An energy-aware scheduling model under demand charge and time-based rate

In recent years, there has been a rising interest in improving energy efficiency and saving energy cost in the production scheduling because of the environmental concerns and energy cost. In this paper, we propose a mathematical optimization model that is designed to achieve energy-aware production scheduling for the general type of manufacturing setting where multiple jobs need to be processed on multiple machines. Considering energy charge based on time-based electricity price and demand charge based on peak power demand that are common practice of utility company to charge electricity bills for commercial and industrial consumers, the proposed optimization model can be formulated to minimize electricity bill. The key idea of the proposed model is to adjust production schedule in terms of the assignment and the deployment of each job in response to time-based electricity price while reducing peak power demand. Specifically, the proposed optimization model can be formulated to determine production schedule to adjust overall electricity power consumption while being aware of the power consumption pattern of each job, which can be extracted and formalized in an stage-wise fashion based on the nature of process. In particular, the proposed model can be formulated as a mixed integer linear program that can be solved by general purpose optimization package. To validate the proposed model, numerical experiments are conducted, and the results show that production schedule can be properly adjusted to reduce energy cost.