Search

The wide scale market penetration of numerous renewable energy technologies is dependent, at least in part, on developing reliable energy storage methods that can alleviate concerns over potentially interrupted and uncertain supplies. Many challenges need to be overcome, not least among them is allowing capacity for the wide range of time scales required to ensure grid stability. In thermal power plant, high frequency/short duration demand fluctuations, acting at the milliseconds to several seconds time scale, are addressed passively by the inertia of the grid. Here, grid inertia can be thought of as the mechanical inertia of spinning steel in steam and gas turbines. This allows time for active control measures to take effect at the tens of second to hours time scale and for the system to recover without a supply frequency deviation that is noticeable to the customer. It is of paramount importance that, as thermal plant is retired, renewable energy generation and storage systems account for the loss of this inertia. In the literature, strategies to address the loss of “real” inertia have often relied on emulation rather than actual replacement. The present work focuses on the preliminary development of a novel energy storage system that makes use of real inertia to address short term supply/demand imbalances while simultaneously allowing for extended depths of discharge. The concept looks to combine flywheel and compressed fluid energy stores in order to power a synchronous generator. By combining these energy storage technologies through a differential drive unit, DDU, it is anticipated that the benefits of high system inertia can be exploited in the short term while allowing energy to be continually extracted from the flywheel in the long term during storage discharge. The use of a DDU makes the present design particularly novel and distinct from other hybrid systems. In essence, this inclusion allows energy to be extracted entirely from the flywheel, inducing “real” inertia, or entirely from the secondary store, inducing “synthetic” inertia, or some combination of the two. Fundamental sizing calculations for a 50 MW system with 20 MWh of storage capacity are presented and used to design a suitable control system that allows for the operation of both primary flywheel and secondary compressed fluid energy stores. The transient behaviour of the system is simulated for several charge/discharge time profiles to demonstrate response stability for the system. Comments on system turnaround efficiency, which is dependent upon loading history but for the intended applications can be considered to be greater than 90% are also made here, along with a case study application to an isolated Californian solar powered grid.

Journal article A service-aged P91 steel was used to perform an experimental program of cyclic mechanical testing in the temperature range of 400 °C–600 °C, under isothermal conditions, using both saw-tooth and dwell (inclusion of a constant strain dwell period at the maximum (tensile) strain within the cycle) waveforms. The results of this testing were used to identify the material constants for a modified Chaboche, unified viscoplasticity model, which can deal with rate-dependant cyclic effects, such as combined isotropic and kinematic hardening, and time-dependent effects, such as creep, associated with viscoplasticity. The model has been modified in order that the two-stage (nonlinear primary and linear secondary) softening which occurs within the cyclic response of the service-aged P91 material is accounted for and accurately predicted. The characterization of the cyclic viscoplasticity behavior of the service-aged P91 material at 500 °C is presented and compared to experimental stress–strain loops, cyclic softening and creep relaxation, obtained from the cyclic isothermal tests. Science Foundation Ireland [Grant No. SFI/2010/IN.1/I3015] peer-reviewed

A procedure to estimate material constants for the unified Chaboche viscoplasticity model from experimental data has been published elsewhere; however several critical assumptions are made to enable this and potential numerical problems can limit the effectiveness of the optimisation. Pragmatic optimisation procedures are therefore required to determine the material properties accurately and efficiently. This is made more complex by the presence of several deformation mechanisms and their interactions. Automation is critical due to the large amounts of data generated in testing. Complications that inhibit this process can arise due to factors such as experimental scatter. In this paper, a general optimisation framework is discussed and investigated using data from isothermal tests on a P91 steel at 600°C. Potential obstacles in the procedure are addressed and solutions (such as pre-optimisation experimental data ‘cleaning’) are suggested. Methods to maximise the amount of confidence a user has in a particular optimised constant set are also discussed.