Dynamic optimisation of price arbitrage techniques

Recent innovations introduced in the electric power system, especially the significant usage of unpredictable renewable energy sources, are making to perform the needed matching of generated and absorbed electricity more difficult than in the past. To facilitate this matching, market regulation can provide economical drivers that stimulate cost-effective energy shifting by the so-called 'prosumers' or the owners of energy storage devices. Price arbitrage, for instance, means to absorb energy when its price is low, and delivering it when is higher. To enhance the revenues achieved with this kind of operation, proper control techniques based on solving a Dynamical Optimisation problem can be considered. This paper will study price arbitrage techniques taking advantage of Modelica language description of the system, that allows easy and fast approach in modelling and also in using dynamical optimisation algorithms. The arbitrage opportunities and the optimal operational strategies will be studied considering different storage sizes and price patterns. Comparison of several strategies will be analysed, discussed and validated using an ad-hoc mixed-integer optimization program whose validity has already been widely checked in previous studies.