Spatio-Temporal Probabilistic Voltage Sensitivity Analysis - A Novel Framework for Hosting Capacity Analysis

TL;DR

This paper introduces a novel, efficient probabilistic framework for hosting capacity analysis in smart grids, enabling accurate voltage violation prediction with reduced computational effort.

Contribution

It presents a new analytical method to compute voltage change distributions caused by distributed PVs, eliminating the need for extensive scenario simulations.

Findings

Validated on IEEE test systems showing accuracy

Reduces computational complexity compared to traditional methods

Provides probabilistic voltage violation assessments

Abstract

Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefore, PV Hosting capacity (HC) is being used as a planning tool to determine the maximum PV installation capacity that causes the first voltage violation and above which would require infrastructure upgrades. Traditional methods of HC analysis are computationally complex as they are based on iterative load flow algorithms that require investigation of a large number of scenarios for accurate assessment of PV impacts. This paper first presents a computationally efficient analytical approach to compute the probability distribution of voltage change at a particular node due to random behavior of randomly located multiple distributed PVs. Next, the derived distribution is used to identify voltage violations for various PV penetration levels and subsequently determine the HC of the system without the need to examine multiple scenarios. Results from the proposed spatio-temporal probabilistic voltage sensitivity analysis and the HC are validated via conventional load flow based simulation approach on the IEEE 37 and IEEE 123 node test systems.