https://github.com/pierre-haessig/solarhome-control-bench

open testbench for control and optimization methods for the energy management of a simple solar home
https://github.com/pierre-haessig/solarhome-control-bench

energy-management energy-storage solar

Last synced: 6 months ago
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open testbench for control and optimization methods for the energy management of a simple solar home

• Host: GitHub
• URL: https://github.com/pierre-haessig/solarhome-control-bench
• Owner: pierre-haessig
• Created: 2018-01-15T08:36:53.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2021-07-02T21:48:50.000Z (over 4 years ago)
• Last Synced: 2025-04-18T20:44:14.866Z (6 months ago)
• Topics: energy-management, energy-storage, solar
• Language: Jupyter Notebook
• Size: 26.9 MB
• Stars: 17
• Watchers: 5
• Forks: 9
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGES.md

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README

          
# Solar home control bench

This repository contains an open testbench for control and optimization methods for the energy management of a simple solar home.

Pierre Haessig, IETR (AUTomatic Control team), CentraleSupélec

## Solar home model

![solar home power flow model](images/solar_home.png)

## Control methods

This repository contains several examples for the energy management of the solar home,

with a different method or in a different language (Python, Julia, Matlab).

Each method lives in dedicated subdirectory of the [methods](methods) folder.

It includes:

* Rule-based control (Julia, Matlab and Python)

* Model Predictive Control (MPC)

* Stochastic Dynamic Programming

* …

## Comparison of control methods

In the [comparison](comparison) folder.

## Solar and load data

Solar production (from PV panels) and home consumption data is taken from the

[Solar home electricity dataset](http://www.ausgrid.com.au/Common/About-us/Corporate-information/Data-to-share/Solar-home-electricity-data.aspx)

by Ausgrid (distribution grid operator in the region near Sydney).

A dataset extract used for this testbench is placed in the [data](data) subfolder.

A description of this data extract is provided in [data/README.md](data/README.md). In particular, the 30 days starting at 2011-11-29 should be used for final testing:

![2011-11-29 week plot](data/data_week_2011-11-29.png)

In addition the dedicated [ausgrid-solar-data](https://github.com/pierre-haessig/ausgrid-solar-data)

repository contains much Python code to analyze the entire Ausgrid dataset. However, it should not be needed for this benchmark.