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<p>Sustainable energy technologies and efficient energy usage are important drivers for reducing greenhouse gas emissions. The manufacturing industry, with its high energy consumption, is particularly important. Integrated energy-oriented production planning becomes essential with the adoption of on-site renewable energy technologies such as photovoltaics, wind power, hydropower, and energy storage systems. However, energy-oriented planning approaches, particularly in terms of lot-sizing, are limited. Hence, we present a novel energy-oriented dynamic lot-sizing model for multiple products in a capacity-restricted production system. Decentralized renewable energy sources supply energy, which can be stored temporarily in an energy storage system. Connections to the national power grid and energy trading are included, assuming that power generation and energy prices are known. The model aims to minimize inventory, setup, and energy costs. Numerical results highlight the superiority of our model in terms of solvability over a model formulation based on the PLSP presented by Liao and Gicquel (<CitationRef CitationID="CR32">2024</CitationRef>). Furthermore, we explore strategies to improve the lower and upper bounds of the monolithic model. The proposed hybrid matheuristic, which combines a Fix-and-Optimize heuristic with local branching, achieves high solution quality. Comparisons with traditional (consecutive) planning approaches underscore the benefits of energy-oriented lot-sizing, including better utilization of renewable energy and cost reductions of up to 19%. These findings demonstrate the potential for significant economic and environmental benefits through integrated energy-oriented production planning.</p>

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Energy-efficient lot-sizing in grid-connected production with on-site renewables and limited energy storage

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月4日

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  • Stephan Köppel,
  • Florian Sahling

摘要

Sustainable energy technologies and efficient energy usage are important drivers for reducing greenhouse gas emissions. The manufacturing industry, with its high energy consumption, is particularly important. Integrated energy-oriented production planning becomes essential with the adoption of on-site renewable energy technologies such as photovoltaics, wind power, hydropower, and energy storage systems. However, energy-oriented planning approaches, particularly in terms of lot-sizing, are limited. Hence, we present a novel energy-oriented dynamic lot-sizing model for multiple products in a capacity-restricted production system. Decentralized renewable energy sources supply energy, which can be stored temporarily in an energy storage system. Connections to the national power grid and energy trading are included, assuming that power generation and energy prices are known. The model aims to minimize inventory, setup, and energy costs. Numerical results highlight the superiority of our model in terms of solvability over a model formulation based on the PLSP presented by Liao and Gicquel (2024). Furthermore, we explore strategies to improve the lower and upper bounds of the monolithic model. The proposed hybrid matheuristic, which combines a Fix-and-Optimize heuristic with local branching, achieves high solution quality. Comparisons with traditional (consecutive) planning approaches underscore the benefits of energy-oriented lot-sizing, including better utilization of renewable energy and cost reductions of up to 19%. These findings demonstrate the potential for significant economic and environmental benefits through integrated energy-oriented production planning.