Mechanism Design for Electricity Markets Under Uncertainty

Download or read book Mechanism Design for Electricity Markets Under Uncertainty written by Javad Khazaei and published by . This book was released on 2012 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we investigate the effects of the electricity market clearing mechanisms on the cost of integrating intermittent resources such as wind. We present a linear supply function equilibrium model of a conventional two settlement electricity market clearing mechanism. We then provide examples of markets for which large-scale wind integration can increase steady state cost of generation and decrease expected social welfare. These counter-intuitive examples lead us to analyse in depth mechanisms that appear to efficiently cater for uncertainty. Recently an alternative so-called stochastic settlement market has been proposed (see e.g. Pritchard et al. [80] and Bouffard et al. [30]). In such a market, the ISO co-optimizes pre-dispatch and spot in one single settlement market. By considering all possible demand realizations ahead of time, pre and spot dispatch is deemed to be scheduled more efficiently. In this thesis we consider simplified models for both stochastic settlement and conventional two settlement market clearing mechanisms. Our models are targeted towards analyzing imperfectly competitive markets. We demonstrate that the stochastic settlement market clearing mechanism can always outperform the two settlement mechanism for symmetric generators. However, we also present an example of an asymmetric market in which, contrary to intuition, the two settlement mechanism yields higher social and consumer welfare in equilibrium. Even though the stochastic settlement mechanism outperforms the two settlement mechanism most of the time, implementing such a system requires extra costs. Thus, we also present results of an empirical study to estimate the value of the stochastic settlement mechanism for New Zealand electricity market. We extend our analysis to hypothetical wind investments in the future.