Publication:
Worst expected ramp rates from cloud speed measurements

Consultable a partir de

Date

2019

Authors

Wang, Guang Chao
Bosch, Juan Luis
Kurtz, Ben
Wu, Elynn

Director

Publisher

IEEE
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa

Project identifier

AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ENE2017-83790-C3-3-R/ES/
MINECO//ENE2014-59454-C3-2-R/ES/
ES/1PE/DPI2016-80641-R
ES/1PE/DPI2016-80642-R

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 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.

Keywords

Cloud speed sensor, Power ramp rate estimate, PV plant design

Department

Institute of Smart Cities - ISC

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

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.

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