Intelligent management of hybrid energy systems for techno-economic performances maximisation

The great diffusion of renewable energy sources in the latest decades led to a pervasive diffusion of hybrid energy systems (HESs), in which several sources of energy are combined to fulfil the user demand. As the number of HES sources and related hardware components raise, the number of interconnections between these latter increases more than proportionately. Such condition determines high HES complexity, that can be exploited to achieve greater overall efficiency. This research deals with the HES designed to meet the electricity load required by a single user. Furthermore, the considered HESs leverage single or multiple components in charge of electricity production (e.g. PV module, wind turbine, etc.) a battery energy storage system (BES) and a connection with the national grid that allows the electricity purchase and sale processes. A two-step approach is proposed to deal firstly with the HES sizing, by exploiting an iterative method to identify the optimal size of each energy component. The second step consists in the energy flows management, i.e. the hourly dispatching between the HES components. Indeed, two different strategies are proposed to intelligently manage the hourly electricity flows. On the one hand, the proposed heuristic algorithm (HA) aims to minimize the purchased energy from grid imposing a constant dispatching of the electricity flows according to the amount of produced energy, the state of charge of the BES and the user request. On the other hand, a mixed integer linear programming (MILP) model leverages the short-time forecasts of environmental parameters, energy tariffs, and load request to optimise in real-time the electricity trade process from an economic point of view. The overall approach, including the comparison between the HA and the MILP, has been tested and validated on several case studies, concerning specific HES architectures, a range of European countries, both domestic and non-domestic users as well as multiple values of energy request. The results justify the HES installation in all the considered case studies, leading to an economic saving greater than 35% compared to electricity purchase from grid uniquely. However, the MILP adoption for the management of energy flows is recommended only for HESs fuelled by multiple energy sources.