Peter Smolek's research while affiliated with TU Wien and other places

Publications (9)

Article
Full-text available
In the challenge of achieving environmental sustainability, industrial production plants, as large contributors to the overall energy demand of a country, are prime candidates for applying energy efficiency measures. A modelling approach using cubes is used to decompose a production facility into manageable modules. All aspects of the facility are...
Article
Full-text available
Demand Response can be seen as one effective way to harmonize demand and supply in order to achieve high self-coverage of energy consumption by means of renewable energy sources. This paper presents two different simulation-based concepts to integrate demand-response strategies into energy management systems in the customer domain of the Smart Grid...
Article
To assess cost, time investment, energy consumption and carbon emission of manufacturing on a per-piece basis, a bottom-up approach for aggregating a real-time product footprint is proposed. This method allows the evaluation of the environmental impact of a batch or even single product using monitoring or simulation data. To analyze the infrastruct...
Conference Paper
In the challenge of achieving environmental sustainability, industrial production plants, as large contributors to the overall energy demand of a country, are prime candidates for applying energy efficiency measures. A modelling approach using cubes is used to decompose a production facility into manageable modules. All aspects of the facility are...

Citations

... The building-related cubes are further explained in Building model within the BaMa digitaltwin ecosystem; however, a detailed description of all other cube models would be beyond the scope of this study. Further information is available in Raich et al. (2016), Smolek et al. (2017), and Smolek et al. (2018). ...
... Also, demand response (DR) can be implemented in such contexts [4]. A recent research implemented different concepts to integrated demand response strategies for end users in households (model predictive control of heating and cooling) and industry (optimization of automation systems) [5]. In the [6], improved load profiles comparison method for the DR Abbreviations: CEEP, Critical Excess Electricity Production; CHP, Combined Heat and Power generation; DR, Demand Response; GHG, Green House Gasses; IAM, Integrated Assessment Model; ICE, Internal Combustion Engine; LCOE, Levelized cost of energy produced; NECP, National Energy and Climate Plan; P2H, Power to Heat technology; P2G, Power to Gas technology; PHS, Pump Hydro Storage; PV, Solar Photovoltaic plants; RES, Renewable Energy Sources including sustainable biomass and hydropower; ROR, Run-of-river hydropower; V2G, Vehicle-to-grid concept for electric vehicles; VRES, Variable Renewable Energy Souces: wind, solar and run-of-river hydropower. ...
... In order to address this deficiency, this research is meant to develop a novel planning tool that increases both the energy efficiency and general performance of production systems, using a hybrid simulation-based optimization approach. The general planning concept has been published by the research team [7], so has the hybrid simulation concept [8] and the development of the optimization module [9]. The particular paper at hand focuses on the adaption of the planning method to a specific real life industrial application and on evaluating the optimization potential in an industrial use case. ...
... Many methods are studied and applied to energy saving and reduction, such as the better mix of energy retrofit measures for different geographical areas proposed by Di Pilla et al. [1] or an interactive and comprehensive platform based on an advanced metering infrastructure for exchanging information on energy consumption proposed by Podgornik et al. [2] or another aspects linked to the facility considered, classified into the building, energy system, production and logistics proposed by Smolek et al. [3]. Another aspect is related to renewable energies as proposed by Dehghan and Pfeiffer [4]. ...
... Of these 37 publications, 10 deal with continuously collected DLCI data. The manufacturing field is represented by various publications regarding personalized furniture manufacturing [27], a generic shop floor [4,28], injection molding [29], grinding [30], and ceramic tile production [31]. The relative overrepresentation of manufacturing case studies in the continuously collected DLCI data category can be attributed to the focus that this sector has received in Industry 4.0 initiatives [6]. ...
... Data of the relevant physical system, parameters outside the selected physical system that affect it, and also its interconnections to other physical systems, are collected, interpreted, and stored in the virtual representation. A detailed description of the BaMa methodology is available in Leobner et al. (2015) and Leobner (2016). BaMa cubes are divided into four classes, which include different generic cube types aiming to be able to model all the functions within the factory (Figure 3). ...
... Different studies and learning objectives for each experiment are listed out. This can be an excellent module for the conduction of virtual lab in both undergraduate and post graduate levels [17]. ...