Empirical assessment of short‐term variability from utility‐scale solar PV plants

Abstract

Variability of solar power is a key driver in increasing the cost of integrating solar power into the electric grid because additional system resources are required to maintain the grid's reliability. In this study, we characterize the variability in power output of six photovoltaic plants in the USA and Canada with a total installed capacity of 195 MW (AC); it is based on minute‐averaged data from each plant and the output from 390 inverters. We use a simple metric, “daily aggregate ramp rate” to quantify, categorize, and compare daily variability across these multiple sites. With this metric, the effect of geographic dispersion is observed, while controlling for climatic differences across the plants. Additionally, we characterized variability due to geographical dispersion by simulating a step by step increase of the plant size at the same location. We observed maximum ramp rates for 5, 21, 48, and 80 MWAC plants, respectively, as 0.7, 0.58, 0.53, and 0.43 times the plant's capacity. Copyright © 2012 John Wiley & Sons, Ltd.

Local short-term variability in solar irradiance

“…While the PDFs of single-sensor observations all exhibit such tails, these features are much less prominent for the spatially averaged k * increment distributions. This result is consistent with previous findings of e.g., Lave and Kleissl (2010), Marcos et al (2011b), Dyreson et al (2014), andvan Haaren et al (2014). Comparing the distributions of increments from multiple pyranometers and PV plants of different capacities for various temporal resolutions, these previous studies all showed high magnitude changes with increasing time lag, and fewer high magnitude changes with increasing PV plant size (or numbers of sensors).…”

“…While overcast conditions may necessitate other power sources to substitute the momentary lack of PV generation, clear and mixed conditions can negatively impact the electrical grid. Under clear conditions, high PV power feedback (i.e., reverse power flow from the distribution grid to the transmission grid) can occur and needs to be managed in areas of high PV penetration (Wirth et al, 2014), whereas mixed conditions may endanger the grid's reliability due to the frequent power ramping of PV systems (van Haaren et al, 2014). In the context of subminute variability, we illustrate the event risk of k * fluctuations by means of increment PDFs in Fig.…”

“…size (Dyreson et al, 2014;Lave et al, 2012;Marcos et al, 2011b;van Haaren et al, 2014). Furthermore, spatial autocorrelation structures and decorrelation length scales of increments in irradiance and clear-sky index (i.e., irradiance normalized to clear-sky conditions), and PV power output have also been studied for a range of spatial scales and increment values (Arias-Castro et al, 2014;Elsinga and van Sark, 2014;Hinkelman, 2013;Hoff and Perez, 2012;Mills, 2010;Perez et al, 2012;Perpiñán et al, 2013).…”

“…Recent studies of PV-related variability have analyzed power spectra of PV systems and solar irradiance (Calif et al, 2013;Curtright and Apt, 2008;Klima and Apt, 2015;Lave and Kleissl, 2010;Marcos et al, 2011a;Tabar et al, 2014;Yordanov et al, 2013b), compared power fluctuations from specific PV plants with corresponding irradiance measurements Marcos et al, 2011a;van Haaren et al, 2014), and characterized power variability as a function of PV plant…”

External Benefit Evaluation of Renewable Energy Power in China for Sustainability

“…Wind power and solar PV power have stochastic, volatile and uncertain characteristics, and biomass power often has a fuel shortage issue. The large-scale penetration of renewable energy power will have certain impacts on multiple stakeholders in China's electric power system, including power generation enterprises, power grid companies, electricity consumers and the environment, as well as society in general [33][34][35][36]. The detailed impacts are analyzed below.…”