Transmission and Distribution Co-Simulation Platform for Renewable-Dense Power Systems with High Solar Penetration
Agboola Alao, Olatunji Adeyanju, Manohar Chamana, Stephen Bayne, Md Shahin Munsi, Tyreek Alexander, David Graves, Felipe Silva, Argenis BilbaoThe rapid acceleration of solar photovoltaic (PV) deployment has introduced unprecedented complexity into power system dynamics, particularly as solar resources transition from peripheral generation to a primary driver of electricity demand patterns. High solar penetration alters traditional load profiles, introduces fast variability and uncertainty, reduces system inertia, challenges voltage and frequency regulation, and leads to intricate interactions between power layers. Traditional simulation tools that decouple transmission and distribution domains fail to capture these dynamic interactions, resulting in inaccurate stability assessment and suboptimal operational decisions. This paper presents the development of a transmission and distribution (T&D) co-simulation platform specifically tailored for renewable-dense power systems with high levels of distributed solar PV. The platform integrates average PV inverter models, distribution feeders, and bulk transmission network dynamics through an iterative coupling algorithm, enabling the study of phenomena such as voltage rise, power flows, and frequency excursions driven by PV variability. Case studies demonstrate how high solar penetration magnifies interactions across network layers, exacerbating voltage imbalance in distribution networks and propagating disturbances into the transmission system. The platform supports coordinated control design, DER dispatch strategies, and resilience metrics such as frequency nadir and energy not supplied (ENS). Results highlight the crucial role of co-simulation in quantifying the impacts of high PV penetration on both T&D networks, informing planning, real-time operations, and policy frameworks for future grids. This work underscores the need for integrated analysis to accurately represent solar dynamics, inverter behavior, and system response across multiple time scales.