| Title |
Supply-cost Optimization Scheduling System for Improving Unutilized Energy Supply Efficiency in Plant Factory |
| Authors |
노태헌(Tae Heon No) ; 이민구(Min Goo Lee) ; 박용국(Yong Kuk Park) ; 정경권(Kyung Kwon Jung) |
| DOI |
https://doi.org/10.5573/ieie.2026.63.1.113 |
| Keywords |
Plant factory; Unutilized energy; Supply-cost optimization; Multiple objective genetic algorithm |
| Abstract |
A plant factory ensures stable production but faces excessive energy consumption and cost challenges from operating various control facilities. This paper proposes a supply-cost optimization scheduling system based on a Multi-Objective Genetic Algorithm (MW-SCH) that applies three improved strategies to achieve simultaneous optimization and convergence stability. The proposed system consists of 'Reverse supply-price based initialization' to generate an initial population focused on low-cost time slots, 'Creep mutation in crossover' to maintain diversity through stable local search, and 'Multi-objective weighted sum evaluation' that comprehensively assesses cost reduction, low-price supply focus, and demand matching. In comparative experiments using 21-day supply-demand data, the proposed system (MW-SCH) demonstrated up to a 61.2% improvement in Supply-Cost Efficiency (SCE) and a 97.14% reduction in the Coefficient of Variation (CV) compared to the conventional system (SO-SCH). These results verify that the proposed method can effectively and stably achieve simultaneous optimization for the conflicting supply-cost problem in plant factory unutilized energy scheduling. |