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  • ๐Ÿ‘‹ Hi, Iโ€™m @kshitizkhanal7
  • ๐Ÿ‘€ Iโ€™m interested in energy systems, planning, machine learning, and open knowledge.
  • ๐ŸŒฑ Iโ€™m currently enrolled in a Ph.D. program at the Department of City and Regional Planning at the University of North Carolina at Chapel Hill. In my dissertation, I investigate the applications of machine learning and geospatial analysis techniques in energy planning.
  • ๐Ÿ“ซ Twitter @kshitizkhanal7
  • I am also building Energy in Numbers. This is a website created as a resource for climate-conscious people interested in energy and analytics. Please check it out and let me know how you find it. I plan to continually improve it.
  • My personal website contains more information about my project portfolio, CV, talks, and teaching experience.

Kshitiz Khanal's Projects

aerogami icon aerogami

An Open Education experiment teaching Aerodynamics using Paper Planes

arm icon arm

Repo for Asia Regional Meeting website.

basopra icon basopra

BASOPRA - BAttery Schedule OPtimizer for Residential Applications. Daily battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute temporal resolution are used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.

bootstrap-lab icon bootstrap-lab

Can you build a science lab in resource-strapped schools? We are looking into experiments and science-education setups that can be built with the most commonly available materials.

causal-ml icon causal-ml

Collection of resources related to causal inference and machine learning

cfdpython icon cfdpython

A sequence of IPython notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/

cv-1 icon cv-1

My CV built using RMarkdown and the pagedown package.

d2l-en icon d2l-en

An interactive deep learning book with code, math, and discussions.

d3-book icon d3-book

Code examples for โ€œInteractive Data Visualization for the Webโ€

energy-analytics-handbook icon energy-analytics-handbook

A handbook of energy analytics covering lessons and tutorials on applications of modeling, optimization, data science, machine learning, spatial analysis and other techniques. The resources are demonstrated primarily in Python, with some developed in R, Excel and other tools best fit for purpose.

hacktoberfest icon hacktoberfest

Participate in Hacktoberfest by contributing to any Open Source project on GitHub! Here is a starter project for first time contributors. #hacktoberfest

hyde icon hyde

A brazen two-column theme for Jekyll.

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