Title: Probabilistic Assessment of PV-Battery System Impacts on LV Distribution Networks,
Abstract: The increasing uptake of residential batteries has led to suggestions that
the prevalence of batteries on LV networks will serendipitously mitigate the
technical problems induced by PV installations. However, in general, the
effects of PV-battery systems on LV networks have not been well studied. Given
this background, in this paper, we test the assertion that the uncoordinated
operation of batteries improves network performance. In order to carry out this
assessment, we develop a methodology for incorporating home energy management
(HEM) operational decisions within a Monte Carlo (MC) power flow analysis
comprising three parts. First, due to the unavailability of large number of
load and PV traces required for MC analysis, we used a maximum a-posteriori
Dirichlet process to generate statistically representative synthetic profiles.
Second, a policy function approximation (PFA) that emulates the outputs of the
HEM solver is implemented to provide battery scheduling policies for a pool of
customers, making simulation of optimization-based HEM feasible within MC
studies. Third, the resulting net loads are used in a MC power flow time series
study. The efficacy of our method is shown on three typical LV feeders. Our
assessment finds that uncoordinated PV-battery systems have little beneficial
impact on LV networks.