Smart Grid Aware Digital Manufacturing Strategy for Low Carbon Production Using Microgrids and Energy Storage

DOI

10.2991/978-94-6239-750-7_48How to use a DOI?

Keywords

Digital manufacturing; Energy-aware scheduling; Reinforcement learning; Smart microgrids; Low-carbon production; Energy storage systems; Digital twin; Sustainable manufacturing; Industrial energy management; Smart factory; Microgrids

Abstract

The need for energy mindful manufacturing frameworks that minimize carbon emissions while balancing productivity and operational reliability has gained traction, alongside the need for the adoption of sustainable industry practices. Traditional manufacturing facilities rely on fossil fuel powered grids and operate unaware of real-time energy conditions. The problems of excessive energy consumption and the impact on the environment are scales of problems that are related to the energy paradigm shifts and the evolving environment of the energy system. This paper presents the Smart Grid Digital Manufacturing Strategy (SG-DMS), which balances low carbon manufacturing with micro grids, renewables, and energy storage within a digital twin-enabled production framework. The SG-DMS employs a three-layered approach. The first layer, Smart Energy, utilizes solar and wind hybrid microgrids with battery storage for local energy generation and buffering. The second layer is Digital Twin Manufacturing. The third layer is the intelligent energy control, management, and scheduling which employs predictive optimization and reinforcement learning to adjust production to the available renewables, load demand, and carbon values. The system implements peak load reduction, adaptive scheduling, and energy conscious operation of machines using a temporal deep learning model that predicts energy production and manufacturing capacity. A new metric, the Carbon Aware Production Index (CAPI) and Energy Flexibility Score (EFS) are proposed to support decision making and measure the sustainability of a system.

Optimized simulations on the smart factory testbed show that the proposed strategy, compared to conventional rule-based scheduling, is able to reduce grid dependency by 38–52% and improve carbon emissions and energy efficiency by 35–45% and 28% respectively. The results suggest that the combination of digital manufacturing intelligence with micromericulture and Integrated Microgrids and Storage Systems (IMIS) creates an effective pathway to scalable, resilient, and ecologically sustainable industrial ecosystems The proposed Integrated Microgrids and Storage Systems (IMIS) with Digital Manufacturing Intelligence (DMI) is a pioneering contribution to the evolution of smart energy and manufacturing convergence.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ashu Nayak
AU  - Sonam Dubey
PY  - 2026
DA  - 2026/08/31
TI  - Smart Grid Aware Digital Manufacturing Strategy for Low Carbon Production Using Microgrids and Energy Storage
BT  - Proceedings of the International Conference on Advanced Design, Manufacturing, and Sustainable Energy Systems (ICADMSES 2026)
PB  - Atlantis Press
SP  - 658
EP  - 670
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6239-750-7_48
DO  - 10.2991/978-94-6239-750-7_48
ID  - Nayak2026
ER  -