Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Electricity market models, implemented as dynamic programming problems, have been applied widely to identify possible pathways towards a cost-optimal and low carbon electricity system. However, the joint optimization of generation and transmission remains challenging, mainly due to the fact that different characteristics and rules apply to commercial and physical exchanges of electricity in meshed networks. This paper presents a methodology that allows to optimize power generation and transmission infrastructures jointly through an iterative approach based on power transfer distribution factors (PTDFs). As PTDFs are linear representations of the physical load flow equations, they can be implemented in a linear programming environment suitable for large scale problems. The algorithm iteratively updates PTDFs when grid infrastructures are modified due to cost-optimal extension and thus yields an optimal solution with a consistent representation of physical load flows. The method is first demonstrated on a simplified three-node model where it is found to be robust and convergent. It is then applied to the European power system in order to find its cost-optimal development under the prescription of strongly decreasing CO 2 emissions until 2050. Terms of use: Documents in

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractAs an attempt to fight global warming, many countries try to reduce CO 2 emissions in the power sector by significantly increasing the proportion of renewable energies (RES-E). A highly intermeshed electricity transmission grid allows the achievement of this target cost-efficiently by enabling the usage of most favorable RES-E sites and by facilitating the integration of fluctuating RES-E infeed and regional electricity demands.However, construction of new lines is often proceeding very slowly in areas with a high population density.In this paper, we try to quantify the benefits of optimal transmission grid extensions for Europe until 2050 compared to moderate extensions when ambitious RES-E and CO 2 reduction targets are achieved. We iterate a large-scale dynamic investment and dispatch optimization model for Europe with a load-flow based transmission grid model, in order to determine the optimal deployment of electricity generation technologies and transmission grid extensions from a system integrated point of view. Main findings of our analysis include that large transmission grid extensions are needed to achieve the European targets cost-efficiently.When the electricity network is cost-optimally extended, 228,000 km are built until 2050, representing an increase of 76% compared to today. Further findings include substantial increases of average system costs for electricity until 2050, even if RES-E are deployed efficiently throughout Europe, the grid is extended optimally, and if significant cost reductions of RES-E are assumed.

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For the past couple of years, Plug-in Hybrid Electric Vehicles (PHEVs) demonstrated their ability to significantly reduce petroleum consumptions. However, more than any other vehicle powertrain, their benefits are dependent on the driving cycles from both an aggressiveness and distance point of view. In this paper, two powertrain configurations will be defined. A power split configuration will be used for low battery energy and a series configuration for high battery energy. For each vehicle we will evaluate several control strategies, including electrical dominant and blended, on real world drive cycles. A conventional vehicle will be defined to use as a baseline. The trade-off between fuel displacement and cost will be evaluated for each option.