Ahead of Print article · Journal article
A Bayesian inference approach to unveil supply curves in electricity markets
Department of Electrical Engineering, Technical University of Denmark1
Center for Electric Power and Energy, Centers, Technical University of Denmark2
Energy Analytics and Markets, Center for Electric Power and Energy, Centers, Technical University of Denmark3
CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark4
With increased competition in wholesale electricity markets, the need for new decision-making tools for strategic producers has arisen. Optimal bidding strategies have traditionally been modeled as stochastic profit maximization problems. However, for producers with non-negligible market power, modeling the interactions with rival participants is fundamental.
This can be achieved through equilibrium and hierarchical optimization models. The efficiency of these methods relies on the strategic producer's ability to model rival participants' behavior and supply curve. But a substantial gap remains in the literature on modeling this uncertainty. In this study we introduce a Bayesian inference approach to reveal the aggregate supply curve in a day-ahead electricity market.
The proposed algorithm relies on Markov Chain Monte Carlo and Sequential Monte Carlo methods. The major appeal of this approach is that it provides a complete model of the uncertainty of the aggregate supply curve, through an estimate of its posterior distribution. We show on a small case study that we are able to reveal accurately the aggregate supply curve with no prior information on rival participants.
Finally we show how this piece of information can be used by a price-maker producer in order to devise an optimal bidding strategy.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2017 |
| Pages: | 2610-2620 |
| ISSN: | 15580679 and 08858950 |
| Types: | Ahead of Print article and Journal article |
| DOI: | 10.1109/TPWRS.2017.2757980 |
| ORCIDs: | Pinson, Pierre |
Aggregates Bayes methods Bayesian inference approach Electricity supply industry Hidden Markov models Indexes Inference algorithms Markov chain Monte Carlo Markov chain Monte Carlo method Markov processes Monte Carlo methods Uncertainty aggregate supply curve day-ahead electricity market decision making decision-making tools hierarchical optimization models nonnegligible market power optimal bidding strategy posterior distribution estimation power markets power system economics price-maker producer pricing profitability rival participant behavior sequential Monte Carlo sequential Monte Carlo methods stochastic profit maximization problems stochastic programming strategic bidding tendering wholesale electricity markets
