Worst expected ramp rates from cloud speed measurements
Date
2019Version
Acceso abierto / Sarbide irekia
Type
Contribución a congreso / Biltzarrerako ekarpena
Version
Versión aceptada / Onetsi den bertsioa
Project Identifier
Impact
|
10.1109/PVSC40753.2019.8981213
Abstract
Large 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 ...
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Large 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. [--]
Subject
Cloud speed sensor,
Power ramp rate estimate,
PV plant design
Publisher
IEEE
Published in
2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), Chicago, IL, USA, 2019, pp. 2281-2286
Departament
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Publisher version
Sponsorship
Juan Luis Bosch has been financed in part by Projects ENE2017-83790-C3-3-R and ENE2014-59454-C3-2-R which were funded by the Ministerio de Ciencia, Innovación y Universidades and Ministerio de Economía y Competitividad, respectively, and co-financed by the European Regional Development Fund. In addition, Iñigo de la Parra has been partially supported by the Spanish State Research Agency (AEI) and FEDER-UE under grants DPI2016-80641-R and DPI2016-80642-R.