Solar Harvesting System for a Manufacturing Plant using Energy Forecasting ARIMA Model

Syaidathul Amaleena Rossli, Robiah Ahmad, Sathiabama T. Thirugnana


Load forecasting plays a substantial role in designing a power harvesting system. All manufacturing plants are highly dependent on the primary grid as their main power supply. Manufacturing plant consumes high electricity due to its nature that requires the plant to operate 24 hours a day. This study explores the potential of solar harvesting system for high grid consumer, and it is conducted to investigate the possibility for manufacturing plant X to rely on the renewable energy as an alternative power supply. Based on the demand of power that may vary during on-peak and off-peak in conjunction with business planning, a forecasting model has been developed to predict the plant’s demand. Based on the model developed, an optimal design of the PV harvesting system for the manufacturing plant is proposed using Hybrid Optimization of Electrical Renewable (HOMER) software with respect to economic aspect. The designed system managed to supply 88.2% of the demand meanwhile 11.2% were supplied by the main grid. However, the cost is intolerable with calculated operating and maintaining the system is RM14.7M (USD 3.57M) per month as compared to current cost which is significantly less. Further research on hybrid renewable energy harvesting may be conducted that may improve the proposed system.


ARIMA model; Energy forecasting; Manufacturing plant; Renewable energy; Solar harvesting

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