1055. Comparing Risk Measures in Stochastic Equilibrium Energy Markets
Invited abstract in session TB-44: Equilibrium modelling in energy markets, stream Energy Economics & Management.
Tuesday, 10:30-12:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Dáire Byrne
|
| College of Business, University College Dublin | |
| 2. | Mel Devine
|
| University College Dublin |
Abstract
Owing to the energy transition, there is a heightened amount of stochasticity in energy markets. This causes firms to modify their behaviour to mitigate against risk, modelled with risk measures. The impact of implementing risk measures – such as conditional value-at-risk, stochastic dominance, or utility functions - into energy markets is underexplored in the literature. This work aims to address this gap for equilibrium energy markets. It considers an illustrative multi-player problem with market power. Players can purchase units at deterministic costs via a forward, or at stochastic costs from a pool. This leads to four mixed complementarity problems; one risk-neutral, one for each risk measure. The work analyses the impact of risk aversion numerically, assessing how retail prices and profits change. This provides insight into both risk aversion itself, and a lens with which to compare the risk measures. The work highlights how risk aversion interfaces with hedging instruments. Further, it provides an analysis of the computational costs associated with implementing each risk measure. Attention is paid to recasting the MCPs to equivalent convex optimization problems; computational advantages of doing so are detailed. Finally, the work incorporates real data into a related model. With energy market models informing policy and investment decisions and stochasticity continuing to heighten, it is crucial that a deeper understanding of the impact of risk aversion is developed.
Keywords
- OR in Energy
- Electricity Markets
- Risk Analysis and Management
Status: accepted
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