| dc.description.abstract | In this master thesis, the main focus has been to create an optimization model for an energy storage unit to consider the potential of storing energy for future use, when also operating in both the energy and balancing markets. The main goal was to successfully implement this model and study the potential of a storage unit maximizing profit within both markets, and how this affects the scheduling of the storage unit for varying storage capacity.
The whole model is split into different phases. It consists of a model setup in which the optimization problem is defined, and has a two-step solution procedure to analyze the given input scenarios. It will first execute the strategy phase to calculate storage values for each possible deterministic scenario which are weighted based on the stochastic probability, and then simulate a sequential performance in the simulation phase.
The results for a deterministic setup showed that the model manages to create a detailed storage value curve when the number of discretized points are kept at a reasonable amount. This also kept the accuracy of the simulation phase reasonably good. However, the accuracy and performance of the strategy phase struggled to be consistent when the capacity of the storage unit increased. This deviation decreased when changing to a stochastic setup, since all possible scenarios affected each other, and several of these scenarios performed better when the price variation increased.
In overall, the storage unit scheduling model has shown good performance and can be a useful option for analyzing storage units from a stochastic point of view when considering multiple markets. | |
