Localized electricity and carbon allowance management for interconnected discrete manufacturing systems considering algorithmic and physical feasibility

Xiaoqing Zhong, Weifeng Zhong, Zhenjia Lin, Guoxu Zhou, Loi Lei Lai, Shengli Xie and Jinyue Yan

Applied Energy, 2024, vol. 372, issue C, No S0306261924011747

Abstract: 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 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123791

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