Development of a state estimator for distribution grids

OData support
Dr. Farkas Csaba
Department of Electric Power Engineering

The basic roles of system operation are to insure continuous and stable power supply and to operate safe and efficient power system. To achieve proper stability and manageability it is necessary to possess the adequate quantity and quality of data of the system being operated, therefore SE (State Estimation) is one of the most crucial and vital functions of EMS (Energy Management System). Its role is to evaluate the possible state of the power system and to establish a consistent database for the calculator and analyser software.

The spread of remote measurements and telemechanics of the distribution system, and increasing of the renewable energy sources cause that currently passive networks become active. Due to the rapidly changing dynamics, smart grid network functions need to be evolved which enable effective monitoring and controlling. Distribution system differ from transmission systems – while monitoring them and the cognition and regulation of their status become more and more critical task – therefore the need arises to adapt EMS functions to DMS (Distribution Management System). DSSE (Distribution System State Estimation) will play a crucial role in enabling the execution of such smart grid functions as DA (Distribution Automation) and DR (Demand Response). DSSE serves basis for the EMS software of the active distribution grids of the future. The mentioned function can gain an important role if system operation wishes to keep up with the gradually increasing proportion of hybrid and electric vehicles and renewable energy sources, with respect to safety, quality, continuity and sustainability; simultaneously wanting to ensure the possibility of new elements spreading further.

In my thesis I wish to present the most important network parameters, system operation itself and the basic philosophy of SE. I am giving a detailed analysis of the SE algorithm of my choice, highlighting the difference between the traditional and the DS state estimation processes. After a short discussion on the ACCS system, I am introducing the network model that was created for testing the DSSE function. Next, I am going to demonstrate and interpret the steps of the implemented algorithm. This is followed by testing and reviewing the software, which was generated with the help of the algorithm.

During the course of my work, I got acquainted with system operation, parameters revealing the status of the system and the SCADA systems in general. I gained valuable knowledge about the ACCS software platform and electric model. I chose the SE algorithm, which I thought the most suitable and I implemented it. I tested it on a small network. Finally, I generated a version of the desired SE function, which operates in ACCS, using Java programming language. This I studied with respect to the general requirements regarding the function.


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