As the number of large-scale solar photovoltaic (PV) facilities increase globally, so do concerns about their environmental and community impacts. Combining solar PV and agriculture through agrivoltaics presents a promising solution to land use conflict, but economic and logistic barriers limit widespread adoption of agrivoltaics designs. To address these gaps, microclimate simulation tools are developed to design and evaluate potential agrivoltaics systems. A computational fluid dynamics (CFD) model is developed to simulate agrivoltaics design scenarios for insights into solar panel cooling from vegetation below, with implications for solar panel power production under certain conditions. The Agrivoltaics Radiation Tool (ART) is developed and used to analyze an agrivoltaics incentive program, with an emphasis on science-based recommendations for improved policy implementation. Another CFD model is developed to analyze airflow through agrivoltaics systems and compare the windbreak effect of solar panels to natural windbreaks. Finally, a machine learning (ML) model is developed to serve as a surrogate to the CFD windbreak model for implementation in agrivoltaics crop models. Results point to opportunities and challenges in agrivoltaics, demonstrating the need for interdisciplinary approaches informed by industry standards.