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An increasing number of solar PV plant developers, operators and owners require high frequency data (1-min) to make qualitative improvements throughout the entire lifecycle of a solar project.
To fulfil this demand, Solargis has collaborated with the University of Malaga to create a new approach to producing 1-min data, which uses statistic methods (stochastic generator) to insert high-frequency weather and solar irradiance events into satellite data.
Illustration of the daily profile of the monthly average GHI value for January 2021 calculated from 1min and 1hr aggregation of the same dataset.
Filling gaps in understanding
Today, the solar industry mostly relies on low frequency weather and solar irradiance data collected at 60-minute intervals. However, low granularity data can lead to gaps in effectively understanding and optimising the financial and technical performance of solar PV plants, and their designs.
Instead, the industry needs to move towards collecting weather and solar irradiance data at shorter intervals. By accurately capturing the solar irradiance variability, weather and PV power potential of a chosen solar plant site, 1-minute data reduces broad and hindered decision making around project design, development, and operations.
In turn, this helps project designers, developers and operators maximise a plant’s energy yield, optimise its relationship with the grid, and, ultimately, strengthen its financial and technical performance.
Illustration of problematic measurement error detection in in the data (specifically the occurrence of dew on the sensor in this case). In 1min data the dew occurrence is visible in the morning hours 7:00-8:00, while in the 1h smoothed dataset the dew on the sensor cannot be identified.
How does Solargis’ 1-min data approach work
1-minute data produces an extremely granular or high frequency dataset, by combining real satellite-based values with a stochastic data generator model, to produce a secondary stream of data that can better describe the variability of a particular site.
The stochastic generator is designed to evaluate solar irradiance over prolonged periods of time, at least one year. To do this, specific transition probability matrices (TPM), alongside four different sky conditions ranging from stable to highly variable GHI, are collected using Solargis’ extensive, multiyear worldwide database. Only the 1-min GHI measurements from locations with comparable solar climatic features are compared to any specific desired location of a solar PV plant.
Next, 1-min GHI is generated through combining 10-15-30-min GHI values and the TPMS as inputs using only 1-minute GHI values whose mean is close to the 10/15/30-min GHI input within a tolerance limit (±1 W/m2).
Through Solargis’ global coverage, data from a vast range of sites can be accessed, enabling a deep analysis to be performed in the planning phase of the project.
What is the potential of Solargis’ approach to 1-min data?
Solargis’ approach to 1-min data has the potential to make qualitative improvements in the simulation of PV systems, in particular addressing transient effects. For example, high frequency data can offer the opportunity to study the temporal and spatial effects of clouds over large area power plants.
Solargis’ 1-min data can be used in combination with ground measurements (although not a necessity) as well as a company’s historical forecasting data, to unlock significant financial and technical benefits that are facilitated by more accurate decision making.
Solargis’ 1-min data blog series
Our following blog series will discuss:
Find out more about Solargis’ 1-minute data methodology.