@misc{13678,
  abstract     = {{The previous methodology for optimizing CO2 emissions and electricity costs in industrial applications is extended by integrating dynamic load shifting with battery energy storage. Building on earlier work that employed Mixed-Integer Linear Programming (MILP) to manage a stationary battery based on real-time electricity prices and CO2 intensity signals, two industrial machines and one electric vehicle (EV) are now incorporated as additional shiftable loads. These new elements introduce further operational constraints while enhancing energy management flexibility. The framework employs an adjustable weighting factor λ to balance environmental impact and cost, and comparative analyses across three scenarios—battery-only, load-shifting-only, and combined—demonstrate nearly additive CO2 reductions alongside non-additive cost improvements, underscoring the synergistic potential for environmental benefits despite diminishing cost returns. Moreover, validation against dynamic programming confirms the MILP approach’s accuracy and computational efficiency.}},
  author       = {{Mousavi, Seyed Davood and Schulte, Thomas}},
  booktitle    = {{2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)}},
  keywords     = {{Feeds, Antennas, System-on-chip, Application specific integrated circuits, Life cycle assessment, Product lifecycle management, Radio access networks, Regional area networks, Smart devices, OWL}},
  location     = {{Paris, France }},
  publisher    = {{IEEE}},
  title        = {{{Enhanced Dynamic Optimization for CO2 Reduction and Cost Savings through Load Shifting in Smart Factories}}},
  doi          = {{10.1109/icecet63943.2025.11472530}},
  year         = {{2026}},
}

@misc{13224,
  abstract     = {{This paper presents a robust methodology for optimizing CO2 emissions and electricity costs in industrial applications, with the aim of developing a flexible and dynamic energy management strategy that balances sustainability and cost-efficiency. Addressing the growing need for sustainable and economically viable energy solutions amidst the global urgency of climate change mitigation, the proposed approach is based on dynamic energy management techniques that minimize dependence on grid electricity, which can fluctuate between energy import and export. A flexible cost function is developed to simultaneously account for CO2 emissions and electricity prices, enabling a balance between environmental impact and operational costs. The optimization framework employs Mixed-Integer Linear Programming (MILP) to derive the optimal energy management strategy, showcasing significant potential for reducing both CO2 emissions and electricity costs. Although the methodology is demonstrated in a specific industrial setting, its flexible design ensures applicability across various energy profiles and operational scenarios, making it relevant for a wide range of industrial applications.}},
  author       = {{Mousavi, Seyed Davood and Griese, Martin and Schulte, Thomas}},
  booktitle    = {{2024 International Conference on Electrical and Computer Engineering Researches (ICECER)}},
  keywords     = {{CO2 Reduction, Electricity Cost Minimization, Life Cycle Assessment, MILP, Smart-E-Factory, Dynamic Energy Management}},
  location     = {{Gaborone, Botswana }},
  publisher    = {{IEEE}},
  title        = {{{Dynamic Optimization of CO<sub>2</sub> Emissions and Electricity Costs in Smart Factories}}},
  doi          = {{10.1109/icecer62944.2024.10920418}},
  year         = {{2024}},
}

@misc{12788,
  abstract     = {{The product environmental footprint (PEF) is one of two life cycle assessment methods from the European Commission. With their published recommendation on environmental footprint methods, the European Commission provides a framework to assess the PEF for every product in a company. Since there is a high probability that the PEF will be mandatory for companies shortly, it is crucial that this recommendation guides companies and mainly technical employees through all phases of the PEF and enables them to execute a PEF study correctly. Therefore, this paper aims to analyze the process of calculating a PEF for a product critically. A PEF study is conducted on a smart luminaire with the software program OpenLCA. The use case concludes that many aspects of the PEF still need to be clarified. Especially the calculation methods behind every impact category need to be more transparent. Further, a comparison of the use case with a provided tutorial from OpenLCA is made. The comparison shows that no information is available on how to model the end-of-life and the use stages, which are mandatory in a PEF study. (c) 2023 The Authors. Published by ELSEVIER B.V.}},
  author       = {{Mordaschew, Viktoria and Tackenberg, Sven}},
  booktitle    = {{5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)}},
  editor       = {{Longo, F. and Shen, W. and Padovano, A.}},
  issn         = {{1877-0509}},
  keywords     = {{Product Environmental Footprint, Life Cycle Assessment, Sustainability, Cyber-physical Systems}},
  location     = {{Lisbon, PORTUGAL}},
  pages        = {{493--503}},
  publisher    = {{Elsevier BV}},
  title        = {{{The Product Environmental Footprint – A Critical Review}}},
  doi          = {{10.1016/j.procs.2024.01.049}},
  volume       = {{232}},
  year         = {{2024}},
}