Probabilistic framework for evaluating droop control of photovoltaic inverters

Abstract Active Power/Voltage (P/V) droop control is a method that is implemented in distributed photovoltaic (PV) units for the mitigation of overvoltage problems. This control does not require inter-unit communication and its benefit with respect to the on–off oscillations, the voltage level and the captured PV energy has already been demonstrated in previous studies. However, previous studies of P/V droop controllers only involved a deterministic “worst-case” approach on small networks and for restricted time periods, which often lead to oversized and costly technical solutions. In this paper, P/V droop control is for the first time evaluated with a probabilistic framework based on smart metering (SM) recordings in an existing Low Voltage (LV) network. Thanks to this approach, the uncertainty of PV energy injection, the randomness of the consumption loads and the fluctuations of voltage at the MV/LV transformer can be taken into consideration in the evaluation of the benefits related to the proposed control. The first objective of this paper is therefore to evaluate droop control in a model that is more faithful to the real operation of a LV network. Within this evaluation, the paper aims at doing a realistic parameter tuning of the control based on detailed probabilistic analysis. Practically, the evaluation model is based on a probabilistic framework previously developed by the authors but which up to now did not consider any voltage based droop (VBD) control. Thus, the second objective of this paper is to present a way for including time-based control strategies (here explained by means of droop control) in the probabilistic framework. The newly developed model is used to simulate an existing LV network and the results (EN50160 voltage requirements, curtailed PV generation, etc.) are compared to the scenario in which P/V droop control is not applied.