Flywheel hybridization to improve battery life in energy storage systems coupled to RES plants

How Hybridization of Energy Storage Technologies Can Provide Additional Flexibility and Competitiveness to Microgrids in the Context of Developing Countries

“…Since the available dataset covered only six months of data, the annual profile was obtained by duplicating the available load profile data, in consideration of the low seasonality of consumption patterns in the island. First, taking into account the acquired PV production and load profiles, the preliminary sizing of the energy storage devices (Li-ion, Lead-gel, also in hybrid flywheel/battery configurations, and VRFBs technologies are applied) is performed through the simulation code presented in reference [21], also providing as output the State of Charge (SoC) trend throughout the year (in terms of angular velocity for flywheel modules). Second, for conventional batteries the SoC trend made it possible to estimate for each storage configuration the number of annual cycles and the relative lifespan in years, through the application of the Rainflow algorithm and the specific "Cycles to Failure" curve of the technology analyzed.…”

“…MG energy performance is evaluated by means of the MG simulation code developed in the Matlab environment for batteries [34] and flywheel/battery hybrid storage sections [21,22]. The code performs power flow management, with a 1 min time step, based on PV production and load profiles.…”

“…In the case of battery/flywheel hybrid architectures, a complex management algorithm is used, as presented by the authors in references. [21,22], implementing the flywheel peak-shaving functionalities on the basis of the difference values (Diff ), the current and the one relative to the previous calculation step, between production and load. Specifically, on the basis of two consecutive Diff values, two step-profiles (i.e., consisting of consecutives step variations), characterized by a slow variation and approximating the Diff trend by excess or defect respectively (with reference to absolute values), are determined in real time.…”

“…In accordance with the particular operating mode (surplus or lack of renewable energy, full charge, complete discharge, power saturation of storage devices), the current value of one of the step-profiles is chosen as the power accumulated/delivered by the battery pack in the time step (or the auxiliary generator in case the storage system cannot be operated), while the oscillation (i.e., the difference between such a parameter and the current Diff value) is processed by the flywheel. The algorithm consists of two main sections corresponding to the case of lack and surplus of PV production, each one structured in several sub-cases identified according to flywheel rotational speed, battery state of charge, and absence/presence of PV production as detailed in reference [21]. It is to note that the code was developed to characterize the energy exchanges in the grid connected MG.…”

“…Regarding technologies hybridization, the coupling of flywheels with conventional batteries for microgrid applications can extend the life of electrochemical storage systems, drastically reducing replacement costs associated with the latter. Specifically, in reference [21] accelerated aging tests, performed over lithium cells operated both in hybrid and non-hybrid configurations, resulted in a one third reduction in the internal resistance increase in the case of hybridization over three years of operation, thus demonstrating that a relevant battery life extension is possible through flywheel-battery coupling. Flywheel energy storage systems (FESS) are capable of coping with highly oscillating power fluctuations [22] and therefore can be used as short-term storage devices [23]; reducing dangerous power spikes meanwhile increasing battery lifetime in hybrid configurations.…”