GSoC 2020 Project

Placeholder for GSoC 2020 participation under NumFOCUS umbrella

Introduction

pvlib-python is the world's most popular open-source library for solar power modeling. Come help us improve and extend these capabilities, and learn about solar power in the process!

immediate priorities

1. due date for proposals is Feb 5th, target date is mid-January
2. NumFOCUS GSoC 2020 Coordinator: Mridul Seth [email protected]
3. examples of other proposals here: https://github.com/pymc-devs/pymc3/wiki/GSoC-2020-projects
4. official Google guidelines here: https://google.github.io/gsocguides/mentor/defining-a-project-ideas-list

from official guidelines:

Each project on the Ideas list should include:

• a project title/description
• more detailed description of the project (2-5 sentences)
• expected outcomes
• skills required/preferred
• possible mentors. And if possible, an easy, medium or hard rating of each project.

Ideas

Project Title: Create usage examples

Project Description: Create iPython notebooks showing how to use pvlib-python for several common use cases for solar power modeling. Priority use cases include:

• Calculating annual energy for a PV system at a given location and orientation, showing use of different models for plane-of-array irradiance, DC power, and cell temperature.
• Comparing power output between fixed-tilt and tracking PV systems.
• Calculating and comparing irradiance from various clear-sky models.
• Comparing power output from a PV system using different PV panels and/or inverters in the system. Mentors will provide detailed descriptions of the use cases, guidance on the modeling process and usage of pvlib-python.

Expected Outcomes: The primary outcome is a set of iPython notebooks. A secondary outcome is to identify improvements to pvlib-python for usability and flexibility.

Skills Required / Preferred: iPython (required), familiarity with solar power modeling preferred, but not required.

Mentors: Cliff Hansen, Mark Mikofski, Will Holmgren

Difficulty: Medium

mentors

past projects (matplotlib) have observed that each student may need have 2-3 mentors.

1. Will Holmgren
2. Cliff Hansen
3. Mark Mikofski