The goal here is to show how to query, analyze and visualize ERA-Interim meteorological data in NetCDF format using tidy principles in R.
This is also a follow up to the AWEA Wind Resource Working Group’s webinar on the open-source ecosystem and an expansion of my original blog post: [https://renewable-analytics.netlify.com/2018/05/30/example-wind-resource-assessment-using-r/].
The goal here is to illustrate how aspects of typical wind resource assessment and energy capture from meteorological data can be accomplished using open source tools, in this case using R. Using publicly available data, I’ll walk through some of the typical steps taken in site screening, importing, visualizing and analyzing meteorological data with the goal of modeling the annual energy capture of a wind turbine at a given location. For kicks, as a wink to the NIMBY’s out there, let’s use my…
USGS just came out with an awesome updated database of operating wind turbine locations in the United States. I wanted to show how you can extract and view this data yourself, using R.
So, alot is made of the functionality of PVSYST as a standard tool to model PV systems. No arguments here. That said, it does not have a programming interface. Thankfully there are some great alternatives out there developed through Sandia National Laboratories, particularly the PV-LIB Toolbox (https://pvpmc.sandia.gov/applications/pv_lib-toolbox/), which contains some really excellent functions for modeling solar position, irradiance, and PV systems. The tool was initially created in MATLAB and…
I spent some time creating a shiny app in R which allows users to access monthly energy production data from power plants in the U.S. which report to the Energy Information Administration (www.eia.gov). The app is driven via a Digital Ocean droplet.
I spent some time creating a Shiny App which interfaces with the National Climatic Data Center using the excellent rnoaa R-package. Not everything in the app works perfectly but it does some useful things. The app is driven via a Digital Ocean droplet.
The purpose of this post is to illustrate an example method for assessing changes in performance for wind turbines based on the installation of performance modifications. In this case we’re looking at Vortex Generators (VG) which are typically after market hardware installed along wind turbine blades and are purported to improve blade performance by reducing flow separation, thereby improving lift, and increasing power efficiency.
The purpose of this post is to illustrate different filtering techniques for calculating the actual power curve of a wind turbine using SCADA data. Typically data in which the turbine is experiencing downtime can be filtered out using status/fault/error codes provided by the Original Equipment Manufacturer’s (OEM) SCADA system. However, it has been my experience that these data are not of sufficient quality to properly filter out all ‘bad’ data and in many cases when analyzing a wind plant these…
Using PV Lib from Sandia to calculate Plane of Array Irradiance for fixed tilt and tracking projects via the Perez Transposition Algorithm