The energy transition and the value of Capacity Remuneration Mechanisms

Capacity Remuneration Mechanisms (CRMs) can be introduced in power markets to address market failures and ensure security of supply. However, investment in capacity is a dynamic process that depends on the evolution of prices and costs over time. In this paper, we investigate the value of capacity u...

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Veröffentlicht in:Energy economics 2024-11, Vol.139, p.107882, Article 107882
Hauptverfasser: Bonaldo, Cinzia, Fontini, Fulvio, Moretto, Michele
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Sprache:eng
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Zusammenfassung:Capacity Remuneration Mechanisms (CRMs) can be introduced in power markets to address market failures and ensure security of supply. However, investment in capacity is a dynamic process that depends on the evolution of prices and costs over time. In this paper, we investigate the value of capacity under a CRM using a stochastic approach. We focus on three possible technologies participating in the market: a Variable Renewable Energy source, a thermal efficient power plant (such as a Combined Cycle one) and a coal-fired power plant. These three types of capacities can be framed within a common theoretical framework with an increasing level of complexity. We first present analytical models and then provide sensitivity analysis and calibration results. Our findings indicate that for all three technologies, the effect of the CRM is to cap the firm revenues and consequently to decrease their value. Moreover, the calibration provides a ranking of investments such that carbon emitting plants, in particular gas-fired ones, display higher values compared to renewable ones. •Investment value in power generation with a Capacity Remuneration Mechanism is studied.•Three technologies are considered: Renewables, gas-fired and coal power plants.•Uncertainty on power prices, technology and quantity risk is considered.•The model is calibrated using Italian power market, fuel and emission cost data.•Capacity remuneration mechanisms lead to investment rankings incompatible with energy transition.
ISSN:0140-9883
DOI:10.1016/j.eneco.2024.107882