Enhancing renewable energy and electric mobility integration through strategic optimization planning of distributed energy resources in an agrifood farm

This project introduces a planning framework that optimizes how distributed energy resources (DERs) and electric mobility are integrated on an agrifood farm. The goal is to help farms cut carbon emissions and become more resilient to power outages. A major obstacle for farm‑scale renewable energy design is the lack of detailed smart‑meter data. To solve this, we built a custom algorithm in MATLAB that recreates hourly electricity‑use profiles from the monthly Time‑of‑Use (ToU) tariff band information that is easy to obtain. The recreated hourly profiles let us size solar‑photovoltaic arrays, battery storage, and electric‑vehicle chargers accurately. We tested the algorithm by comparing its output to real hourly consumption data from

both residential and non‑residential farm facilities across different seasons. Performance was measured with normalized root‑mean‑square error (nRMSE) and normalized mean absolute error (nMAE). Both metrics showed that the reconstruction is highly accurate. This simulation‑based approach gives agricultural engineering students a hands‑on method to design, optimize, and assess the economic and environmental viability of integrated farm energy systems—without needing costly metering equipment.

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