A multi-objective scheduling model for a flexible manufacturing system to reduce peak load using an energy storage system.

The global manufacturing sector is currently subject to Time-of-Use energy pricing, compelling them to avoid peak demand. Overuse of energy by industries can lead to the utilisation of thermal power plants, which can have a severe influence on the environment. Energy-efficient production scheduling can help manufacturers to reduce energy costs. This paper focuses on the energy efficiency and production output of a flexible manufacturing system (FMS) consisting of five machines and operates based on sequence-dependent scheduling. A centralised energy storage system is considered in the model to improve the voltage profile during peak load hours and lower peak load demand. A simple and effective strategy is proposed for peak load shaving via real-time scheduling of the FMS. The scheduling problem is treated as a multi-objective issue and tackled using a whale optimisation algorithm. The optimisation results demonstrate the effectiveness of the proposed model in reducing peak demand from the energy supplier side to zero by utilising the energy storage system while also maintaining an acceptable makespan. The model can help energy-intensive industries reduce peak demand by moving load to an energy storage system. By adopting these measures, industrial facilities can reduce their carbon footprint and contribute to the global effort to mitigate climate change. Highlights: The study focuses on a flexible manufacturing system's energy efficiency and production output. The study uses a centralised energy storage system to improve the voltage profile. The whale optimisation algorithm is used to solve the multi-objective problem. [ABSTRACT FROM AUTHOR]