State Estimation Tool

A real-time data processing algorithm for estimating the operating state of the Mesogia pilot site of the Greek demo    

The State Estimation tool is a distribution system state estimator designed to ensure the observability of the Mesogia pilot site and thus to estimate its real-time operating state, using conventional and synchronized (PMU) measurements. The SE tool is a scalable and customizable function that can be adjusted to the needs of a DSO for state estimation purposes via open-source software.


Interview with:
Themistoklis C. Xygkis, Dr Electr. & Comp. Eng.
National Technical University of Athens (NTUA)

Interviewer: Themistoklis Xygkis, the State Estimation Tool is one of the key results of the Platone project whose development was coordinated by (NTUA) and the Hellenic Electricity Distribution Network Operator S.A. (HEDNO). Let´s assume I am a member of the IT department at a Greek DSO. I mostly spend my days implementing digital consortium partner NTUA solutions for our business. I am also responsible for finding products that could fit the current needs of our company. We currently want to increase the observability of our network’s state both in temporal and spatial contexts. Therefore, we want a tool that can leverage the existing infrastructure, be easily implemented, and communicate with legacy systems already in place. As a large organization, the solution must also be scalable. Having knowledge of the real network state can help us improve our services further by avoiding grid congestions, reducing voltage or thermal line limit violations, as well as minimizing demand and generation curtailment costs. Looking at the State Estimation Tool - how could it be helpful for the staff in the DSO IT department?

Themistoklis Xygkis: Our open-source and license free grid management tool might just be what you’re looking for. You can easily fork our solution via GIT and customize the code to your needs. To this direction, a state estimation functionality is the most appropriate solution for you, since it can support real-time network monitoring by delivering the most likely estimate of the actual network state. Importantly, the actual state is unobtainable due to the limited number of available measurements/ information, their associated errors, lack of synchronization etc. We have the expertise to develop a SE functionality customized to the needs of a DSO using open-source software.

Interviewer: Let's assume that the IT department will be able to execute the forking. What about support? Are you or somebody at your organization available to grant help if needed? How can an interested party get in touch with you? Is there a way to increase the State Estimation tool’s efficiency? How long is the inference time of the SE tool?

Themistoklis Xygkis: No problem at all. Even though this solution was created in a scientific project, we made sure that you can always reach out to us. The dedicated support needs to be remunerated though.

We can support you if needed, since we have a long-standing experience in power system state estimators. Besides, we are very interested in developing this functionality in distribution networks, since its operation currently is rather the exception than the rule.  

The SE accuracy, that is how close the estimated values of the network states and of the measured quantities are to their actual values, can be significantly improved by the integration of measurements from PMUs. It is worth noting though that merging PMU measurements with conventional, pre-existing ones can be a challenging task, which, if not properly tackled, may lead to poor convergence KPIs of the SE tool. Additionally, the locations of installed PMUs are also a matter of importance; certainly their placement in primary (HV/MV substations) is desired. As for their allocation downstream of a feeder, their optimal locations can be determined based on sophisticated optimization algorithms.    

Moreover, the installation of smart meters at LV consumers or any other state-of-the-art measurement units can also be beneficial to the SE tool.

Finally, the methodology which the SE tool is based on can also improve its efficiency; instead of a standard WLS model, the deployment of equality constraints for all measurements referring to zero injection is likely to boost the convergence speed and accuracy of the solution algorithm of the SE tool.  

Such a notion is irrelevant for WLS based SE.

Interviewer: Are there any training materials that could be used to help with internal distribution?

Themistoklis Xygkis: Unfortunately, we don’t have extensive tutorials or manuals. The only thing we offer is the functional description on GIT. We could offer webinars or on-premises workshops as a service if you’re interested.

The use of tutorial or manual is somewhat irrelevant regarding the SE tool. A functional description or even a mini workshop in order to get a deeper insight into the SE tool and learn how to update the network and the measurement models in case the network under study is expanded or new data are available due to installation of new measurement units are more helpful.  

Interviewer: What would be the next steps after having successfully implemented and tested your solution?
Themistoklis Xygkis: You can sign a support contract that includes training sessions and stand-by support. This will ensure further development of the tool internally as well as better understanding of such processes in general within our organization.  

Interviewer: Themistoklis Xygkis, thanks a lot for this interview!