Electrification by means of renewable energy sources in electricity production (RES-E) is a key strategy to meet global climate goals established in the Paris Agreement. The increasing share of RES-E as a result of this has significant implications on the functioning of the electricity system and the adequacy of the electricity market design, as these technologies exhibit different characteristics compared to conventional generators. Their intermittent output combined with near negligible marginal costs has an effect on electricity price formation and will lead to an increased demand for flexibility services to level out these fluctuations. These trends will induce an increased investment risk for flexible generation capacity. This increased investment risk feeds into the risk-averse behaviour of investors that is already present due to market failures that exist in electricity markets. It remains unclear whether the liberalised neoclassical electricity market design provides sufficient incentives to invest in generation capacity in order to maintain system adequacy during the energy transition.
One possible market design option that is proposed to address this increased investment risk are Capacity Mechanisms. Capacity Mechanisms allow for an adequate remuneration of (flexible) generation capacity, by providing a steady income stream to firm capacity on top of revenues obtained from selling electricity. The purpose of this thesis is to evaluate the effectiveness of a capacity market - a specification of a capacity mechanism - in maintaining system adequacy in a system with an increasing share of RES-E. Additionally, it aims to fulfil the need for electricity system models that allow for performing robustness analysis as this it is seen as increasingly important to adequately account for uncertainty that is inherently related to the unfolding of the energy transition. This research was carried out by extending an existing quantitative model of the Dutch electricity system, referred to as Myopic Optimisation Detailed Operational (or MODO), with a capacity market. The methodology applied relies on myopic optimisation.
Conceptualisation of the capacity market model is based largely on the design of the NYISO Installed Capacity Market (NYISO-ICAP), as this design is relatively simple whilst being considered a successful capacity market. A thorough literature review on the NYISO-ICAP was performed to establish a profound understanding of real-world capacity market dynamics and how these can be translated to the model. The conceptualisation of the capacity market forms a basis for formalisation and is used to establish the formal rules of the capacity market model complying with the basic structure of linear programming problems. This serves as input for the implementation of the extension of the capacity market in MODO, and thus in Linny-R.
With the resulting model, the effectiveness of a capacity market in maintaining system adequacy was assessed on the performance of several Key Performance Indicators. These encompass the Supply Ratio, the average annual volume of Energy-not-Served [MWh], the average Electricity Price [€/MWh] and the total Consumer Spending [€]. A comparative analysis was performed between the performance of the energy-only market and the capacity market on the identified Key Performance Indicators in four pre-specified scenarios. The four scenarios are varied on key uncertainties underlying the unfolding of the energy transition to explore the robustness of results, such as weather conditions and the level of risk aversion of investors.
From this thesis, it can be concluded that a capacity market can be an effective and robust policy instrument to maintain system adequacy during the energy transition at a lower cost to consumers. This can specifically be seen in the increased number of investments in peaking generators compared to the energy-only market when forecasted revenues of the capacity market are sufficient, which has a positive effect on the electricity system's robustness to different weather conditions. Furthermore, when the level of a risk aversion of investors is high, a capacity market is more robust in ensuring system adequacy compared to an energy-only market.
Nonetheless, a capacity market can be prone to investment cycles which can have a negative influence on the effectiveness of a capacity market to maintain system adequacy at all times. These investment cycles are a result of the bounded rationality and myopia experienced by investors, ultimately leading to imperfect forecasting of the revenues of the capacity market. Results of this thesis have shown that in busts of investment cycles, investments in generation capacity can be insufficient to maintain system adequacy.
To conclude, a capacity market can be a viable option in order to maintain system adequacy in the energy transition. However, whether it is the most suitable option to maintain system adequacy is not clear. Novel flexibility options such as storage could potentially serve a significant role in maintaining system adequacy. If additional flexibility options have a lower perceived investment risk compared to flexible generation units, the electricity market can potentially continue to rely on its initial liberalised neoclassical market design whilst maintaining system adequacy. This requires further exploration in future research.
Furthermore, MODO and its capacity market extension fill the need for electricity system models that allow for performing robustness analysis, as it has a relatively low computation burden. Hence, an interesting avenue for future research is to evaluate the effectiveness of a capacity market in many possible futures.