@misc{13675,
  abstract     = {{This paper extends a previously developed biobjective Mixed-Integer Linear Programming (MILP) methodology for reducing electricity costs and CO2 emissions in Smart-E-Factory applications. While the earlier approach assumed fixed photovoltaic (PV) and battery capacities, we now propose a cascaded optimization framework to determine the optimal sizing (power rating and orientation of the PV system, battery capacity) while simultaneously optimizing battery dispatch. The cost function combines operational costs with amortized investment costs of both PV and battery systems, embedded in a dynamic scheduling optimization that addresses real-time electricity price and CO2 signals. Numerical results indicate that intermediate capacities and balanced east/west orientation maximize cost-effectiveness and emission reductions. This study underscores the value of coupling parametric design and dispatch optimization to achieve scalable, sustainable solutions for industrial energy systems.}},
  author       = {{Mousavi, Seyed Davood and Schulte, Thomas}},
  booktitle    = {{	 6th International Conference on Electrical, Communication and Computer Engineering (ICECCE 2025) : 27-28 August 2025, Istanbul, Türkiye}},
  isbn         = {{979-8-3315-4915-2 }},
  keywords     = {{Photovoltaic systems, Cost, Electricity, Tariffs, Stochastic processes, Real-time systems, Robustness, Batteries, Planning, Mixed integer linear programming}},
  location     = {{Istanbul, Turkiye }},
  publisher    = {{IEEE}},
  title        = {{{Cascaded Optimization of PV and Battery Sizing Under Dynamic Cost and CO Signals}}},
  doi          = {{10.1109/icecce67514.2025.11257982}},
  year         = {{2025}},
}

@misc{12391,
  abstract     = {{Daylight saving time (DST) affects millions of people in various everyday situations and is a common topic of debate in legislative parliaments around the world. This paper presents a literature review on the effects of the clock change and DST on electricity usage, health, crime rates, road safety, and economic aspects. This addresses a gap in current literature reviews, as there is a lack of linked analyses considering these research fields. We show that there are partial positive effects on crime rates and road safety generally that result from the delay in ambient light availability. This contrasts with the clearly negative effects on health and the economic aspects, which are mainly driven by the disturbed circadian rhythm and the resulting sleep problems. Furthermore, we find that the initial idea of DST to save electricity will probably no longer apply and may even lead to increased usage. This literature review provides a basis for future research and promotes interdisciplinary research by summarizing current findings in a cross-disciplinary manner and identifying research gaps and opportunities. Furthermore, the findings may guide policy-making discussions and decisions. }},
  author       = {{Neumann, Philipp and von Blanckenburg, Korbinian}},
  booktitle    = {{Time & Society}},
  issn         = {{1461-7463}},
  keywords     = {{circadian rhythm, clock chang, crime rates, daylight saving time, economic aspects, electricity usage, health, road safety, sleep deprivation}},
  publisher    = {{SAGE Publications}},
  title        = {{{What Time Will It Be? A Comprehensive Literature Review on Daylight Saving Time}}},
  doi          = {{10.1177/0961463x241310562}},
  year         = {{2025}},
}

@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}},
}