Stephan Hutterer

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The implementation of intelligent power grids, in form of smart grids, introduces new challenges to the optimal dispatch of power. Thus, optimization problems need to be solved that become more and more complex in terms of multiple objectives and an increasing number of control parameters. In this paper, a simulation based optimization approach is(More)
While an increasing share of intermittent and non- dispatchable renewable energy plants cause probabilistic behavior at the power grids' supply side, the expected penetration of electric mobility at the demand side offers the opportunity of controllable load. Their optimal coordination is one major concern for future smart grids. Therefore, a multi-agent(More)
—Probabilistic power flow studies form essential investigations for both operation and analysis of electric power grids under stochastic conditions. Especially the increasing penetration of intermittent and non-dispatchable power plants like wind power plants cause probabilistic behaviour at the supply side. At the same time, the expected penetration of(More)
The present paper deals with the application of atomic force microscopy (AFM) as a tool for morphological characterization of histological brain tumor samples. Data mining techniques will be applied for automatic identification of brain tumor tissues based on AFM images by means of classifying grade II and IV tumors. The rapid advancement of AFM in recent(More)
Actual developments in power grid research, analysis, and operation are dominated clearly by the strong convergence of electrical engineering with information technology. Hence, new control abilities in power grids come up that revolutionize traditional optimization issues, requiring novel solution methods. At the same time, heuristic algorithms have(More)
Optimal integration of electric vehicles (EVs) into modern power grids plays a promising role in future operation of smart power systems. The role of aggregators as e-mobility service providers is getting investigated steadily in recent times and forms a fruitful ground for control of EV charging. Within this paper, a policy-based control approach is shown(More)
Electric power grid operation being an ever challenging scientific field is faced with a high variety of optimization problems. Since the future vision of so called smart grids causes higher complexity and new requirements to these problems, sophisticated investigation in suitable optimization algorithms is essential. Here, metaheuristic optimization(More)
Since the electrification of individual traffic may cause a critical load to power grids, methods have to be investigated that are capable of handling its highly stochastic behaviour. From a power grid's point of view, forecasting applications are needed for computing optimal power generation schedules that satisfy end-user's energy needs while considering(More)
The optimal power flow (OPF) is one of the central optimization problems in power grid engineering, building an essential tool for numerous control as well as planning issues. Methods for solving the OPF that mainly treat steady-state situations have been studied extensively, ignoring uncertainties of system variables as well as their volatile behavior.(More)