On Distributed Balancing of Wind Power Forecast Deviations in Competitive Power Systems

Wind power generation does, on the one hand, contribute to a less polluting and more sustainable electric power generation mix. On the other hand, the uncertainty and the variability of the power output do challenge the operation of the power system: hourly variations in wind power generation are hardly predictable in a precise way. To decrease the need for balancing power, it might be beneficial from the overall system-perspective to subject power generating companies to stricter balancing incentives/rules.The way the market is designed has become crucial to exploit the existing flexibility in the power system and to increase the efficiency in its operation: inappropriate market designs can counteract all technical achievements. The work conducted for this thesis is embedded in a project on wind power integration and electricity market design following the aim to develop a simulation tool to analyse the consequences of changes in specific market rules.This thesis analyses wind power variations and forecast errors in the Swedish power system and explores the question whether internal ex-ante self-balancing can efficiently reduce the need for balancing power. Applying internal ex-ante self-balancing, every power generating company re-schedules its own power plants in order to balance its commitments towards other market actors with its newest production forecast. This is done shortly before the hour of delivery.To assess the value of this self-balancing, possible trading and scheduling decisions for power generating companies are modelled based on a hydro-thermal generation portfolio within the framework of the Nordic electricity market design. The model is based on a sequence of mixed-integer linear optimisation problems for the clearing of the different sub-markets. Both the data and the model have an hourly time resolution. In a case study, the model is applied on a simplified test-system. The need of real-time balancing by the transmission system operator, the total variable generation cost of the system, as well as the extent to which the power generating companies re-scheduled their production are then used as indicators to evaluate self-balancing.

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