REGKLAM Entwicklung und Erprobung eines integrierten regionalen Klimaanpassungsprogramms für die Modellregion Dresden

Dies ist ein Poster aus dem REGKLAM-Vorhaben, welches einen Überblick über das Projekt als Ganzes liefert

On the micciancio-voulgaris algorithm to solve the long-horizon direct MPC optimization problem

Conference ProceedingsIt is widely accepted that model predictive control (MPC) with long prediction horizons yields, in general, a better performance than with short horizons. In the context of power electronic systems, the main advantages include improved closedloop stability and lower current distortion per switching frequency. A shortcoming of MPC with long prediction horizons is the computational burden associated with solving the optimization problem in real time, which limits the minimum possible sampling interval. The solution to the MPC optimization problem is a polyhedral partition of the state-space. Pre-processing of the state-space and storing representative information thereof offline assists in reducing the online computational burden. The problem structure is a special case in the form of a truncated lattice. Exploiting this characteristic enables representation of the partitioned space to be is stored as a minimal set of Voronoi relevant vectors describing the basic Voronoi cell of a lattice. We evaluate the algorithm proposed by Micciancio and Voulgaris known as the MV-algorithm to solve the closest vector problem with pre-processing (CVPP). The performance of the algorithm is evaluated in a simulated three-level neutral point clamped (NPC) voltage source inverter with an RL load

Hält die technische Analyse was sie verspricht? Eine Empirische Untersuchung des technischen Aktienindikators MACD in verschiedenen Märkten und Marktphasen

Technische Analyse, Efficient Market Hypothesis, Moving Average Convergence Divergence Indicator (MACD), Average Directional Movement Indicator (ADX), Aktienmärkte

Declarative Guideline Conformance Checking of Clinical Treatments: A Case Study

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Thus, this technique is predestined to be used in the medical context for the comparison of treatment cases with clinical guidelines. However, medical processes are highly variable, highly dynamic, and complex. This makes the use of imperative conformance checking approaches in the medical domain difficult. Studies show that declarative approaches can better address these characteristics. However, none of the approaches has yet gained practical acceptance. Another challenge are alignments, which usually do not add any value from a medical point of view. For this reason, we investigate in a case study the usability of the HL7 standard Arden Syntax for declarative, rule-based conformance checking and the use of manually modeled alignments. Using the approach, it was possible to check the conformance of treatment cases and create medically meaningful alignments for large parts of a medical guideline

Three-Level Optimized Pulse Patterns With Reduced Common-Mode Voltage

This paper proposes the computation of three-level optimized pulse patterns (OPPs) with reduced common-mode voltage (CMV) over the whole range of modulation indices. Limiting the CMV, however, gives rise to increased current harmonics. To mitigate this, the OPP optimization problem is reformulated to allow for symmetry relaxations and multipolar switch positions. In doing so, the current harmonics not only remain low, but they are occasionally even lower than those of traditional OPPs. The presented numerical results, based on a medium-voltage (MV) drive consisting of a three-level converter and an induction machine, demonstrate the benefits of the proposed approach.acceptedVersionPeer reviewe

Gradient-Based Predictive Pulse Pattern Control

This paper presents a control scheme that combines the optimal steady-state performance of optimized pulse patterns (OPPs) with the fast dynamics of direct model predictive control (MPC). Due to inherent challenges that relate to the utilization of OPPs in a closed-loop setting, OPPs are traditionally used in slow control loops. As a result, the associated dynamic performance of the drive system is considerably poor. To overcome this, in this work, a direct MPC algorithm is employed to manipulate the OPPs in a fast, yet optimal, manner. Specifically, the MPC algorithm takes advantage of the knowledge of the stator current evolution—as described by its gradient—within the prediction horizon. Subsequently, a constrained optimization problem with a receding horizon is solved to compute the optimal modification of the offline-computed OPP such that superior steady-state and dynamic performance is achieved. The effectiveness of the proposed method is verified based on a variable speed drive system, which consists of a two-level inverter and a low-voltage induction machine.acceptedVersionPeer reviewe

A Direct Model Predictive Control Strategy with Optimized Sampling Interval

In this paper we present a direct model predictive control (MPC) scheme with time-varying sampling intervals. These sampling intervals are computed based on modulation (half-)cycles, which are obtained offline and stored in a look-up table. By utilizing the optimized modulation (half-)cycles and combining control and modulation in one computational stage, the proposed direct MPC scheme achieves lower current total harmonic distortion (THD) than conventional linear controllers with a dedicated modulator, and fast transient responses that characterize direct control methods. The effectiveness of the proposed control scheme is verified on a variable speed drive system consisting of a two-level voltage source inverter and an induction machine.acceptedVersionPeer reviewe

Gradient-Based Predictive Pulse Pattern Control with Active Neutral Point Balancing for Three-Level Inverter Medium-Voltage Drives

This paper presents a control method for three-level neutral point clamped (NPC) inverter medium-voltage (MV) drives that addresses the stator current control problem and balancing of the neutral point (NP) potential in a single control loop. To do so, a model predictive control (MPC) algorithm, designed as a multiple-input multiple-output (MIMO) controller, manipulates optimized pulse patterns (OPPs) in real time. As a result, minimal current harmonic distortions are produced, while the NP potential is kept balanced both during steady state and transients. The presented results demonstrate the effectiveness of the proposed control strategy for three-level NPC inverter MV variable speed drive systems.acceptedVersionPeer reviewe

Gradient-Based Predictive Pulse Pattern Control of Medium-Voltage Drives-Part I : Control, Concept, and Analysis

This article proposes a control and modulation strategy for medium-voltage (MV) drives that exhibits excellent steady-state and transient behavior. Specifically, optimized pulse patterns (OPPs) and direct model predictive control are employed so that the associated advantages of both, such as minimum stator current total demand distortion (TDD) and fast transients, respectively, are fully exploited. To do so, the current reference trajectory tracking and modulation problems are addressed in a coordinated manner in the form of a constrained optimization problem that utilizes the knowledge of the stator current evolution-as described by its gradient-within the prediction horizon. Solving this problem yields the optimal real-time modification of the offline-computed OPP, which guarantees that very low-and close to its theoretical minimum value-stator current TDD is produced at steady state, and very short settling times during transients. To highlight the effectiveness of the proposed strategy, a variable speed drive system consisting of a three-level neutral point clamped inverter and an MV induction machine serves as a case study.publishedVersionPeer reviewe

Gradient-Based Predictive Pulse Pattern Control of Medium-Voltage Drives-Part II : Performance Assessment

In this article, the performance of gradient-based predictive pulse pattern control (GP 3C) is evaluated for a medium-voltage variable-speed drive consisting of a three-level neutral-point-clamped (NPC) inverter and a medium-voltage induction machine. To this end, real-time tests are performed in a hardware-in-the-loop (HIL) environment, which, along with extensive simulation studies, elucidate the potential of performance gains achieved with GP3C. As shown, by manipulating offline-computed optimized pulse patterns (OPPs) in real time such that the stator current of the machine follows a precalculated optimal current trajectory, superior steady-state and transient performance can be achieved. Specifically, the current total demand distortion (TDD) is significantly reduced compared with established control methods, such as field-oriented control (FOC) with space vector modulation (SVM), while shorter settling times during transients are achieved. Finally, to complete the assessment of the control method of interest, real-time implementation aspects are discussed in detail.publishedVersionPeer reviewe