Last update: 11th Sep 2024
We must be at the forefront of modelling and coding tools and practices to carry out advanced studies involving Future Distribution Networks, DER Integration, Smart Grids, and Data Analytics. Some of the leading research tools used in our Research Team include OpenDSS, Anaconda/Python, and GitHub. These and other tools, such as Slack, Teams, and Asana, not only help to develop and manage our research but also provide essential skills valuable in the industry.
Below are links to our publicly available OpenDSS training material, which is key to our research.
To see the power of OpenDSS in action, you need to use it for specific distribution network studies. We have put together advanced training material focusing on DER Hosting Capacity and Operating Envelopes, with examples that include large-scale medium-voltage (MV) and low-voltage (LV) networks, as well as time-series demand and DER profiles.
Presentations and Files to Run Simple Simulations
We have put together training material (presentations and files to run simulations) designed to give you a quick exposure to:
time-series analyses of distribution networks (critical for studies involving solar PV, electric vehicles, etc.); and,
the use of the COM server via MS Excel VBA and Python (which will facilitate more complex studies).
This training material, all available on Research Gate, has multiple parts (listed below) that should be done sequentially. Each of them has a presentation. In addition, from part 3, there are also files for you to run your own simulations according to the examples. Since this material is for beginners, the examples consider very simple MV and LV networks. Nonetheless, the OpenDSS implementation aspects that will be learned can be generalised to any distribution network.
State-of-the-Art Modelling of Distribution Networks
This preso will give you an introduction to challenges faced by distribution companies due to the uptake of distributed energy resources and why it is important to have adequate models when investigating impacts and solutions.
This preso is a general intro to OpenDSS, what it is, key features, etc.
Simple MV Network (and here are the files to practice)
With this preso, we start the hands-on training. You will learn important modelling considerations of OpenDSS, put together a simple MV network, and run basic hourly time-series analyses involving OLTCs and a generator.
LV Networks 3ph+n (and here are the files to practice)
This preso moves the hands-on training to the LV part. Here you will model single-phase houses and play with minute-by-minute time-series analyses involving solar PV.
OpenDSS via Excel VBA and COM (and here are the files to practice)
OpenDSS is great. But even better when we drive it from a more flexible environment (also known as co-simulation). With this preso, you will learn how to do so from MS Excel VBA using the COM interface. More importantly, you will learn how to do basic control of elements or participants in the network. All using Excel!
OpenDSS via Python and COM (and here are the files to practice)
The serious research starts with Python :-) This preso will show you how to drive OpenDSS using Python and do the basic control from the previous part. You will also learn how to improve performance when dealing with the COM interface.
Advanced Analysis (and here are the files to practice)
This preso takes the analysis of solar PV and LV networks to a slightly more advanced level. Here you will learn how to carry out more realistic analyses using multiple residential demand profiles, multiple solar PV generation profiles, and a real LV circuit (aka feeder) from the UK. This is done with Excel VBA but the principles apply to Python or any other programming language.
PV Inverter Functions (and here are the files to practice)
With this preso, you will learn how to use the PV inverter functions (which are common these days) embedded in OpenDSS.
All the training material can also be found in this Research Gate project: https://www.researchgate.net/project/OpenDSS-Training-Material.
Note: Since OpenDSS continues to evolve (thanks EPRI!), the content above might not necessarily consider the latest functionality. But the principles will be similar :-)
Once you go through the material above, you can move on to more sophisticated uses of OpenDSS, driving it through Python, using the native dss_python, and applying all of this to realistic case studies. More info in the next section.
Links to real LV network models and time-series profiles
As part of the "Low Voltage Network Solutions" Project funded by ENWL in the UK and completed in 2014, we made available 25 real residential, underground UK LV networks fully modelled in OpenDSS, including large sets of time-series profiles of demand and low carbon technologies (e.g., PV, EVs, EHPs, uCHP). For the corresponding documentation and files use the links below.