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The future of industrial manufacturing and production will increasingly manifest in the form of cyber-physical production systems. Here, Digital Shadows will act as mediators between the physical and digital world to model and operationalize the interactions and relationships between different entities in production systems. Until now, the associated concepts have been primarily pursued and implemented from a technocentric perspective, in which human actors play a subordinate role, if they are considered at all. This paper outlines an anthropocentric approach that explicitly considers the characteristics, behavior, and traits and states of human actors in socio-technical production systems. For this purpose, we discuss the potentials and the expected challenges and threats of creating and using Human Digital Shadows in production.
Non-nuclear and non-fossil energy resources and their possibilities for future power generation
(1975)
It must be stressed that the assessment of the exploitation possibilities of the energy resources discussed in this paper requires further studies. With this proviso, the situation can be provisionally summarised as follows: The total potential of known geothermal steam sources is only 64 GW. Geothermal energy could therefore only make a significant contribution to covering the worldwide power needs if we succeed in exploiting dry geothermal reservoirs. Exploitation of tidal energy is limited to a few geographically favourable locations. The power generation potential at these locations is only about 64 GW. An important drawback of tidal power is discontinuous power generation. Large scale exploitation of wind, wave and glacier energy, and of ocean heat, requires solution of a number of technological problems. The environmental effects of exploitation of these energy resources are to some extent of a qualitatively different nature from those of operation of fossil-fuel-fired and of nuclear power plants. The scanty knowledge in this area often results in these effects being underestimated. In any case, however, it would be deliberately misleading to postulate that any form of power generation is possible without some detrimental effects on the environment. It may be stated in conclusion that, owing to their small potential or to the as yet insufficiently advanced technological development, none of the energy resources discussed in this paper can make a significant contribution to the solution of middle-term energy supply problems, i.e., to a rapid replacement of mineral oil and natural gas.
This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.