Adrian Bürger

Path to Zero GmbH

District heating networks with decentralized heat production are ideally suited to include a high share of renewable energy sources for heat production in urban areas with limited space. A new concept is a prosumer-based district heating network in which some or even all buildings are equipped with decentralized building-level heat storages and hea...

For the fast approximate solution of Mixed-Integer Non-Linear Programs (MINLPs) arising in the context of Mixed-Integer Optimal Control Problems (MIOCPs) a decomposition algorithm exists that solves a sequence of three comparatively less hard subproblems to determine an approximate MINLP solution. In this work, we propose a problem formulation for...

Die fluktuierende Verfügbarkeit regenerativer Energiequellen stellt eine Herausforderung bei der Planung und Auslegung regenerativer Gebäudeenergiesysteme dar. Die in einem System benötigten Speicherkapazitäten hängen dabei sowohl von der eingesetzten Regelungsstrategie als auch von den temperaturabhängigen Wirkungsgraden der Anlagenkomponenten ab....

Drawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this ori...

A coordinated operation of decentralised micro-scale hybrid energy systems within a locally managed network such as a district or neighbourhood will play a significant role in the sector-coupled energy grid of the future. A quantitative analysis of the effects of the primary energy factors, energy conversion efficiencies, load profiles, and control...

This work presents the results of experimental operation of a solar‐driven climate system using mixed‐integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with...

Multi-modal distributed energy system planning is applied in the context of smart grids, industrial energy supply, and in the building energy sector. In real-world applications, these systems are commonly characterized by existing system structures of different age where monitoring and investment are conducted in a closed-loop, with the iterative p...

Due to the increasing share of fluctuating renewable energy resources in the energy supply, the supply-demand balance needs to be increasingly supported by prosumers, who are able to adapt their energy demand and production depending on the current supply. Since small and medium-sized companies are expected to yield the potential for providing a si...

The ongoing transition from energy supply systems mainly based on fossil fuels towards supply systems based on renewable sources yields great potential for reduction of green house gas emissions. This transition can be supported by advanced control strategies such as Model Predictive Control (MPC), which can directly incorporate forecasts for fluct...

Application of Model Predictive Control (MPC) for nonlinear switched systems often leads via discretization to Mixed-Integer Non-Linear Programs (MINLPs), which in a real-time setting can be solved approximately using a dedicated decomposition approach. One stage within this approach is the solution of a so-called Combinatorial Integral Approximati...

Optimisation based economic despatch of real-world complex energy systems demands reduced order and continuously differentiable component models that can represent their part-load behaviour and dynamic responses. A literature study of existing modelling methods and the necessary characteristics the models should meet for their successful applicatio...

This work presents a whole-year simulation study on nonlinear mixed-integer Model Predictive Control (MPC) for a complex thermal energy supply system which consists of a heat pump, stratified water storages, free cooling facilities, and a large underground thermal storage. For solution of the arising Mixed-Integer Non-Linear Programs (MINLPs) we ap...

Within this work, we present a warm-started algorithm for Model Predictive Control (MPC) of switched nonlinear systems under combinatorial constraints based on Combinatorial Integral Approximation (CIA). To facilitate high-speed solutions, we introduce a preprocessing step for complexity reduction of CIA problems, and include this approach within a...

This work presents a whole-year simulation study on nonlinear mixed-integer Model Predictive Control (MPC) for a complex thermal energy supply system which consists of a heat pump, stratified water storages, free cooling facilities, and a large underground thermal storage. For solution of the arising Mixed-Integer Non-Linear Programs (MINLPs) we ap...

With the need for optimisation based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear characteristics of the components, but also certain unknown process dynamics like their internal control logic. We present in this paper an extensive literature study of existin...

This paper presents an Optimal Control Problem (OCP) tailored to assess the system performance of a rigid wing Airborne Wind Energy (AWE) pumping system prior to real flight tests. The proposed method is validated against experimental data obtained using a small prototype designed by the Dutch company Ampyx Power B.V. Within such analysis, it is sh...

Airborne wind energy (AWE) refers to a novel technology capable of harvesting energy from wind by flying crosswind patterns with tethered autonomous aircraft. Successful design of flight controllers for AWE systems relies on the availability of accurate mathematical models. Due to an expected nonconventional structure of the airborne component, the...

This work presents an algorithm for solution of Mixed-Integer Optimal Control Problems (MIOCPs) for Solar Thermal Climate Systems (STCSs) with MPC-capable runtime. We implement the so-called Combinatorial Integral Approximation (CIA) algorithm for a model of an STCS of a building that incorporates an adsorption cooling machine and apply the algorit...

Airborne Wind Energy (AWE) refers to systems capable of harvesting energy from wind by flying crosswind patterns with a tethered aircraft. Accurate models are crucial for tuning and validation of flight controllers. Due to the non-conventional structure of the airborne component, an intensive flight test campaign must be set where maneuvers are per...

The ability to catalytically reduce NOx efficiently with ammonia (NH3) has made the selective catalytic reduction (SCR) technology indispensable in diesel after-treatment systems. Ammonia is dosed periodically in the form of urea which decomposes to ammonia and reacts with NOx. During the application of real-world driving cycles, owing to fast tran...

Airborne Wind Energy (AWE) refers to a novel technology capable of harvesting energy from wind by flying crosswind patterns with tethered autonomous aircraft. Successful design of flight controllers for AWE systems rely on the availability of accurate mathematical models. Due to the non-conventional structure of the airborne component, the system i...

Accurate mathematical models of aerodynamic properties play an important role in the aerospace field. In some cases, system parameters of an aircraft can be estimated reliably only via flight tests. In order to obtain meaningful experimental data, the aircraft dynamics need to be excited via suitable maneuvers. In this paper, optimal maneuvers are...

Accurate mathematical models of aerodynamic properties play an important role in the aerospace field. In some cases, system parameters of an aircraft can be estimated reliably only via flight tests. In order to obtain meaningful experimental data, the aircraft dynamics need to be excited via suitable maneuvers. In this paper, optimal maneuvers are...

Realizing Internet of Things (IoT) is still a huge challenge for Small and Medium-sized Enterprises (SMEs) caused by heavy upfront capital investments and inadequate infrastructure. An opportunity to counteract the concern is provided in this paper by introducing an extensible and lightweight IoT analytics platform. Therefore, we present an archite...

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as fo...

Within this paper, a Mixed-Integer Linear Programming formulation for price-based demand response is proposed. Through modeling of multiple machines, storages, and production sorts, the formulation can be used not only for optimizing the electricity purchase resulting in electricity cost savings but also for production planning problems. As a case...

Optimization problems arising in Optimum Experimental Design (OED) applications require repeated covariance matrix evaluations of the underlying Parameter Estimation (PE) problems. The complexity of this task grows quickly with the problem dimensions, especially when process noise is considered. In this paper, a Schur complement method is proposed...