Approximation Methods in Stochastic Max-Plus Systems

Stochastic max-plus systems belong to a special class of discrete-event systems. This class consists of systems with synchronization but no choice and the models of such systems are defined using the operators maximization and addition. Stochastic max-plus systems can be further extended to stochastic switching max-plus systems and stochastic min-max-plus-scaling systems. In the identification and control problem of all these systems, the objective function appearing in the optimization problem can be written as the expected value of the maximum of several affine expressions. The focus of this thesis is on finding an efficient method to compute this expected value since the currently available methods are both too complex and too time-consuming. To address this issue, this thesis proposes an approximation method based on the higher-order moments of a random variable. By considering the relationship between the infinity-norm and the p-norm of vectors, we obtain an upper bound for the expected value of the maximum of several affine expressions. This approximation method can be applied to any distribution that has finite moments and in the case that these moments have a closed form (such as for a uniform distribution, normal distribution, beta distribution, or gamma distribution), the approximation method results in an analytic expression. For all the above-mentioned systems, we have compared the performance of the proposed approximation method with other available methods, such as analytic and numerical integration, and Monte Carlo simulation. In nearly all cases, the computation time of the proposed approximation method is at least two orders of magnitude smaller than that of other methods, while still resulting in a comparable control performance.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin

Hydrogen-based integrated energy and mobility system for a real-life office environment

The current focus on the massive CO2 reduction highlights the need for the rapid development of technology for the production, storage, transportation and distribution of renewable energy. In addition to electricity, we need other forms of energy carriers that are more suitable for energy storage and transportation. Hydrogen is one of the main candidates for this purpose, since it can be produced from solar or wind energy and then stored; once needed, it can be converted back to electricity using fuel cells. Another important aspect of future energy systems is sector coupling, where different sectors, e.g. mobility and energy, work together to provide better services. In such an integrated system, electric vehicles – both battery and hydrogen-based fuel cell – can provide, when parked, electricity services, such as backup power and balancing; when driving they produce no emissions. In this paper we present the concept design and energy management of such an integrated energy and mobility system in a real-life environment at the Shell Technology Centre in Amsterdam. Our results show that storage using hydrogen and salt caverns is much cheaper than using large battery storage systems. We also show that the integration of electric vehicles into the electricity network is technically and economically feasible and that they can provide a flexible energy buffer. Ultimately, the results of this study show that using both electricity and hydrogen as energy carriers can create a more flexible, reliable and cheaper energy system at an office building.Energy TechnologyEnergy & Industr

Analysis and control of max-plus linear discrete-event systems: An introduction

The objective of this paper is to provide a concise introduction to the max-plus algebra and to max-plus linear discrete-event systems. We present the basic concepts of the max-plus algebra and explain how it can be used to model a specific class of discrete-event systems with synchronization but no concurrency. Such systems are called max-plus linear discrete-event systems because they can be described by a model that is “linear” in the max-plus algebra. We discuss some key properties of the max-plus algebra and indicate how these properties can be used to analyze the behavior of max-plus linear discrete-event systems. Next, some control approaches for max-plus linear discrete-event systems, including residuation-based control and model predictive control, are presented briefly. Finally, we discuss some extensions of the max-plus algebra and of max-plus linear systems.Delft Center for Systems and ControlTeam DeSchutterEnergy & Industr

Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty

Scheduled charging offers the potential for electric vehicles (EVs) to use renewable energy more efficiently, lowering costs and improving the stability of the electricity grid. Many studies related to EV charge scheduling found in the literature assume perfect or highly accurate knowledge of energy demand for EVs expected to arrive after the scheduling is performed. However, in practice, there is always a degree of uncertainty related to future EV charging demands. In this work, a Model Predictive Control (MPC) based smart charging strategy is developed, which takes this uncertainty into account, both in terms of the timing of the EV arrival as well as the magnitude of energy demand. The objective of the strategy is to reduce the peak electricity demand at an EV parking lot with PVarrays. The developed strategy is compared with both conventional EV charging as well as smart charging with an assumption of perfect knowledge of uncertain future events. The comparison reveals that the inclusion of a 24 h forecast of EV demand has a considerable effect on the improvement of the performance of the system. Further, strategies that are able to robustly consider uncertainty across many possible forecasts can reduce the peak electricity demand by as much as 39% at an office parking space. The reduction of peak electricity demand can lead to increased flexibility for system design, planning for EV charging facilities, deferral or avoidance of the upgrade of grid capacity as well as its better utilizationEnergy TechnologyEnergy & Industr

A hydrogen-based integrated energy and transport system: The design and analysis of the Car as Power Plant Concept

In recent years, the European Union (EU) has set ambitious targets toward a carbon-free energy transition. Many studies show that a drastic reduction in greenhouse gas emissions-at least 90% by 2050-is required. In the transition toward a sustainable energy system, solar (or green) hydrogen plays many important roles, as it is a clean and safe energy carrier that can also be used as a fuel in transportation and in electricity production. To understand and steer the transition from the current energy system toward an integrated hydrogenbased energy and transport system, we propose a framework that integrates a technical and economic feasibility study, a controllability study, and institutional analysis. This framework is applied to the Car as Power Plant (CaPP) concept, which is an integrated energy and transport system. Such a system consists of a power system based on wind and solar power, conversion of renewable energy surpluses to hydrogen using electrolysis, hydrogen storage and distribution, and hydrogen fuel cell vehicles that provide mobility, electricity, heat, and water. Controlling these vehicles in their different roles and designing an appropriate organizational system structure are necessary steps in the feasibility study. Our proposed framework for a future 100% renewable energy system is presented through a case study.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Energy & IndustryEnergy TechnologyTeam DeSchutterDelft Center for Systems and Contro