This NSF project aims to design and evaluate honeybee-inspired virtual electric peer-to-peer networks to enable efficient and resilient control of distributed energy resources. These resources include electric vehicles, heat pumps, electric water heaters, and battery energy storage systems at the distribution level. Existing electrical infrastructures are undersized to handle increasing loads, and a lack of effective coordination among these resources further exacerbates this challenge. Inspired by the decentralized coordination mechanisms observed in honeybee colonies—where energy (food) is exchanged among members in a process called trophallaxis—this project will develop a bio-inspired cyber-physical system where distributed resources (“bees”) and storage systems (“hive”) dynamically allocate energy. By applying principles from collective insect behavior, this research seeks to transform energy coordination, benefiting grid operators and consumers alike. The intellectual merits of the project include novel mathematical models based on trophallaxis, development of bio-inspired control strategies, and validation through virtual testbeds and real-world demonstrations. The broader impacts include advancing non-wire alternatives that enhance grid resilience, improving access to electricity services, and fostering interdisciplinary knowledge exchange between biology, computing, and engineering. Additionally, the project will provide publicly available open-source software, engage students through an undergraduate design competition, and disseminate findings through workshops and outreach initiatives. This project will address existing technical challenges in energy coordination by translating honeybee trophallaxis into mathematical models and integrating them into an innovative cyber-physical framework. It will develop predictive models for uncertain building loads and energy behaviors using stochastic transfer learning. Additionally, it will create bidirectional biology-technology knowledge transfer frameworks to inform control-oriented models across multiple system layers. New bio-inspired control methods will be designed to optimize peer-to-peer energy sharing and grid operations. The project will leverage virtual testbeds using Python and GridLAB-D for rigorous evaluation, with experimental demonstrations conducted at the University of Colorado Boulder’s microgrid. By combining expertise from biology, computer science, and engineering, this research will generate novel strategies for resilient, adaptive, and efficient grid operations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.