Optimizing Industrial Process Flow for Energy Cost Reduction through Demand-Side Management

Energy demand has grown rapidly over the past decades and will continue to grow in the future. The rise in energy demand is primarily due to industrialization and the evolution from a conventional to a smart-grid paradigm. Therefore, the future energy grids have to be redesigned in order to adapt to the ever-growing global energy demand and achieve environmental goals. Demand-side management (DSM) is a promising solution to these challenges and can significantly improve the financial performances and reliability of electrical power systems. This paper presents a new DSM solution for industrial users in a smart grid. The goal of the load scheduling model is to minimize the operational cost of the industrial users while helping the utility providers to reshape the peak load profile. The proposed linear programming model allows the users to preset the target demand of end-product throughout the time horizon while monitoring the rescheduling of workforce so that the operation cost can be reduced. Besides, users have the flexibility to set constraints to avoid the maximum demand penalty imposed by the utility company. Simulation results show that DSM is able to reduce the peakto-average ratio of the total power demand, as well as industrial user's electricity charges. The proposed model is feasible and realistic to be applied in the industry sectors since many practical constraints are included.