MIT License

项目介绍

adrianghc/HEMS 是一个托管在 GitHub 上的开源项目,主要使用 Jupyter Notebook 编写,采用 MIT License 许可证,目前获得 16 个 Star、2 次 Fork。

仓库全名
adrianghc/HEMS
开源许可证
MIT License
Star 数
16
Fork 数
2
未关闭 Issue
5

README 摘要

HEMS - Home Energy Management System This is a partial implementation of a Home Energy Management System for a residential solar installation. It enables the user to schedule appliances in a targeted way, increasing energy self-consumption based on energy production predictions via weather forecasts. These predictions can achieve R² scores of over 0.9 when using global radiation data, or up to 0.8 when global…

完整内容见 GitHub 原始 README 或本页 。

常见问题

HEMS 用什么语言开发?

主要使用 Jupyter Notebook 编写,采用 MIT License 许可证,目前有 16 个 Star。

HEMS 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 HEMS 的源码?

可以直接克隆仓库:git clone https://github.com/adrianghc/HEMS.git;安装与运行步骤见仓库 README。

HEMS 最近还在维护吗?

仓库最近一次更新为 2021年6月6日,当前有 5 个未关闭 Issue;Star 数为 16,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

HEMS - Home Energy Management System for a residential PV installation. It enables the user to schedule appliances in a targeted way, increasing energy self-consumption based on energy production predictions via weather forecasts.

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
36
价值分
11
活跃状态
活跃

语言占比

C
C++
HTML
Jupyter Notebook
Makefile
Python
Shell

贡献者

README

HEMS - Home Energy Management System

This is a partial implementation of a Home Energy Management System for a residential solar installation. It enables the user to schedule appliances in a targeted way, increasing energy self-consumption based on energy production predictions via weather forecasts. These predictions can achieve R² scores of over 0.9 when using global radiation data, or up to 0.8 when global radiation data is not available. The allocation of tasks can reach perfect efficacy if sufficient energy for all appliances is expected to be available, and an efficacy of up to about 63% allocated energy if total task energy consumption is expected to be as high as 150% of the total available energy budget.

This application was conceptualized and developed in the context of a master’s thesis in computer science at Freie Universität Berlin, submitted in June 2021. The thesis manuscript serves as documentation and is available in this repository in the doc directory.

This prototype implementation consists of a C++ program for Linux and a set of accompanying Python tools.

Prerequisites

This project can be opened as a Visual Studio Code workspace that includes convenience functions like launch configurations and tasks for building and tests.

The C++ 14-based core portion of the HEMS program (in src and include) has the Boost C++ library as the only prerequisite. Builds were produced and tested with Boost version 1.73.0, which can be installed with

$ sudo apt install libboost1.73-all-dev

on Debian-based distributions.

The Python tools (in tools) are based on Python 3.8. Each tool lists its dependencies in a corresponding requirements.txt file, which can be installed via

$ pip3 install -r requirements.txt

Build

$ make

Run

To run the HEMS core:

$ cd build/native/hems
$ ./launcher

To run a tool, go to its directory and

$ ./run.sh

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