On the Need, Impact, and Design of Capacity Remuneration Mechanisms

In theory, electricity spot markets provide social optimal levels of capacity assuming ideal conditions,  i.a., rational market participants acting on perfect and complete markets. However, concerns of several authorities and scientific literature suggest that market participants might act risk-averse or strategically rather than perfectly rational. Additionally, several authorities introduced price caps on the electricity markets to mitigate price risks for consumers. These factors can weaken the investment incentives and could, therefore, cause underinvestments in generation capacity. To counteract underinvestments and to secure generation adequacy, capacity remuneration mechanisms (CRMs) can be implemented. However, as CRMs can impose market distortions if tuned faulty, they sometimes are considered controversial. 

The main question of this dissertation is how demand elasticity, risk aversion, and strategic investment behavior affect the need, impact, and design of capacity remuneration mechanisms in the long-term equilibrium of electricity systems. This dissertation primarily focuses on market distortions due to risk aversion, but also touches upon strategic behavior. To address this question, it is subdivided into four objectives. Considering ongoing developments that render the electricity demand elastic, the necessity of CRMs can be questioned. Therefore, the first objective is to evaluate the need for CRMs if the electricity demand becomes short-term elastic.  The results of a stylized analysis suggest that short-term electricity demand elasticity can even amplify the negative effect of risk aversion on the energy-only market in the long-term equilibrium. A capacity market can be used to hedge against the negative effects of risk aversion, even if the capacity target is not set ideally. Furthermore, it is shown that a capacity market can be used to mitigate welfare transfer to investors and lower the loss of load expectation induced by risk aversion.

As no consensus about the principles of robust tuning of capacity demand curves exists, the second objective is to compare different design methodologies for capacity demand curves. To this end, it is shown that the choice of the capacity demand curve of a CRM is dependent on the anticipated uncertainty. If necessary parameter estimations are certain, a capacity demand curve, which is defined with the net cost of new entry at  the reliability target, performs socially optimal. Anticipating erroneous parameter estimations on the value of lost load and the degree of risk aversion, a conservatively tuned marginal reliability impact-based curve provides higher protection against elevated costs.

In principle, risk aversion can resemble strategic investment behavior. Hence, the third objective is to disentangle both types of behaviors. In this regard, a stylized analysis is conducted confirming that strategic investment behavior can lead to the same market outcomes as risk-averse investment behavior. It is shown that the distinguishability of the two types of behavior is highly technology-dependent and influenced by the way the capacity target is set.

To improve the usability of equilibrium problems, the last objective is to lay a foundation for a generic framework for equilibrium models. Therefore, the so-called ELDEST framework is developed. The framework constitutes a solid base for future studies connected to generation expansion planning in energy markets. A proof of concept illustrates the executability but also presents features such as dynamic decision making and flexibility in the choice of solution mechanism and the consideration of different types of agents.