Towards Real-Time Estimation of Solar Generation From Micro-Synchrophasor Measurements

Towards Real-Time Estimation of Solar Generation From Micro-Synchrophasor Measurements

Emre C. Kara emrecan@slac.stanford.edu Grid Integration Systems and Mobility Group, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
Ciaran M. Roberts Energy Storage and Distributed Resources Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Michaelangelo Tabone Energy and Resources Group, University of California, Berkeley, CA, USA
Lilliana Alvarez Riverside Public Utilities, Riverside, CA, USA
Duncan S. Callaway Energy and Resources Group, University of California, Berkeley, CA, USA
Emma M. Stewart Energy Storage and Distributed Resources Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

Submitted on Jul 11, 2016  

Abstract

This paper presents a set of methods for estimating the renewable energy generation downstream of a measurement device using real-world measurements. First, we present a generation disaggregation scheme where the only information available for estimation is the micro-synchrophasor measurements obtained at the substation or feeder head. We then propose two strategies in which we use measurements from the substation as well as a proxy solar irradiance measurement. Using these two measurement points, we first propose a multiple linear regression strategy, in which we estimate a relationship between the measured reactive power and the load active power consumption, which are then used in disaggregation. Finally, we expand this strategy to strategically manage the reconstruction errors in the estimators. We simultaneously disaggregate the solar generation and load. We show that it is possible to disaggragate the generation of a 7.5 megawatt photovoltaic site with a root-mean-squared error of ≈ 450 kilowatts.