Prospect
Quick estimate of PV site's solar potential
All Solar industry players need to simulate their power plant designs and financial plans at some point. To do so against summarized conditions given by data products like Typical Meteorological Years has been common until recently. However, running energy simulations using more realistic conditions described by Multi-Year Time Series of data is recommended to reduce project risk and evaluate all scenarios.
Solar irradiance modeling involves computing the amount of sunlight reaching the Earth's surface. During eclipses, the moon obstructs solar radiation, leading to a temporary reduction in irradiance.
In this article, we are sharing how Solargis has improved the accuracy of air temperature datasets we provide along with other parameters affecting solar energy power simulations.
The study summarizes the results of comparing the data provided by various institutional or commercial providers of solar irradiance models against ground measurements collected at 129 sites distributed globally. It helps solar developers navigate through all the available databases.
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.
Due to the impact that surface albedo has in PV yield calculations (mostly when we talk about bifacial modules), we have noticed an increasing interest in knowing more about this parameter. These are the most typical questions we are receiving (with their corresponding answers):
Bad data in equals bad data out. This well-known phrase is very relevant in a context of technical design and energy simulation of photovoltaic (PV) power plants. Most solar companies understand this and are carefully evaluating uncertainty of solar resource data used for feasibility purposes ...
To assess the solar resource or energy yield potential of a site, we model the solar resource/energy yield using best available information and methods. The resulting estimate is the P50 estimate, or in other words, the “best estimate”. P50 is essentially a statistical level of confidence suggesting that we expect to exceed the predicted solar resource/energy yield 50% of the time. However, ...
The process of estimating solar radiation data uncertainty can be sometimes unclear. We've tried to summarise in 4 simple steps.
