【Applied Energy 最新原创论文】考虑算法和物理可行性的互联离散制造系统间本地电能和碳配额管理

•Enabling electricity and carbon allowance sharing among manufacturing systems.

•A local electricity and carbon allowance sharing problem is formulated.

•An alternating optimization procedure-based distributed method is proposed.

•A convex-concave procedure-based feasibility recovery procedure is introduced.

•Guaranteeing algorithmic and physical feasibility when solving the problem.

离散制造系统的运行导致显著的能源消耗和碳排放。然而，目前研究中对这些系统的能源消耗和碳排放的减少尚未充分探索。

Discrete manufacturing systems (MSs) are prevalent across various sectors such as electronic production, food processing, and apparel manufacturing. However, their operation raises critical concerns regarding significant energy consumption and carbon emissions. Implementing local electricity and carbon allowance sharing among MSs presents a potential solution to these issues, which is explored in this paper. The main contribution of this paper lies in achieving distributed electricity and carbon allowance sharing among MSs while addressing challenges related to algorithmic and physical feasibility. Firstly, a local electricity and carbon allowance sharing problem for MSs is formulated, which involves numerous binary decision variables due to the operation of discrete manufacturing facilities and energy storage, rendering the problem challenging to solve in a distributed manner. To tackle this challenge, we propose an alternating optimization procedure (AOP)-based distributed method to solve the problem while ensuring algorithmic feasibility. Secondly, the second-order cone relaxation program (SOCP)-based power flow model is identified cannot guarantee the exactness of the distribution system model when conducting local electricity sharing. We tackle this challenge by employing a convex-concave procedure (CCP)-based feasibility recovery procedure (FRP) to recover the exactness of the SOCP relaxation, thereby ensuring physical feasibility. The numerical results demonstrate that conducting local electricity and carbon allowance sharing can effectively reduce energy costs and carbon emissions for MSs. Moreover, compared with the alternating direction method of multipliers (ADMM), the proposed distributed method can guarantee both algorithmic and physical feasibility when solving the problem.

Keywords

Manufacturing systems;

Local resource sharing;

Alternating optimization procedure;

Convex-concave procedure;

Feasibility guarantees;

Fig. 1. The schematic model of interconnected discrete MSs.

Fig. 6. The electricity sharing results among MSs.

Fig. 8. Solutions of operation costs for MSs under different solution methods.

Fig. 9. Comparative results under different operation mechanisms (LS: local sharing).

Fig. 11. The reduction processes of the sum of SOCP relaxation gaps for the distribution system during the CCP.

       本研究由广东工业大学谢胜利教授团队和香港理工大学严晋跃教授团队共同完成。

通讯作者简介：

       谢胜利，广东工业大学教授，博士生导师，国家杰出青年科学基金获得者，IEEE Follow，国家自然科学二等奖第一完成人，何梁何利基金科学与技术进步奖获得者，教育部创新团队学科带头人，粤港澳大湾区人工智能与自动化学会会长。

第一作者简介：

     钟晓青，广东工业大学助理研究员，博士后，香港理工大学严晋跃教授团队访问学者，以第一作者发表学术论文7篇，其中中科院SCI一区论文5篇，主持项目包括：国家自然科学基金青年基金、中国博士后科学基金面上资助、广东省青年优秀人才国际培养计划博士后项目。

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