Browsing by Author "Probst, Oliver"

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Comparative fatigue life assessment of wind turbine blades operating with different regulation schemes
(2019) Loza, Brian; Probst, Oliver; Minchala Ávila, Luis Ismael; Cárdenas, Diego; Pacheco Chérrez, Josué
A comparative evaluation of the fatigue damage occurring in the blades of small wind turbines, with different power regulation schemes, has been conducted for the first time. Three representative test cases were built, one based on stall regulation and two using pitch regulation. The power curves were tuned to be identical in all cases, in order to allow for a direct comparison of fatigue damage. A methodology combining a dynamic simulation of a wind turbine forced by stochastic wind speed time series, with the application of the IEC 61400-2 standard, was designed and applied for two levels of turbulence intensity. The effect of the wind regime was studied by considering Weibull-distributed wind speeds with a variety of parameter sets. Not unexpectedly, in typical wind regimes, stall regulation led to a generally higher fatigue damage than pitch regulation, for similar structural blade design, but the practical implications were smaller than thought previously. Given the need for cost-effective designs for small wind turbines, stall regulation may be a viable alternative for off-grid applications.
Minimization of energy storage requirements in wind farms by controlling the state of charge of a battery bank
(Institute of Electrical and Electronics Engineers, 2022) Probst, Oliver; Minchala Ávila, Luis Ismael; Mendieta, Miguel
This paper presents a methodology for reducing energy storage requirements through batteries (BESS) applied to smoothing the power variation of a wind farm (WF). This reduction is achieved by combining the operation of an energy management system (EMS) with an optimally sized BESS. The EMS deploys a state-of-charge feedback-based (SOC-FB) control system to reduce a WF's power variations by coordinating the BESS's charge and discharge cycles. At the same time, an evolutionary optimization algorithm determines the BESS's power capacity to keep the WF's power variation within specific limits defined in a cost function. This approach is tested using data from met towers used during the development phase of the WF. Simulation results show a significant reduction of the WF output power variation with an optimal-calculated capacity of the BESS in comparison with the operation of the WF without the approach proposed in this study.