Stephan Hutterer

Probabilistic power flow studies represent essential challenges in nowadays power system operation and research. Here, especially the incorporation of intermittent supply plants with optimal control of dispatchable demand like electric vehicle charging power shows nondeterministic aspects. Using simulation-based optimization, such probabilistic and...

Dynamic and stochastic problem environments are often difficult to model using standard problem formulations and algorithms. One way to model and then solve them is simulation-based optimization: Simulations are integrated into the optimization process in order to evaluate the quality of solution candidates and to identify optimized system configur...

In nowadays operations research, dynamic optimisation problems are a central and challenging research topic. Especially in complex real-world systems such as electric power grids, dynamic problems occur where robust solutions need to be found that enable (near-) optimal control over time in volatile as well as uncertain power grid operation. The au...

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 ha...

Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in t...

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 beha...

General optimal power flow (OPF) is an important problem in the operation of electric power grids. Solution methods to the OPF have been studied extensively that mainly solve steady-state situations, ignoring uncertainties of state variables as well as their near-future. Thus, in a dynamic and uncertain power system, where the demand as well as the...

Taking a look at actual developments in the field of bioinformatics, computer support in different fields of medicine and biology is an increasing field of interest. Especially for recognition and classification of various kinds of diseases, researchers already identified the usage of data mining techniques as supporting tool for computer supported...

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...

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...

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...

In future smart electric grids, the control of electric vehicles' charging processes will be a central aim of demand side management. While this control enables the avoidance of possible critical peak-load values, the optimal coordination with supply from fluctuating renewables offers promising possibilities for power grid operation. Within this wo...

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 optimizati...

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 con...

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...