Optimization of Distributed Integrated Multi-energy System Considering Industrial Process Based on Energy Hub

As a typical scenario of distributed integrated multi-energy system (DIMS), industrial park contains complex production constraints and strong associations between industrial productions and energy demands. The industrial production process (IPP) consists of controllable subtasks and strict timing constraints. Taking IPP as a control variable of optimal scheduling, it is an available approach that models the IPP as material flow into an extension energy hub (EH) to achieve the optimization of industrial park. In this paper, considering the coupling between the production process and energy demands, a model of IPP is proposed by dividing the process into different adjustable steps, including continuous subtask, discrete subtask, and storage subtask. Then, a transport model of material flow is used to describe the IPP in an industrial park DIMS. Based on the concept of EH, a universal extension EH model is proposed considering the coupling among electricity, heat, cooling, and material. Furthermore, an optimal scheduling method for industrial park DIMS is proposed to improve the energy efficiency and operation economy. Finally, a case study of a typical battery factory is shown to illustrate the proposed method. The simulation results demonstrate that such a method reduces the operation cost and accurately reflects the operation state of the industrial factory.