Poster Session 2, 11:30 AM - 12:15 PM: Room 165 [D11]

Presenter: Philip Paskal

Faculty Sponsor: Manish Wadhwa

School: Salem State University

Research Area: Computer Science

ABSTRACT

Small-scale solar systems are becoming more popular for residential and off-grid applications, but many lack the intelligent monitoring capabilities that some users may want. Users will often depend on either standalone charge controllers that regulate charging but provide limited system visibility and minimal automation beyond what the manufacturer provides, or the systems are expensive and can lock users into vendor product catalogues. This project presents the design and implementation of a Raspberry Pi based solar power monitoring system. The Pi communicates with the charge controller to retrieve voltage, current, and battery status information. A Python script processes these reported values to calculate instantaneous power output and estimate battery charge percentage. Benchmarks for success include accurate interpretation of controller data, stable operation, and recovery after power interruption. By integrating existing off-the-shelf hardware, this project demonstrates a practical and scalable approach to enhancing the efficiency, safety, and intelligence of small-scale solar energy systems.