cost-calculator

Cost calculator for https://www.offgridai.us

https://github.com/offgridai-us/cost-calculator

Science Score: 13.0%

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Keywords

calculator offgrid solar streamlit
Last synced: 6 months ago · JSON representation

Repository

Cost calculator for https://www.offgridai.us

Basic Info
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  • Stars: 15
  • Watchers: 2
  • Forks: 4
  • Open Issues: 0
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Topics
calculator offgrid solar streamlit
Created about 1 year ago · Last pushed 12 months ago
Metadata Files
Readme License

README.md

Introduction

This is a cost calculator for a datacenter powered by solar, batteries, and gas generation.

It can simulate a datacenter of any load anywhere in the world, with any combination of solar, battery, and gas generation. The output is a Levelized Cost of Energy (LCOE) in $/MWh, and a yearly financial model.

The code calculates the LCOE using the following steps: 1. It pulls weather data for the speciifed (lat, long) 2. It simulates the solar power from the weather data 3. It simulates the powerflow of the system between the solar, battery, generator, and datacenter. 4. It calculates the annual cashflows and the LCOE of the system.

Usage

There are three ways to use this code:

1. Streamlit interface

streamlit run app.py

2. Command line interface

One-shot LCOE calculation

This simulates a single case. bash python calculate_lcoe_one_shot.py --lat 31.9 --long -106.2 --solar-mw 250 --bess-mw 100 --generator-mw 125 --datacenter-load-mw 100

(See calculate_lcoe_one_shot.py for all possible args)

LCOE Ensemble Calculation

This simulates a range of cases and saves the results to a CSV file. The "raw results" for every case are saved as a CSV, as well as the Pareto-optimal frontier on LCOE vs renewable-percentage. bash python run_ensemble.py You can define the test cases in run_ensemble.py.

3. Python

```python """There are three steps to calculate the LCOE: 1. Get solar weather data 2. Simulate powerflow 3. Calculate LCOE """

1. Get solar weather data

solaracdataframe = getsolarac_dataframe(lat, long)

2. Simulate powerflow

powerflowresults = simulatesystem(lat, long, solaracdataframe, ...)

3. Create DataCenter instance and calculate LCOE

datacenter = DataCenter( powerflowresults=powerflowresults, solar=100, bess=100, generator=125, generatortype="Gas Engine", # CAPEX rates solarcapextotaldollarperw=0.25, besscapextotaldollarperkwh=0.10, # O&M rates solaromfixeddollarperkw=0.01, bessomfixeddollarper_kw=0.01, ... # See datacenter.py for all options and defaults )

lcoe = datacenter.calculate_lcoe() ```

Authors

Owner

  • Name: offgridai.us
  • Login: offgridai-us
  • Kind: organization
  • Email: feedback@offgridai.us

How off-grid solar microgrids can power the AI race

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Dependencies

requirements.txt pypi
  • numpy ==1.26.3
  • pandas ==2.2.0
  • plotly ==5.18.0
  • streamlit ==1.31.1