Large-Scale Processing and Validation of Grid Data for Assessing the Fair Spatial Distribution of PV Hosting Capacity

TL;DR

This paper develops a large-scale methodology for processing and validating grid data to assess and ensure fair spatial distribution of PV hosting capacity, addressing challenges from increasing PV integration and electrification.

Contribution

It introduces a comprehensive data validation process and a novel approach to evaluate spatial fairness in PV hosting capacity across distribution grids.

Findings

Validated grid data using rule-based and power flow checks.

Proposed a fairness-based assessment method for PV hosting capacity.

Quantified economic costs of spatial fairness in PV deployment.

Abstract

The integration of PV systems and increased electrification levels present significant challenges to the traditional design and operation of distribution grids. This paper presents a methodology for extracting, validating, and adapting grid data from a distribution system operator's (DSO) database to facilitate large-scale grid studies, including load flow and optimal power flow analyses. The validation process combines rule-based sanity checks and offline automated power flow analyses to ensure data consistency and detect potential errors in the grid database, allowing for their correction. As a practical application, the paper proposes a method to assess the PV hosting capacity of distribution grids, with a focus on ensuring fairness in their spatial distribution. By incorporating fairness criteria into the analyses, we quantify the costs (in terms of missed revenues from selling PV generation) associated with spatial fairness.