Green scheduling of distributed two-stage reentrant hybrid flow shop considering distributed energy resources and energy storage system

Abstract

In order to build a green manufacturing model and realize energy conservation and emission reduction, we establish a distributed two-stage reentrant hybrid flow shop bi-level scheduling model, which takes makespan, total carbon emissions and total energy consumption costs as the optimization objectives. There are multiple heterogeneous factories, and in each factory the manufacturing stage and the inspection and repair stage are considered simultaneously. The upper model determines the optimal scheduling scheme of jobs to minimize makespan. On this basis, the lower model obtains the power supply allocation scheme of distributed energy resources (DERs), energy storage system (ESS) and main grid to minimize total carbon emissions and total energy consumption costs. An improved hybrid salp swarm (SSA) and NSGA-III algorithm is proposed to solve this problem. Through a large number of experiments, it is proved that the use of DERs and ESS can effectively reduce carbon emissions and energy costs under the TOU electricity price. Meanwhile, it is proved that the proposed algorithm has significant advantages for solving such problem.