Electricity Consumption Forecasting for Seafood Processing Plants Using a Hybrid ANN–PSO Model

Tóm tắt

The study develops a hybrid ANN–PSO model to forecast the electrical load of a seafood processing plant in Sóc Trăng, where consumption fluctuates strongly due to seasonal production and refrigeration systems. Data were collected from an MFM-384-C meter (1 hour/sample for 1 month) and processed through an HMI WEINTEK MT8071iE on an IoT platform. The ANN–PSO model uses a 1–5–1 structure, with PSO optimizing weights and biases to improve accuracy. Results show very low errors: hourly forecasts are mostly