Distribution networks measured background voltage variations, probability distributions characterization and Solar PV hosting capacity estimations

Highlights

• Long-term, high-time resolution measurements of pre-connection voltage with 33 distribution transformers.

• A method for obtaining input to stochastic hosting capacity studies from measurements of voltage magnitude and other aleatory uncertainties.

• Identifying which statistical properties of the pre-connection voltage impact the hosting capacity for solar PV.

• General knowledge of the range and details of the background voltage variations essential for hosting capacity estimation, measurements for many years were not needed and 11 % underestimation of HC from 10 am – 2 pm sunny-hours to the whole day.

Abstract

Solar photovoltaics in electricity distribution networks is often limited by the rise in voltage magnitude. The pre-connection voltage magnitude is an important factor that determines the hosting capacity.

This paper studies to which extent details of the pre-connection voltage magnitude impact the hosting capacity. Extensive measurements of voltage magnitude and solar power production were obtained for a number of distribution networks with 10-minute resolution. The measured background voltage during the sunny-hours from the two-year measurements was used to obtain representative probability distribution functions. A guide for selecting the time-of-day (ToD) used is presented.

The obtained probability distribution functions are applied to estimate the stochastic hosting capacity for a low-voltage distribution network with 83 customers. The impact of various details on the hosting capacity are studied.

The results show that general knowledge about the range of the pre-connection voltage are essential for the hosting capacity estimation. Measurements over one year were shown to be sufficient to estimate the hosting capacity. The hosting capacity considering the entire day was underestimated by 11 % when compared to the 10 am – 2 pm sunny-hours. The proposed method is general and can be applied to other aleatory uncertainties and other types of hosting capacity studies.