This research demonstrates AI-optimized coordination to enhance voltage regulation in distribution networks, improving reliability and reducing OLTC stress.
The rapid growth of photovoltaic (PV) generation in modern distribution networks has fundamentally altered feeder operation, giving rise to challenges such as voltage rise, reverse power flows, and increased stress on On-Load Tap Changers (OLTCs). Unlike traditional load-driven variations, PV-induced fluctuations are fast and irregular, often causing frequent OLTC operations. Such excessive switching not only accelerates mechanical wear and shortens the expected lifetime of tap changers but also undermines feeder reliability. In parallel, the deployment of smart inverters equipped with Volt/VAR droop functionality provides a flexible means of localized voltage regulation. However, when these devices operate independently, their reactive power actions may conflict with OLTC responses, resulting in control instability and inefficient operation. To address this gap, this paper introduces an AI-optimized coordination framework that harmonizes smart inverter Volt/VAR support with OLTC operation. The proposed approach reduces unnecessary tap movements, alleviates thermal and mechanical stress on transformers, and enhances overall feeder reliability in PV-rich distribution networks.
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Mohare et al. (2025) studied this question.
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