Universität Stuttgart
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Item Open Access Feasibility analysis of using Model Predictive Control in Demand-Side Management of residential building(2020) Ramachandran Selvaraj, Sri VishnuThe energy systems are becoming smart recently with an increase in communication capabilities between producer, distributor and consumer. Also, many distributed renewable energy producers both in large and domestic scale are adding to the system day by day. Executing Smart Demand-Side Management (DSM) programs can help in providing financial benefits and stability of the energy system without compromising the comfort of end-users. Model Predictive Control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. Due to its ability to predict future events and generate optimal control, it is widely used in process industries since the 1980s and in recent years it is introduced in power systems. This motivates to study the economic feasibility of using MPC in executing DSM for Residential building, to optimize the power consumption costs and stability of the energy system in the presence of local renewable energy sources (E.g., PV system). The main contribution of this thesis work is to measure the economic benefit of using MPC on DSM of household electricity consumption. A detailed study of modeling the demand side, i.e the appliances of a smart home, along with the domestic energy generators is done in the initial part. Apart from the physical properties of the renewable energy generators, the influence of external factors like weather, dynamic-pricing of electricity and changing user preference is also considered in the model. This formulated model is used to perform simulation of the residential building to generate an optimized energy consumption schedule and calculate the resulting economic benefits. The periodic changes in weather forecast and dynamic-prices are fed into the simulation to improve the prediction accuracy of the system. Lastly, the model is evaluated on a physical implementation to analyze its performance. There are multiple findings as part of the result of this thesis, like the economic benefit of using such a system will encourage many users to participate in Demand response programs, this in turn will help in the reduction of pollution originating from non-renewable energy generators.Item Open Access Economic feasibility analysis of vehicle-to-grid service from an EV owner's perspective in the german electricity market(2020) Malya, Prasad PrakashThe increasing number of Electrical Vehicles (EV) has led to a tremendous amount of inac- cessible electric energy stored in the EV batteries. Vehicle-to-grid (V2G) services can utilize this energy to profit the EV owners’ and stabilize the grid during faults and fluctuations. This thesis presents a novel way of estimating the profitability of V2G from the EV owner’s perspective. The main contribution of this thesis is the formulation of a profit model that includes the EV battery degradation due to V2G. The work done so far considers fixed battery degradation cost, whereas in this work, an online battery degradation model is used. This model takes into account the parameters that represent real-life scenarios resulting in more accurate battery degradation estimation. The V2G profit model uses the electricity price signal from the German energy market for the year 2019 and estimates the annual profit. The first part of the thesis calculates the profitability of V2G, where EV can participate freely in energy arbitrage. This analysis explores the range of profit when EV participates in V2G purely based on the EV owner’s discretion. A sensitivity analysis is done with respect to battery capacity, battery efficiency, and driving distance. The second part of the thesis evaluates the profitability of EV participating in the German energy market’s frequency regulation ancillary service.=. The analysis compares the profitability of EV participating in primary, secondary, and tertiary frequency regulation services. The results of this thesis provide several findings, the potential profit from V2G services should encourage EV owners’ to participate in the V2G services. Additionally, participating in V2G service can extend the life of the battery. However, this depends on the battery technology and battery usage during V2G services. Ancillary services provide higher potential profit compared to energy arbitrage because of the high remuneration scheme. The ancillary services with both capacity and energy payment result in higher profit compared to ancillary services with only capacity payment.Item Open Access Enhancing HTN planning with deep reinforcement learning for method selection(2025) Bahrami, SepidehAutomated planning is a central area within Artificial Intelligence (AI), enabling intelligent behavior in domains such as cloud computing, autonomous systems, context-aware activity recognition, and smart environments. Hierarchical Task Network (HTN) planning, which decomposes complex tasks into simpler subtasks using predefined methods, has proven effective in such structured domains. However, its performance is often constrained by static method selection strategies that lack adaptability to varying planning contexts. To address this limitation, this thesis proposes a neuro-symbolic framework that integrates HTN planning with Deep Reinforcement Learning (DRL), combining the strengths of symbolic reasoning and data-driven learning. Among the available DRL algorithms, Deep Q-Learning (DQL) is particularly suitable due to its off-policy nature, batch-efficient learning, and robust generalization across symbolic planning states. These characteristics align well with deterministic and hierarchical planners, enabling offline learning from curated datasets without requiring interactive exploration. The proposed integration introduces a learning-based decision layer that improves adaptability while preserving the reproducibility and determinism of the underlying planner. The effectiveness of this approach is demonstrated through a comprehensive evaluation across planning efficiency, memory consumption, and plan quality. Results highlight the potential of reinforcement learning to enhance classical HTN systems and support intelligent decision-making in complex, structured environments.Item Open Access Die Rolle von Verschränkung im Quantencomputing : Speedup und Konsensusprotokolle(2019) Salm, Marie OliviaIn Zukunft werden Quantencomputer Probleme womöglich effizienter lösen als klassische Computer. Dies wäre eine bahnbrechende Errungenschaft und erweckt daher große Hoffnungen bei Forschung und Wirtschaft. Noch befindet sich das Gebiet der Quanteninformatik und des Quantencomputings vor allem in der Grundlagenforschung, und die Entwicklung eines leistungsfähigen Quantencomputers liegt noch in weiter Ferne. Dennoch werden bereits heute Quantenalgorithmen entwickelt, die eine Überlegenheit gegenüber klassischen Algorithmen aufzeigen könnten. So könnten verteilte Systeme von den quantenmechanischen Eigenschaften unter anderem durch Kommunikationsersparnisse profitieren. In dieser Arbeit wurde untersucht, ob das Phänomen der Verschränkung für den möglichen Speedup gegenüber klassischen Computer verantwortlich ist. Dazu wurden Annahmen wissenschaftlicher Arbeiten zusammengefasst. Des Weiteren wurde das Konsensusprotokoll Paxos mit quantenmechanischen Konzepten erweitert. Für eine der Erweiterungen wurde der verschränkte W-Zustand für die Wahl eines Proposers eingesetzt. In der zweiten Erweiterung wurde für die Bestimmung einer Rundennummer Superposition verwendet. Zudem wurde das 2-Phasen-Commit-Protokoll in unterschiedlichen Varianten mit dem GHZ-Zustand erweitert. Auch für das 3-Phasen-Commit-Protokoll wurde der W-Zustand für die Wahl eines Koordinators verwendet. Die Ergebnisse zeigen unter anderem, dass eine Reduzierung des Kommunikationsaufwands bei Paxos und dem 3-Phasen-Commit-Protkoll möglich ist. Es zeigt sich auch, dass eine Deblockierung des erweiterten 2-Phasen-Commit-Protokolls in der behandelten Weise nicht möglich ist.Item Open Access Ereignisbasierte Architektur für Quantenanwendungen(2021) Basaric, StefanIm Vergleich zu herkömmlichen Rechnern können mithilfe von Quantencomputern zum ersten Mal komplexe Probleme mit akzeptablen Berechnungszeiten gelöst werden. Diese werden heutzutage durch eine Vielzahl von öffentlichen Cloud-Diensten wie IBM Quantum, Amazon Braket oder Azure Quantum registrierten Nutzern verfügbar gemacht. Um ihre Experimente auf Quantencomputern durchführen zu können, müssen Nutzer Quantenschaltungen schreiben und an die von den Cloud-Diensten bereitgestellten Schnittstellen schicken. Die Quantenschaltungen kommen dabei zunächst in eine Warteschlange, bevor sie schließlich auf dem Quantencomputer ausgeführt werden. Das hat zur Folge, dass die Ausführung im Vergleich zur reinen Berechnungszeit auf dem Quantencomputer sehr lange dauern kann. Die aktuell verfügbaren Cloud-Dienste bieten derzeit keine Möglichkeit, die Quantenanwendungen ihrer Nutzer zu hosten und sie beim Eintritt von Ereignissen automatisch auszuführen. In dieser Arbeit wird ein Konzept für eine ereignisbasierte Architektur vorgestellt, welches die automatisierte Ausführung von Quantenanwendungen beim Eintritt von beliebigen Ereignissen ermöglicht. Zusätzlich wird ein anhand des Konzepts umgesetzter Prototyp präsentiert, welcher mithilfe von IBM Quantum und OpenWhisk die ereignisbasierte Ausführung von Quantenanwendungen trotz einiger Limitationen ermöglicht.Item Open Access Integration of IoT devices via a blockchain-based decentralized application(2017) Ahmad, AfzaalBlockchains are shared, immutable ledgers for recording the history of transactions. They foster a new generation of transactional applications that establish trust, accountability, and transparency. It enables contract partners to secure a deal without involving a trusted third party. Initially, the focus was on financial industry for digital assets trading like Bitcoin, but with the emergence of Smart Contracts, blockchain becomes a complete programmable platform. Many research and commercial organization start diving into blockchain world, bringing new ideas of its application in different sectors like supply chain, Health, and autonomous shopping. This thesis presents an idea to integrate Internet of Things (IoT) devices via a blockchain based decentralize application based on Ethereum. The application consists of front-end application which can be deployed to any web server, and a smart contract which will be deployed on a private blockchain network comprises of Peer-to-Peer (P2P) connected IoT devices acting as full Ethereum node. The application emulates the digital transport ticketing system where the asset is a ticket which can be purchased and paid by the user using ether in their Ethereum account on the blockchain. Once the purchase transaction is mined, it is propagated to all the peers. Ticket can now be accessed locally without requesting any centralized system, which makes the system easily accessible and safe because of the security, data integrity and decentralization of the blockchain-based systems.Item Open Access Crawling hardware for OpenTOSCA(2017) Choudhury, PushpamHeterogeneity is the essence of the IoT paradigm. There is heterogeneity in communication and transport protocols, in network infrastructure, and even among the interacting devices themselves. Managing discovery of the different devices in such a paradigm is an extremely complex task. The typical solutions include an abstraction layer, commonly known as the middleware layer, that handles this complexity for the devices, thereby, allowing them to interact with one another. One major limitation of the existing middleware solutions is in their ability to allow for an easily configurable approach required to handle the tremendous scale of heterogeneous components in the IoT. The objective of this thesis is to develop such a highly configurable discovery middleware approach. The proposed approach aims to discover a variety of heterogeneous devices and services depending on a multi-level plugin layer, consisting of independent plugins that interact with each other based on the pipes and filters architectural pattern. To allow for the dynamic configuration of the middleware, a discovery configuration is developed. The output from the middleware includes a list of devices and their capabilities and is accessible via a web interface which can interact with a range of different clients. The proposed approach is validated on a scenario in a real-life environment.Item Open Access Modeling and timing analysis of micro-ROS application on an off-road vehicle control unit(2022) Bappanadu, Suraj RaoROS is known to be the most popular middleware for the development of software in modern day robots. It's next version, ROS 2 is highly modular and offers flexibility by supporting on microprocessors running desktop operating systems. Micro-ROS puts the major ROS 2 features on microcontrollers, i.e., highly resource-constrained computing devices running specialized real-time operating systems. ROS 2 is also of great importance for other domains, including autonomous driving and the off-road sector. Accordingly, there is significant interest in bringing micro-ROS to typical automotive control units. These embedded platforms support AUTOSAR Classic OSEK-like operating system which is very different in many aspects when compared to the platforms supported by micro-ROS. Some of the aspects have already been addressed in a previous work. This thesis mainly focuses on mapping the micro-ROS execution scheme to AUTOSAR scheme and dynamic memory management of the micro-ROS stack. From the micro-ROS architecture perspective, to successfully port the stack on an AUTOSAR-based ECU, the middleware and other layers of the stack are also analysed and adapted using a standard approach to support tasks-like execution model instead of threads-like execution model. Additionally, the support for standard CAN protocol based on custom transport configuration with the hardware CAN on the BODAS ECU is introduced. Model-based development methods have proven their utility in automotive industry. Therefore, we also focus on describing the timing properties of the micro-ROS stack in a model-based approach. We develop a generic model which is independent of a specific modeling language. In the next step, we realize the generic model using the widely used AMALTHEA language and analyse how well the developed model predicts the timing behavior of micro-ROS tasks. Finally, the effectiveness of the approach regarding timing and modeling is demonstrated with a micro-ROS test application first on Linux and then on the off-road vehicle control unit BODAS RC18-12/40 by Bosch Rexroth.Item Open Access API diversity for microservices in the domain of connected vehicles(2018) Gajek, FabianWeb services in the domain of connected vehicles are subject to various requirements including high availability and large workloads. Microservices are an architectural style which can fulfill those requirements by fostering the independence and decoupling of software components as reusable services. To achieve this independence, microservices have to implement all aspects of providing the services themselves, including different API technologies for heterogeneous consumers and supporting features like authentication. In this work, we examine the use of a service proxy that externalizes these concerns into a sidecar that provides multiple APIs and common service functionality in a platform-independent manner. We look at how different kinds of API styles and technologies solve selected classes of problems and how we can translate between API technologies. We design and implement a framework for building gateways that enables the creation and composition of reusable components, in the fashion of Lego bricks, to maximize flexibility, while reducing the effort for building gateway components. We design and implement selected components of common and reusable API functionality enabling us to build a reference setup with a service proxy as a sidecar using our framework. Finally, we evaluate the proposed solution to identify benefits and drawbacks of the approach of using our framework as a service proxy. We conclude that the examined approach provides benefits for the development of many polyglot microservices, but splitting one service into two components adds additional complexity that has to be managed.Item Open Access Industry practices and challenges of using AI planning : an interview-based study(2024) Vashisth, DhananjayIn the rapidly evolving landscape of industrial applications, AI planning systems have emerged as critical tools for optimizing processes and decision-making. However, implementing and integrating these systems present significant challenges that can hinder their effectiveness. This thesis addresses the urgent need to understand the best practices and challenges involved in designing, integrating, and deploying AI planning systems in industrial settings. Without this understanding, industries risk inefficient implementation, leading to poor performance and resistance from end-users. This research employs a methodology that includes a literature review and interviews with industry professionals and researchers to identify common strategies and obstacles practitioners face. The study examines existing literature to uncover reported best practices and challenges in AI planning systems. Interviews provide additional perspectives, enriching the data collected and ensuring a thorough analysis. The findings reveal best practices, including the importance of cross-disciplinary collaboration, robust data management strategies, and iterative development processes. Additionally, recurring challenges such as integration complexities, scalability issues, and the need for continuous system evaluation are identified. These insights highlight critical areas for improvement and offer practical recommendations for enhancing the effectiveness of AI planning systems in industrial applications.