Analytical Inverter-Based Distributed Generator Model for Power Flow Analysis

TL;DR

This paper introduces an analytical inverter-based distributed generator model that accurately captures inverter characteristics, improving power flow analysis in distribution systems with high solar penetration.

Contribution

It develops a novel inverter-based DG model considering inverter topology, sensing, and control, extending positive sequence generator models for better accuracy and convergence.

Findings

Model accurately predicts inverter behavior in power flow simulations.

Simulation results demonstrate robustness and improved convergence.

Model effectively handles high solar penetration scenarios.

Abstract

Quantifying the impact of inverter-based distributed generation (DG) sources on power-flow distribution system cases is arduous. Existing distribution system tools predominately model distributed generation sources as either negative PQ loads or as a PV generator and then employed a PV-PQ switching algorithm to mimic Volt/VAR support. These models neglect the unique characteristics of inverter-based distributed generation sources, have scalability and convergence issues, and are ill-suited for increasing solar penetration scenarios. This work proposes an inverter-based DG model accounting for the inverter's topology, sensing position, and control strategies. The model extends recently introduced analytical positive sequence generator models for three-phase studies. The use of circuit-simulation based heuristics help achieve robust convergence. Simulation of the PG&E prototypical feeders using a prototype solver demonstrate the model's accuracy and efficacy.