Open Access

ARTICLE

Adaptive Droop Control Method for Grid-Forming Low-Voltage Interconnected Converters Considering High-Penetration Distributed Photovoltaics

Shu Zhou, Wenfeng Yang, Guoxing Wu^*, Xinming Jiang, Qingmiao Guo

Shenzhen Power Supply Bureau Co., Ltd., Power Grid Planning Research Center, Shenzhen, 518001, China

* Corresponding Author: Guoxing Wu. Email:

(This article belongs to the Special Issue: Advances in Renewable Energy and Storage: Harnessing Hydrocarbon Prediction and Polymetric Materials for Enhanced Efficiency and Sustainability)

Energy Engineering 2026, 123(5), 11 https://doi.org/10.32604/ee.2025.072997

Received 08 September 2025; Accepted 24 November 2025; Issue published 27 April 2026

Abstract

The integration of high-penetration distributed photovoltaic (PV) systems in low-voltage (LV) distribution networks introduces significant challenges, including voltage violations, power quality degradation, and coordination difficulties among multiple distributed energy resources. Grid-forming converters with droop control offer autonomous voltage and frequency regulation capabilities, yet conventional fixed-parameter droop strategies perform poorly in resistance-dominant LV networks under variable PV generation conditions. This paper proposes an adaptive droop control method that dynamically adjusts control parameters to address these challenges. The proposed strategy incorporates three key innovations: (1) power-flow-aware adaptive voltage droop coefficients specifically designed for resistance-dominant networks, (2) a distributed consensus-based optimization algorithm enabling decentralized coordination without centralized infrastructure, and (3) comprehensive stability constraints ensuring robust operation under time-varying parameters. Each grid-forming converter autonomously updates its droop coefficients based on local measurements of PV penetration, voltage deviations, and power flow patterns, while exchanging limited information with neighboring converters to achieve system-wide optimization. The adaptation mechanism includes rate limiters and dead-band functions to prevent parameter chattering and ensure smooth transitions during varying operating conditions. Small-signal stability analysis establishes explicit constraints on the adaptation rates and parameter ranges to maintain adequate stability margins throughout the operating envelope. Simulation validation encompasses three representative scenarios: 24-h steady-state operation with varying PV penetration (30%–120%), severe cloud transients with 70% generation drops, and evening load pickup transitions. Results demonstrate superior performance with voltage regulation within 0.95–1.05 p.u. at 120% PV penetration, power sharing errors below 3% vs. 15% for conventional control, and 65% faster transient response (0.8 vs. 2.3 s settling time). Compared to fuzzy logic methods, the proposed approach achieves 55% error reduction while eliminating expert knowledge requirements. The method enables resilient high-penetration PV integration in LV distribution networks through fully decentralized operation.

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Keywords

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