Techno-economic comparison of dispatch strategies for stand-alone industrial demand integrated with fossil and renewable energy resources

Abstract

The industrial sector is the world’s largest energy consumer and carbon emitter. In Iran, the importance of applying new energy resources is even greater due to industrial growth, the capacity shortage of conventional power plants, and the low reliability of power supply during peak times. However, detecting the optimal dispatch strategy for managing the application of nonrenewable sources along with renewable technologies is a major challenge. In this study, we performed the design and optimization of a hybrid energy system, including photovoltaic, wind turbines, a diesel generator, a natural gas generator, and a storage bank, for a small-scale industrial case in a southern industrial park of Iran. The HOMER Pro software was utilized to optimize the hybrid renewable energy system and supply an average demand of about 820 kWh/day through five different dispatch strategies. The results showed that predictive dispatch, with the foresight of renewable production and demand in the next 48 h, outperforms combined dispatch, cycle charging, load following, and generator order dispatch strategies. The optimum scenario showed an 84% renewable fraction, a cost of energy of 0.105–0.120 $/kWh, and about 24.8% excess power, which improves local grid reliability and the potential for renewable energy utilization by the industrial unit. The technical results showed that the optimum use of battery bank capacity based on upcoming predicted power consumption/generation potential effectively reduces the need for installation capacity of power equipment, which is critical for remote industrial demands.