The changing requirements in the distribution grids demand for more detailed knowledge of loading situations as well as a better analysis of the grids' performance. Usually represented by single peak load power consumption values, the loads of private customers are not considered adequately by the DSO in the distribution grid planning process. The utilization of extreme scenarios in the planning process without consideration of their probability can result in inappropriate grid reinforcements. In this paper, the added value of modelling the demand of private customers probabilistically in the planning process is o utlined and demonstrated with the help of a simulation environment, called SimoNA. Based on the multi agent concept, every grid user is presented by an agent with individual behavior and objective functions. The load agents derive their behavior from analyzed smart meter data. Additionally, they implement existing and future interdependencies with ambient grid users and the environment.
['Jan Kays', 'Andre Seack', 'Christian Rehtanz']
Consideration of smart-meter measurements in a multi-agent simulation environment for improving distribution grid planning