OPTIMUM BIDDING STRATEGY FOR HYDRO, WIND AND SOLAR POWER PLANTS IN DAY AHEAD ELECTRICITY MARKET

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2021-9-08

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Özcan, Mehmet

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The main challenge related to the trade of electricity from renewable energy sources is their intermittency due to stochastic nature of their generation output. This leads to the imbalance cost in day ahead markets (DAM) and raise the concerns for collaboration. There are 2 possible strategies for wind power plants (WPPs) and solar power plants (SPPs) to maximize their income in day ahead markets (DAM) in the presence of imbalance cost: Joint Bidding (JB) via collaboration by participating to balancing groups and deployment of storage technologies. There are limited studies in the literature covering the comparative analysis of “collaborative joint bidding strategy” with “battery deployment strategy”. In the existence of balancing responsibility, the comparative analysis of these strategies is the main contribution of this study to the literature. Second contribution is the analysis of the impact of different regulatory regimes, which are set by the regulatory authority, on total income. JBM (Joint Bidding Model), which is the model for joint bidding via different collaboration groups, is developed for the analysis of first strategy, BDM (Battery Deployment Model), which is the model covering the deployment of storage technology, is developed for the analysis of second strategy. The impact of each strategy on total income is analyzed. According to the analysis of the results of the models, while the first strategy, which is sensitive to the regulatory regime, increases the total annual income of the collaboration groups up to 1,38%, second strategy seems not feasible and financially viable. On the other hand, extra income values per MW of battery for SPP is between $218 and $400 /MW-year, while these values are between $2.460-$6.795/MW-year for the group of 15 WPPs. Therefore, deployment of battery for WPPs creates extra income more than 10 fold of that of SPP. Second strategy can be viable if the levelized cost of deployment of battery drops below the extra income values achieved per MW of battery.

Subject Keywords

trade of renewable energy; day ahead electricity market; optimum bidding; optimization

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https://hdl.handle.net/11511/94261

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. Özcan, “OPTIMUM BIDDING STRATEGY FOR HYDRO, WIND AND SOLAR POWER PLANTS IN DAY AHEAD ELECTRICITY MARKET,” Ph.D. - Doctoral Program, Middle East Technical University, 2021.