Wang, Guang ChaoBosch, Juan LuisKurtz, BenParra Laita, Íñigo de laWu, Elynn2021-03-182021-03-182019G. C. Wang, J. Luis Bosch, B. Kurtz, Í. d. l. Parra, E. Wu and J. Kleissl, 'Worst Expected Ramp Rates from Cloud Speed Measurements,' 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), Chicago, IL, USA, 2019, pp. 2281-2286, doi: 10.1109/PVSC40753.2019.8981213.0160-837110.1109/PVSC40753.2019.8981213https://academica-e.unavarra.es/handle/2454/39421Large PV power ramp rates are of concern and sometimes even explicitly restricted by grid operators. Battery energy storage systems can smooth the power output and maintain ramp rates within permissible limits. To enable PV plant and energy storage systems design and planning, a method to estimate the largest expected ramps for a given location is proposed. Because clouds are the dominant source of PV power output variability, an analytical relationship between the worst expected ramp rates, cloud motion vectors, and the geometrical layout of the PV plant is developed. The ability of the proposed method to bracket actual ramp rates is assessed over 8 months under different meteorological conditions, demonstrating an average compliance rate of 96.9% for a 2 min evaluation time window.6 p.application/pdfeng© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.Cloud speed sensorPower ramp rate estimatePV plant designinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess