Niklas Rotering

Optimal Charge Control of Plug-In Hybrid Electric Vehicles in Deregulated Electricity Markets

Plug-in hybrid electric vehicles are a midterm solution to reduce the transportation sectors dependency on oil. However, if implemented in a large scale without control, peak load increases significantly and the grid may be overloaded. Two algorithms to address this problem are proposed and analyzed. Both are based on a forecast of future electricity prices and use dynamic programming to find the economically optimal solution for the vehicle owner. The first optimizes the charging time and energy flows. It reduces daily electricity cost substantially without increasing battery degradation. The latter also takes into account vehicle to grid support as a means of generating additional profits by participating in ancillary service markets. Constraints caused by vehicle utilization as well as technical limitations are taken into account. An analysis, based on data of the California independent system operator, indicates that smart charge timing reduces daily electricity costs for driving from

A Decision-Making Framework and Simulator for Sustainable Electric Energy Systems

0.43 to

Medium-voltage network planning with optimized power factor control of distributed generators

0.2. Provision of regulating power substantially improves plug-in hybrid electric vehicle economics and the daily profits amount to

Demand for energy storage and grid developement in Germany with increased renewable generation according to the federal government's energy concept

1.71, including the cost of driving.

Energiespeicher für die Energiewende : Speicherungsbedarf und Auswirkungen auf das Übertragungsnetz für Szenarien bis 2050 ; Gesamttext

In this paper, we propose a new framework for the organization of the electric power industry, based on extensive use of information technology (IT) and on interactive decision making, where consumers and distributed producers join the traditional actors, utilities in particular, in making decisions. While many ideas considered in this paper have been put forward in recent years, such as the need to manage intermittency of renewable resources by means of proactive forecasting, and coordination with responsive demand and storage, we introduce a possible systematic IT-enabled mechanism necessary for the actual implementation of these technologies. We point out that in order to achieve a long-term sustainable energy utilization, it is essential to provide on-line information to internalize the value of just-in-time, just-in-place, and just-in-context distributed adaptation across the entire supply chain, ranging from the smallest consumers and energy providers, through their aggregators and system coordinators. We illustrate using our model-based novel simulator, how a carefully designed multidirectional and multitemporal information exchange could enable sustainable decision making while accounting for unique needs and capabilities of various resources and users. At the same time, information incentivizes the resources and users to contribute to system-wide sustainability objectives at value. We illustrate the dependence of such decisions-driven industry evolution on the industry rules (choice of performance objectives), as well as on the operating and planning practices for implementing the industry rules (temporal and spatial factors). Our model-based simulator could be used as a means of designing novel regulation defining rules, rights, and responsibilities regarding the type and rate of information to be exchanged in support of sustainable industry evolution.

Dezentrale Energiespeicher : Einsatzmöglichkeiten, Bedarf und Wirtschaftlichkeit

Distributed generation causes new challenges in medium voltage networks. Especially voltage stability is becoming an issue. Conventional planning measures, like network expansion, can be used to address this challenge, but they should be planned with great care due to their high costs. Power factor control of distributed generators is an alternative to such measures. Therefore it should also be considered in long term distribution network planning. It is the purpose of this paper to present a new approach for long term medium-voltage network optimization that integrates near optimal power factor control. The structural optimization is heuristic and based on a Delaunay triangulation in combination with an ant colony algorithm. Power factor control is predicated on dynamic programming. It is shown how near optimal results can easily be realized under German law with present technologies. A case study illustrates the impacts and advantages of an integrated planning approach. The integrated optimization resulted in network costs that are 2.5 % lower than the costs of the best topology found by conventional planning.

Dezentrale Energiespeicher: Studie zu Stromspeichern in der Nieder- und Mittelspannungsebene

According to the German federal governments energy concept renewable energies are to supply 80 % of the gross electricity consumption till 2050. The study “Energiespeicher für die Energiewende”, provided by the Association for Electrical, Electronic and Information Technology (VDE), is focused on the question which storage demand is needed to achieve this goal and what effect the storage plants and their operation will have on the German transmission network.