Probabilistic modeling of short term fluctuations of photovoltaic power injection for the evaluation of overvoltage risk in low voltage grids

Probabilistic Study of the Impact on the Network Equipment of Changing Load Profiles in Modern Low Voltage Grids

“…In previous studies, this tool was used for assessing the respect of technical constraints (voltage level, voltage imbalance…) in grids in the presence of a large number of PV installations [4]- [5]. However, it is also of interest for the DSO to compute the power flows in the different feeders as well as in the MV/LV substation as it has a direct impact on the lifetime of the equipment.…”

“…Such a study is vital for the DSO in order to avoid unexpected investments due to a premature aging of the network facilities. The methodology relies on a probabilistic model based on quarterly energy flows coming from smart meters installed at some customers [4]- [5]. Although these smart meters are expected to be widely deployed in the future, this data gathering is still limited to some sparse areas of the distribution grids.…”

Probabilistic framework for evaluating droop control of photovoltaic inverters

“…In this scope, the restructured probabilistic framework has been used in this paper for parameter tuning of droop control in an existing LV network (Section 3). The results of this evaluation are compared to the ones obtained from the original probabilistic framework that is presented in [26][27][28].…”

“…This last one is based on a probabilistic framework previously developed by the authors in [26][27][28] but which never considered the action of P/V controllers. The undeniable advantage of the probabilistic model is the consideration of multiple possible network states, represented by the Cumulative Distribution Functions (CDFs) of the variable parameters, in a fast optimised way.…”

“…The probabilistic analysis can lead to refined solutions in techno-economic terms, compared to the usually oversized and costly ones of deterministic approach. For this reason, in this paper, the initial probabilistic framework [26][27][28] is restructured such that it integrates P/V droop control; in such a way not only the currently possible system states but also the effect of a control strategy are analysed in a probabilistic manner (Section 2). Thus, the first objective of this paper is to evaluate droop control in a model that is more realistic compared to previous deterministic models.…”