Integrated optimization of production planning and electric trucks charging and discharging scheduling

Abstract

The majority of supply chains in any manufacturing industry rely on heavy trucks for their flow of material from suppliers to end-users. Transportation by these heavy trucks causes greenhouse gas emissions detrimental to the environment. To cope with challenges caused by environmental issues and energy crises, replacing heavy trucks with electric trucks seems to be a viable solution. They can be considered as an energy resource that supports grid-to-vehicle and vehicle-to-grid, enabling efficient energy management for smart manufacturing systems and supply chains. Proper scheduling of charging and discharging activities of electric trucks also supports the penetration of renewable energy sources with volatile energy generation. This paper encourages sustainable practices and proposes a mixed integer programming model for the simultaneous optimization of production planning and transportation scheduling of electric trucks in a smart manufacturing system. The uncertainty sources considered in this system include power generation of renewable energy, transportation patterns, and customer demand for products. The results show that utilizing electric trucks in smart manufacturing with real-time pricing, save up to 11% of the total cost compared to traditional manufacturing systems without electric trucks and renewable energies. This integration also increases the efficient utilization of renewable energies such as wind and solar powers. The savings decrease to 4% and 8% under flat and time-of-use electricity pricing strategies. The results also highlight the complexity of setting utilization level of electric trucks and renewable energy sources into well-implemented sustainability standards.