The use of renewable energies strengthens decarbonization strategies. To integrate volatile renewable sources, energy systems require grid expansion, storage capabilities, or flexible consumption. This study focuses on industries that adapt production to real-time energy markets, offering flexible consumption to the grid. Flexible production considers not only traditional goals like minimizing production time, but also minimizing energy costs and emissions, thereby enhancing the sustainability of businesses. However, existing research focuses on single goals, neglects the combination of makespan, energy costs, and emissions, or assumes constant or periodic tariffs instead of a dynamic energy market. We present a novel memetic NSGA-III to minimize makespan, energy cost, and emissions, integrating real energy market data, and allowing manufacturers to adapt energy consumption to current grid conditions. Evaluating it with benchmark instances from literature and real energy market data, we explore the trade-offs between objectives, showcasing potential savings in energy costs and emissions on estimated Pareto fronts.

翻译：可再生能源的使用强化了脱碳战略。为整合波动性可再生能源，能源系统需要电网扩容、储能能力或柔性消费。本研究聚焦于通过调整生产以适应实时能源市场的工业领域，为电网提供柔性消费。柔性生产不仅考虑最小化生产时间等传统目标，还致力于最小化能源成本与排放，从而提升企业可持续性。然而，现有研究或聚焦单一目标，或忽视完工时间、能源成本与排放的多目标组合，抑或采用固定或周期性电价假设而非动态能源市场。本文提出一种新颖的模因NSGA-III算法，以最小化完工时间、能源成本与排放为目标，整合真实能源市场数据，使制造商能够根据当前电网状况调整能耗。通过文献基准案例与真实能源市场数据评估算法，我们在估计的帕累托前沿上探索多目标间的权衡关系，展示了能源成本与排放的潜在节约空间。