Posters

Abstract

The energy transition towards the decarbonization of the economy implies changes in the power system with an increasing penetration of renewable resources and a gradual withdrawal of synchronous plants. This context requires solutions that ensure the electricity supply and the whole system flexibility, reliability and resilience. One of these solutions is the hybridisation. It allows combining generation and/or energy storage technologies to increase the annual capacity factor, to maximise the primary resources utilisation (solar, wind), to improve the manageability of intermittent renewable resources when combined with storage, to obtain higher incomes by means of dispatching in multiple markets, including the more profitable (but exigent) ancillary markets, and to optimise the use of the existing network infrastructures without extra investments. However, to achieve all these benefits, utilities must execute important investments in assets with huge capital costs (such as batteries or electrolysers) finding the optimum investment time according to the existing regulation, the decreasing costs and the funding associated to Research and Development programs. Once the hybrid plant has been commissioned, utilities should optimize both its technical operation (Operating and Management O&M department) and its economic exploitation (Energy Management department). For this purpose, the application of dynamic and integrated operational strategies with algorithms based on the smart interrelation of huge amount of data is essential. Data may be static (such as the connection point specifications) or dynamic by means of both historians and predictions (electricity prices, health indexes affected by the assets degradation, wind availability, Operating System OS orders…).