PyPSA-UK

A PyPSA-based framework for modelling energy storage integration, renewable energy resources and power system optimisation.

📖Overview

This repository contains Python code for power system modelling and optimisation using PyPSA (Python for Power System Analysis). The project focuses on:

• GB grid simulation and optimisation
• Optimal energy storage allocation
• Battery degradation modelling economically and physically
• Energy storage investment expansion planning
• Renewable integration studies
• Scenario-based optimal power flow analysis

GB 29 Bus with Interconnectors 2040

Renewable Generation for 2040 with Optimal Energy Storage Allocation

Installation

To use this code you need to install PyPSA as follows:

pip install pypsa

and then the following requirments:

• CPLEX - Adcademic version a high-performance, commercial software package for mathematical optimization
• numpy – numerical computing and array operations
• scipy – scientific computing and sparse matrix calculations
• pandas – data structures for time series and component data
• xarray – labeled multidimensional data handling
• linopy – optimization modeling interface used by PyPSA
• networkx – network graph calculations
• matplotlib – plotting and visualization
• seaborn – statistical plotting utilities
• plotly – interactive plotting
• netcdf4 – reading and writing NetCDF data files
• validators – validation utilities
• deprecation – API deprecation warnings
• highspy – HiGHS optimization solver interface

Create a virtual environment and activate it (optional but recommended)

python -m venv pypsa-env

then run following code:

Investment_GB29Ed_2040_Whole_Year_All_Storage.py

Licence

PyPSA-UK is released under the MIT License.

Cite Us

If you use PyPSA for your research, we would appreciate it if you would cite the following paper:

• Sobhan Naderian, Marko Aunedi, “Optimal Energy Storage Deployment in GB Transmission Grid Using Open-Source Software” MDPI Energies, 2026, under review