contracts and on spot markets is developed for this purpose.