<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Wind |</title><link>https://philipholler.com/tags/wind/</link><atom:link href="https://philipholler.com/tags/wind/index.xml" rel="self" type="application/rss+xml"/><description>Wind</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 15 Jun 2026 00:00:00 +0000</lastBuildDate><image><url>https://philipholler.com/media/icon_hu_34c12f47fa3f08cc.png</url><title>Wind</title><link>https://philipholler.com/tags/wind/</link></image><item><title>LCOE Calculator — U.S. solar &amp; wind</title><link>https://philipholler.com/projects/lcoe-calculator/</link><pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate><guid>https://philipholler.com/projects/lcoe-calculator/</guid><description>&lt;p&gt;An interactive web application, built with &lt;strong&gt;Shiny for Python&lt;/strong&gt;, that estimates the &lt;strong&gt;levelized cost of electricity (LCOE)&lt;/strong&gt; for &lt;strong&gt;solar and wind across U.S. states&lt;/strong&gt;. Costs can be compared across the utility, commercial, and residential segments, and wind capacity factors can be derived from alternative reanalysis datasets (HRRR, ERA5, MERRA2). The tool combines modelled hourly capacity factors with technology cost assumptions to show how generation costs vary by location and market segment.&lt;/p&gt;
&lt;p&gt;A collaboration with Thimo Merke and Minghao Chen.&lt;/p&gt;
&lt;div style="margin: 1.5rem 0;"&gt;
&lt;iframe
src="https://unimamises-lcoe-calculator-shiny.hf.space"
title="LCOE Calculator — U.S. solar and wind"
style="width: 100%; height: 820px; border: 1px solid #e5e7eb; border-radius: 12px;"
loading="lazy"
allow="fullscreen"&gt;
&lt;/iframe&gt;
&lt;/div&gt;</description></item></channel></rss>