Integrated Hydrogen-Electricity Market Design

Integrated Hydrogen-Electricity Market Design: The effect of risk aversion and the use of capacity remuneration mechanisms

Berdin, Alessio (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Energie and Industrie)

De Vries, Laurens (mentor)
Bruninx, K. (mentor)
Correljé, A. (graduation committee)

Delft University of Technology

Electrical Engineering | Sustainable Energy Technology

2023-08-28

The decarbonization of the energy system is driven by the electrification process and the expansion of variable renewable energy capacity. Green hydrogen, produced through electrolysis powered with renewable electricity, represents a major complementary vector that can support this transition. By enabling long-term storage, it addresses the challenges arising from the unpredictability of a renewable energy-based electricity system. It represents a backup and increases the reliability of the electricity system.

In an interconnected decarbonized system where energy carriers are interdependent, new sector-coupling dynamics emerge. Energy-only markets, in theory, yield socially optimal levels of installed capacity across both sectors assuming rational participants and perfect markets. However, risk-averse behaviour among market participants might lead to underinvestment in generation capacity, undermining the efficacy of hydrogen backup.

The main objective of this research is to assess the adequacy of market designs in attracting socially optimal levels of investment in electrolyzers and storage capacity within a decarbonized and integrated system with risk-averse agents.

The stylized stochastic equilibrium model formulated is solved by using the Alternating Direction Method of Multipliers algorithm. Participants formulate their strategy based only on market prices, which are influenced by 18 scenarios that differ in terms of electricity demand, hydrogen demand and variable renewable energy sources availability. The demand for electricity and hydrogen is considered price-elastic.

An energy-only market, an energy market supported by a capacity market for electricity generators, and an energy market supported by capacity markets for both electricity and hydrogen generators are tested under different degrees of risk aversion.

The analysis confirms how risk aversion, by increasing the risk premium required, entails a reduction in installed capacity. Underinvestment is combined with a general reduction in the served energy and an increase in energy prices and frequency of periods of high prices. These trends are more considerable in the hydrogen market, where agents are exposed to risk from the uncertainties in both hydrogen demand and electricity prices.

The energy-only market is more sensitive to the impact of risk aversion due to the absence of risk trading opportunities. In this case, the increase in energy prices is the only solution to recover the risk premium.
Introducing a capacity market for dispatchable electricity generators mitigates the impact of risk aversion in the electricity sector. However, this exacerbates performance issues in the hydrogen market during scarcity periods by amplifying hydrogen price fluctuations. On the other hand, incorporating a capacity market for hydrogen counteracts the effects of risk aversion on the hydrogen sector. This dual approach not only benefits the hydrogen sector but further improves the electricity sector’s adequacy and reduces consumer costs.

Capacity markets are an effective instrument to hedge risk, but their application in an integrated system has to be consistent and include both electricity and hydrogen generation capacity. Furthermore, the strong dependence of hydrogen generation on electricity prices advocates for a direct instrument to hedge risk for renewable generators such as contracts for difference, as an adequate vRES capacity improves the whole system’s performance by reducing hydrogen prices and increasing its availability.

Energy Systems
Capacity Market
Green Hydrogen
Risk Analysis

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Student theses

master thesis

© 2023 Alessio Berdin