Solar irradiance estimations for modeling the variability of photovoltaic generation and assessing violations of grid constraints: A comparison between satellite and pyranometers measurements with load flow simulations

Abstract

Global horizontal irradiance (GHI) is typically used to model the potential of distributed photovoltaic (PV) generation. On the one hand, satellite estimations are non-pervasive and already available from commercial providers, but they have a limited spatiotemporal resolution. On the other hand, local estimations, e.g., from pyranometers, sky-cameras and monitored PV plants, capture local irradiance patterns and dynamics, but they require insitu monitoring infrastructure and upgrading the asset of electrical operators. Considering that in most power systems, PV generation is typically the aggregated contribution of many distributed plants, are local GHI estimations necessary to characterize the variability of the power flow at the grid connection point (GCP) and detect violations of the limits of voltages and line currents accurately? To reply, we consider GHI measurements from a dense network of pyranometers (used to model the ground truth GHI potential), satellite estimations for the same area, and information about a medium and low voltage distribution system. We perform load flows at different levels of installed PV capacity and compare the nodal voltages, line currents, and the power at the GCP when the irradiance is from pyranometers and when from satellite estimations, deriving conclusions on the necessity, or not, of highly spatiotemporally resolved irradiance estimations.

Countrywide PV hosting capacity and energy storage requirements for distribution networks: The case of Switzerland

“…where T air t is the air temperature ( • C), α = −0.0043 and β = 0.038 are empirical parameters as in [59] for open-rack PV plants.…”

Distributed Photovoltaic Optimization Configuration Based on Marine Predators Algorithm in Low Voltage Transformer Area

“…The output of photovoltaic power plants depends on the specific weather conditions in the installation area. This article establishes an actual output model of photovoltaic power sources based on the irradiance and environmental temperature received by photovoltaic array panels [11] .…”

Optimal Grid-Forming Control of Battery Energy Storage Systems Providing Multiple Services: Modelling and Experimental Validation

“…total capacity, location, tilt, azimuth) allows computing the Global Normal Irradiance (GNI) and obtaining an estimation of the total PV production, and the related uncertainties. The best and worst PV production scenarios are computed by transposing the GHI forecast data and applying a physical model of PV generation accounting for the air temperature [33]. For a given day-ahead forecast, the vector containing the best and worst production scenario for the PV, with a time resolution of 5 minute are named as PV ↑ and PV ↓ , respectively.…”