× This Challenge was posted 4 years ago

Challenge view

Back to Project

PV self-consumption optimization

Evaluate and optimize trade-offs in the design of battery storage for PV systems

Pitch Readme

With the AEW data of a 60 kWp PV installation, we optimized the solar energy self-consumption by a battery system. For this, we calculated different parameters such as battery load, new self-consumption and new grid supply and estimated the optimal battery capacity with further values such as energy and battery prices, life span, contract duration, minimal charge, maximum load power in Google sheet and as well with Python.

Finally, our customer can select, whether he wants the most economical battery solution or maximise his autarky. Our tools calculate the maximized economic benefit over lifetime.

Google Sheet Prototyp

Create a copy

Github

Contains initial Python implementation and some exploratory analysis, see also README below.

29.08.2020 12:02

Analysis and Design of Battery Storage for PV Systems

Challenge No. 2 @ Energy Data Hackdays 2020

This repo contain some additional analysis scripts that use the original data files (CSV) provided for the challenge.

Data

Data on power generation, grid feed, grid supply and overall consumption of three power plants by AEW Energie AG. First time published for the Challenge 3 of Energy Data Hackdays 2020 in Brugg. A.csv B.csv C.csv

For questions on the data, reach out at https://github.com/zuzfil/PV-optimisation/issues.

The data were created during the operation of AEW-owned PV plants in 2019. The plants are all located in Aargau, Switzerland. The power values in kW refer to the average over the 15min period.

License

This Data Package is made available by its maintainers under the Public Domain Dedication and License v1.0, a copy of the full text of which is in LICENSE.md.

This content is a preview from an external site.
 
👋 Contact 🌐 Open 💻 Source
Contributed 4 years ago by jonas_huber for Energy Data Hackdays 2020
All attendees, sponsors, partners, volunteers and staff at our hackathon are required to agree with the Hack Code of Conduct. Organisers will enforce this code throughout the event. We expect cooperation from all participants to ensure a safe environment for everybody. For more details on how the event is run, see the Guidelines on our wiki.

Creative Commons LicenceThe contents of this website, unless otherwise stated, are licensed under a Creative Commons Attribution 4.0 International License.

PV Optimisation Energy Data Hackdays 2020 Read your own Smart Meter