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Excessive price reduction and extreme volatility in wind dominant electricity markets; solutions and emerging challenges
High intermittency in the nature of wind power emphasize conceptual revising in the mechanisms of electricity markets with high wind power penetration levels. This paper introduces overmuch price reduction and high price volatility as two adverse consequences in future wind dominant electricity markets. While high price volatility imposes elevated risk levels for both electricity suppliers and consumers, excessive price reduction of electricity is a disincentive for investment in new generation capacity and might jeopardizes system adequacy in long term. A comparative study between marginal to discriminatory pricing mechanisms are conducted in this paper. This particular direction has been chosen because the discriminatory approach is traditionally known for lowering price volatility while gently increasing average price. To this end an adaptive agent based simulator under two pricing mechanisms is developed. The paper indicates discriminatory pricing approach can be beneficial in high penetration of wind power because it alleviates high price variations and spikiness in one hand and prevents overmuch price reduction in wind dominant electricity markets on the other hand.
- IT University of Copenhagen Denmark
- École Normale Supérieure France
- Aalborg University Denmark
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
