Caratterizzazione e massimizzazione dell'efficienza di impianti di produzione di energia elettrica da fonti rinnovabili tramite l'utilizzo di elettronica di potenza distribuita ed integrazione di sistemi di storage

This thesis focuses on large or utility-scale photovoltaic (PV) plants. The first target is to improve the energy production by using distributed converters. The second target, which is linked to the first one, is to optimize the management of energy flows by integrating distributed energy storage systems (ESS) realized with several battery packs. The approach is the implementation of innovative energy management strategies supported by suitable models for both PV field and storage system. In particular, a behavioural model is applied to large PV plants. This model is built in the form of an integrated state-space average model used to compute all the electrical quantities in each section of a PV plant allowing a simple calculation of power, energy, losses, voltage drops, etc. The final model is obtained as the merging of the state-space average models developed for each component of the PV plant. Moreover, this approach leads to a straightforward way to calculate the average DC-link current at the input side of inverters from the direct-sequence components of the AC currents, the latter being state variables. Thanks to this novelty, no any data storage is required to calculate the integral terms of the common formulation of DC-link current, obtaining a significant simplification without decreasing the accuracy level. About the storage system, estimation of State of Charge (SOC) and State of Health (SOH) of battery packs play a key role for the effective integration of battery packs in large PV plants. Because of the large amount of data to manage for both PV system and ESS, the algorithms developed in this work for the estimation of SOC and SOH aim to keep a low computational effort while ensuring a satisfactory accuracy. Such algorithms belong to two different categories. The first one relates to PI-based observers. The second one, classified as a mixed algorithm, mixes two basic estimation methods in order to benefit from their advantages while compensating their drawbacks. The core of these estimation algorithms is the equivalent circuit model of the battery pack. An in-depth literature review and extensive experimental tests lead to the selection of proper models to be integrated in algorithms. 5 Power and energy capability of battery packs represent the link between the model of ESS and the model of PV plant. The justification of this approach deals with the limitation of complexity. In fact, the separation of PV plant model and of ESS estimation algorithm is useful to keep a low computational effort. At the same time, the link based on actual values of power capability allows a suitable integration of the models for the optimal energy management of the entire system. Validation of the novelties presented in this thesis has been carried out by means of laboratory tests and by processing large databases collected during measurement campaigns carried out in two case studies: a 300 MW PV plant in Brazil and a 2 MW PV plant in Central Italy.