Long-term Scheduling of Hydro Power Systems in Multiple Markets
MetadataShow full item record
- Institutt for elkraftteknikk 
Hydropower scheduling models are vital for achieving an optimal utilization of water stored in reservoirs. The high percentage of flexible hydropower generation in Norway has led to scarce volumes in the reserve markets, thereby little focus on developing models for generation in multi markets. Recent year's developments in both the political and energy sector, with stronger interconnections in the transmission grid and growing renewable generation, has led the energy producers to evaluate other markets for their electricity supply. The motivation for this thesis is to investigate the influences a detailed hydropower scheduling model imposes for capacity reservation in a medium-term scope. Two models were developed; first a Strategy Model, based on Stochastic Dual Dynamic Programming (SDDP), was applied to generate a strategy that connects the time-stages in the model. Secondly a Simulator Model were developed, described by a detailed description of the hydropower system properties, that utilized the strategy obtained by from the Strategy Model. A detailed elaboration of both models was carried out before they were tested on a realistic case study coordinated with Lyse Produksjon AS. A great amount of work was invested in literature studies of hydropower scheduling models in general and the SDDP algorithm in particular. Moreover, model enhancements of the Strategy Model and development of the Simulator Model contributed considerably to the work load. A run with the Simulator Model, where the models had access to a day-ahead market and the primary market for weekly FCR-N capacity reservation, resulted in a 2.48% reduction of expected profit, compared to the Strategy Model. In the Simulator Model the expected profit from capacity reservation was also reduced by 52% compared to the Strategy Model. The results of this study has indicated that a more detailed modelling, including enhanced power station modelling, when considering capacity reservation is of importance.