Interested in Distribution Networks, Distributed Energy Resources (DERs), and Smart Grids?
Here you will find multiple repositories produced by Prof Nando Ochoa’s Research Team at The University of Melbourne. These repositories can help you understand and develop advanced techniques to model and analyse distribution networks with DERs such as residential solar PV ☀️🏡, electric vehicles 🔌🚗, batteries 🔋, etc.
The repositories have been designed for power engineering students (undergraduate and postgraduate), power engineers, researchers, consultants, etc. They require some knowledge of coding (of course! 🤓) but not too advanced. If you are a decent coder, you will manage 😉.
In most of our repositories, you will be using OpenDSS - an open-source distribution network analysis tool developed by the Electric Power Research Institute (EPRI), USA. OpenDSS will be used here entirely with Python code thanks to the dss_python module developed by researchers at the University of Campinas, Brazil. You will also use anonymised network and demand data that was kindly provided by the Australian distribution company AusNet Services. So, thanks to our colleagues and friends at EPRI, UNICAMP, and AusNet Services for these important contributions to the world! 🙏
This tutorial will guide you, using interactive code via Jupyter Notebook and Python, through the different steps to run advanced, detailed time-series simulations to properly assess the technical impacts of DERs (such as solar photovoltaics) on realistic three-phase unbalanced distribution networks.
- Part 0: Using dss_python
- Part 1: Advanced Tools for the Analysis of Three-Phase Unbalanced LV Networks
- Part 2: Time-Series Analysis and PV Hosting Capacity of LV Networks
- Part 3: Volt-Watt Control and PV Hosting Capacity of LV Networks
- Part 4: Monte Carlo Assessment of PV Hosting Capacity of an Integrated MV-LV Network
Want to learn more about DER Hosting Capacity? Check out these reports [1], [2], these papers [3], [4], [5] and the webinars of our projects PV-Rich Distribution Networks and EV Integration.
Want to learn more about Model-Free DER Hosting Capacity? Check out the webinars and reports of our Model-Free Project.
These repositories demonstrate, using interactive code via Jupyter Notebook and Python, different Operating Envelope (OE) algorithms that could be implemented by distribution companies. This work is part of the CSIRO-funded projects Accelerating the Implementation of Operating Envelopes Across Australia and Assessing the Benefits of Using OEs to Orchestrate DERs Across Australia.
- Calculation of OEs considering LV only
- Calculation of OEs considering MV and LV
- OE Algorithm 1: Ideal (Integrated MV-LV)
- OE Algorithm 2: Asset Capacity (Integrated MV-LV)
- OE Algorithm 3: Asset Capacity & Critical Voltage OE (Integrated MV-LV)
- OE Algorithm 4: Asset Capacity & Delta Voltage OE (Integrated MV-LV)
Want to learn more about Operating Envelopes? Check out this free online course on Operating Envelopes and Their Implementation, also this article [6], these papers [7], [8], [9] and the webinars of our projects Project EDGE and Assessing the Benefits of Using OEs to Orchestrate DERs Across Australia.
Want to learn more about Model-Free Operating Envelopes? Check out these papers [10], [11] and our Model-Free Project.
This repository provides four real large-scale three-phase Australian MV (22kV L-L) distribution networks and corresponding pseudo LV networks (European-style three-phase networks for urban and two-phase networks for rural) down to the connection point of single-phase customers (the pseudo LV networks have been created following modern Australian LV design principles [12]). These networks are run and operated by AusNet Services, a distribution company in the State of Victoria. This repository also includes a large pool of anonymised real 30-min resolution residential demand (kW) profiles. Furthermore, this repository provides the code necessary to extract network data, run time-series power flow simulations, and visualise the results including geographical data, voltage profiles, and asset utilisation.
This repository provides realistic time-series EV profiles necessary to carry out detailed distribution network studies.
Want to learn more about MV-LV networks and pseudo LV networks? Check out this paper [12] and these reports [13], [14], as well as the webinars of our projects Advanced Planning of PV-Rich Distribution Networks and EV Integration.
Want to learn more about EV Profiles? Check out this paper [15] and the webinars of our project EV Integration.
These repositories show how to manage DERs directly by using Active Network Management (ANM) or indirectly by using Operating Envelopes (OEs).
- ANM of LV Networks - Rule-Based Approach
- ANM of MV Networks - Balanced AC OPF for Distributed Generation Studies
- OEs - The Basics
Want to learn more about AC OPF for Distribution? Check out this article [16] and these papers [17], [18], [19], [20], [21], [22], [23].
Nando Ochoa (luis.ochoa@unimelb.edu.au ; https://sites.google.com/view/luisfochoa)
Want to learn more about our research with industry? Check out Our Projects.
The contents of these repositories have been produced with direct and/or indirect inputs from multiple members (past and present) of Prof Nando Ochoa’s Research Team. So, special thanks to all of them (many of whom are now in different corners of the world).
- https://sites.google.com/view/luisfochoa/research/research-team
- https://sites.google.com/view/luisfochoa/research/past-team-members
We also would like to thank AusNet Services for making it possible to share anonymised data with the power community around the world. 🙏
