Tillmann Mühlpfordt

• MSc
• scientific employee at Karlsruhe Institute of Technology

The increase in renewable energy sources (RESs), like wind or solar power, results in growinguncertainty also in transmission grids. This affects grid stability through fluctuating energy supplyand an increased probability of overloaded lines. One key strategy to cope with this uncertainty isthe use of distributed energy storage systems (ESSs). In...

The increase in renewable energy sources (RESs), like wind or solar power, results in growing uncertainty also in transmission grids. This affects grid stability through fluctuating energy supply and an increased probability of overloaded lines. One key strategy to cope with this uncertainty is the use of distributed energy storage systems (ESSs)....

The increase in renewable energy sources (RESs), like wind or solar power, results in growing uncertainty also in transmission grids. This affects grid stability through fluctuating energy supply and an increased probability of overloaded lines. One key strategy to cope with this uncertainty is the use of distributed energy storage systems (ESSs)....

The uncertainty associated with renewable energies creates challenges in the operation of distribution grids. One way for Distribution System Operators to deal with this is the computation of probabilistic forecasts of the full state of the grid. Recently, probabilistic forecasts have seen increased interest for quantifying the uncertainty of renew...

Due to their large power draws and increasing adoption rates, electric vehicles (EVs) will become a significant challenge for electric distribution grids. However, with proper charging control strategies, the challenge can be mitigated without the need for expensive grid reinforcements. This article presents and analyzes new distributed charging co...

Solving the power flow problem in a distributed fashion empowers different grid operators to compute the overall grid state without having to share grid models—this is a practical problem to which industry does not have off-the-shelf answers. We propose two physically consistent problem formulations (a feasibility and a least-squares formulation) a...

In this contribution, we present a gas-power benchmark problem tailored to simulation and optimization of coupled electrical grids and gas networks in a time-varying setting. Based on realistic data sets from the IEEE database and the GasLib suite, we describe the full set up of the underlying equations and motivate the choice of parameters. The il...

In traditional power system operations real-time control policies are based on simple control policies such as automatic generation control and/or local voltage control. Although these simple policies have worked well in the past, the increased variability associated with higher penetrations of renewable energy strengthens the case for more general...

A bstract The reproduction number is an indicator of the evolution of an epidemic. Consequently, accurate estimators for this number are essential for decision making in politics. Many estimators use filtered data as input to compensate for fluctuations of reported cases. However, for daily-based estimations, this filtering leads to delays. Some ap...

Solving the power flow problem in a distributed fashion empowers different grid operators to compute the overall grid state without having to share grid models-this is a practical problem to which industry does not have off-the-shelf answers. In cooperation with a German transmission system operator we propose two physically consistent problem form...

Due to their large power draws and increasing adoption rates, electric vehicles (EVs) will become a significant challenge for electric distribution grids. However, with proper charging control strategies, the challenge can be mitigated without the need for expensive grid reinforcements. This manuscript presents and analyzes new distributed charging...

Zusammenfassung: Der Beitrag analysiert die Auswirkungen von wöchent-lichen Periodizitäten und zeitlichen Korrekturen auf die Schätzung einer zeitabhängigen Reproduktionszahl R bei Infektionskrankheiten. Zur Reduktion dieser Schwankungen wird eine einfache Methode vorgeschlagen, die auf einem akausalen Filter der Filterlänge 7 und optionalen Schätz...

Polynomial chaos expansion (PCE) is an increasingly popular technique for uncertainty propagation and quantification in systems and control. Based on the theory of Hilbert spaces and orthogonal polynomials, PCE allows for a unifying mathematical framework to study systems under arbitrary uncertainties of finite variance; we introduce this problem a...

In this contribution, we aim at presenting a gas-to-power benchmark problem that can be used for the simulation of electricity and gas networks in a time-dependent environment. Based on realistic data from the IEEE database and the GasLib suite, we describe the full set up of the underlying equations and motivate the choice of parameters. The simul...

Polynomial chaos expansion (pce) is an increasingly popular technique for uncertainty propagation and quantification in systems and control. Based on the theory of Hilbert spaces and orthogonal polynomials, PCE allows for a unifying mathematical framework to study systems under arbitrary uncertainties of finite variance; we introduce this problem a...

We fix errata encountered in letter T. Mühlpfordt et al. “Comments on Truncation Errors for Polynomial Chaos Expansions”. In: IEEE Control Systems Letters 2.1 (2018), pp. 169–174.

The need to de‐carbonize the current energy infrastructure, and the increasing integration of renewables pose a number of difficult control and optimization problems. Among those, the optimal power flow (OPF) problem—i.e., the task to minimize power system operation costs while maintaining technical and network limitations—is key for operational pl...

As the share of renewables in the grid increases, the operation of power systems becomes more challenging. The present paper proposes a method to formulate and solve chance-constrained optimal power flow while explicitly considering the full nonlinear AC power flow equations and stochastic uncertainties. We use polynomial chaos expansion to model t...

As the share of renewables in the grid increases, the operation of power systems becomes more challenging. The present paper proposes a method to formulate and solve chance-constrained optimal power flow while explicitly considering the full nonlinear AC power flow equations and stochastic uncertainties. We use polynomial chaos expansion to model t...

The optimal power flow (OPF) problem—i.e., the task to minimize power system operation costs while maintaining technical and network limitations—is key for the operational planning of power systems. The influx of inherently volatile renewable energy sources calls for methods that allow to consider stochasticity directly in the OPF problem. Modeling...

The Energiewende is a paradigm change that can be witnessed at latest since the political decision to step out of nuclear energy. Moreover, despite common roots in Electrical Engineering, the control community and the power systems community face a lack of common vocabulary. In this context, this paper aims at providing a systems-and-control specif...

The Energiewende is a paradigm change that can be witnessed at latest since the political decision to step out of nuclear energy. Moreover, despite common roots in Electrical Engineering, the control community and the power systems community face a lack of common vocabulary. In this context, this paper aims at providing a systems-and-control specif...

The operation of power systems has become more challenging due to feed-in of volatile renewable energy sources. Chance-constrained optimal power flow (ccOPF) is one possibility to explicitly consider volatility via probabilistic uncertainties resulting in mean-optimal feedback policies. These policies are computed before knowledge of the realizatio...

Deregulated energy markets, demand forecasting, and the continuously increasing share of renewable energy sources call---among others---for a structured consideration of uncertainties in optimal power flow problems. The main challenge is to guarantee power balance while maintaining economic and secure operation. In the presence of Gaussian uncertai...

Deregulated energy markets, demand forecasting, and the continuously increasing share of renewable energy sources call---among others---for a structured consideration of uncertainties in optimal power flow problems. The main challenge is to guarantee power balance while maintaining economic and secure operation. In the presence of Gaussian uncertai...

Distributed optimization methods for Optimal Power Flow (OPF) problems are of importance in reducing coordination complexity and ensuring economic grid operation. Renewable feed-ins and demands are intrinsically uncertain and often follow non-Gaussian distributions. The present paper combines uncertainty propagation via Polynomial Chaos Expansion (...

The present paper discusses the application of the recently proposed Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) method to non-convex AC Optimal Power Flow Problems (OPF) in a distributed fashion. In contrast to the often used Alternating Direction of Multipliers Method (ADMM), ALADIN guarantees locally quadratic convergence...

The present paper discusses the application of the recently proposed Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) method to non-convex AC Optimal Power Flow Problems (OPF) in a distributed fashion. In contrast to the often used Alternating Direction of Multipliers Method (ADMM), ALADIN guarantees locally quadratic convergence...

Polynomial chaos expansion methods allow to approximate the behavior of uncertain stochastic systems by deterministic dynamics. These methods are used in a wide range of applications, spanning from simulation of uncertain systems to estimation and control. For practical purposes the exploited spectral series expansion is typically truncated to allo...

Methods based on polynomial chaos expansion allow to approximate the behavior of systems with uncertain parameters by deterministic dynamics. These methods are used in a wide range of applications, spanning from simulation of uncertain systems to estimation and control. For practical purposes the exploited spectral series expansion is typically tru...

This paper investigates the distributed solution of non-convex AC power flow optimization problems arising in electrical grids. Specifically, we consider the application of a recently proposed Augmented Lagrangian Based Alternating Direct Inexact Newton (ALADIN) scheme to AC optimal power flow problems. Using standard reformulations, we show how AL...

The uncertain nature of electric energy production from distributed generation based on renewable resources has to be considered when managing and operating distribution grids. In several cases, this uncertainty can be described using non-Gaussian random variables, requiring appropriate probabilistic load flow techniques. The present paper proposes...

The present contribution demonstrates the applicability of polynomial chaos expansion to stochastic (optimal) AC power flow problems that arise in the operation of power grids. For rectangular power flow, polynomial chaos expansion together with Galerkin projection yields a deterministic refor-mulation of the stochastic power flow problem that is s...

In many control problems, not all states can be measured and the system is subject to parametric uncertainties, measurement noise, and hard input constraints. To tackle such problems for linear systems, we propose to combine a recursive parameter and state estimator (based on Bayes’ theorem) with a stochastic model predictive control approach. Prob...

In this paper, an MPC scheme for a missile pitch axis autopilot is proposed. The scheme uses a nonlinear prediction model to give it an ability to push the controlled missile very close to its operating limits, and is stabilised through the use of an ellipsoidal terminal constraint. Tracking performance and computational load of the scheme are comp...