A nearly zero-energy microgrid testbed laboratory: Centralized control strategy based on SCADA system

Currently, despite the use of renewable energy sources (RESs), distribution networks are facing problems, such as complexity and low productivity. Emerging microgrids (MGs) with RESs based on supervisory control and data acquisition (SCADA) are an effective solution to control, manage, and finally deal with these challenges. The development and success of MGs is highly dependent on the use of power electronic interfaces. The use of these interfaces is directly related to the progress of SCADA systems and communication infrastructures. The use of SCADA systems for the control and operation of MGs and active distribution networks promotes productivity and efficiency. This paper presents a real MG case study called the LAMBDA MG testbed laboratory, which has been implemented in the electrical department of the Sapienza University of Rome with a centralized energy management system (CEMS). The real-time results of the SCADA system show that a CEMS can create proper energy balance in a LAMBDA MG testbed and, consequently, minimize the exchange power of the LAMBDA MG and main grid

Formal Specification and Verification for Automated Production Systems

Complex industrial control software often drives safety- and mission-critical systems, like automated production plants or control units embedded into devices in automotive systems. Such controllers have in common that they are reactive systems, i.e., that they periodically read sensor stimuli and cyclically execute the same program to produce actuator signals. The correctness of software for automated production is rarely verified using formal techniques. Although, due to the Industrial Revolution 4.0 (IR4.0), the impact and importance of software have become an important role in industrial automation. What is used instead in industrial practice today is testing and simulation, where individual test cases are used to validate an automated production system. Three reasons why formal methods are not popular are: (a) It is difficult to adequately formulate the desired temporal properties. (b) There is a lack of specification languages for reactive systems that are both sufficiently expressive and comprehensible for practitioners. (c) Due to the lack of an environment model the obtained results are imprecise. Nonetheless, formal methods for automated production systems are well studied academically---mainly on the verification of safety properties via model checking. In this doctoral thesis we present the concept of (1) generalized test tables (GTTs), a new specification language for functional properties, and their extension (2) relational test tables (RTTs) for relational properties. The concept includes the syntactical notion, designed for the intuition of engineers, and the semantics, which are based on game theory. We use RTTs for a novel confidential property on reactive systems, the provably forgetting of information. Moreover, for regression verification, an important relational property, we are able to achieve performance improvements by (3) creating a decomposing rule which splits large proofs into small sub-task. We implemented the verification procedures and evaluated them against realistic case studies, e.g., the Pick-and-Place-Unit from the Technical University of Munich. The presented contribution follows the idea of lowering the obstacle of verifying the dependability of reactive systems in general, and automated production systems in particular for the engineer either by introducing a new specification language (GTTs), by exploiting existing programs for the specification (RTTs, regression verification), or by improving the verification performance

The DS-Pnet modeling formalism for cyber-physical system development

This work presents the DS-Pnet modeling formalism (Dataflow, Signals and Petri nets), designed for the development of cyber-physical systems, combining the characteristics of Petri nets and dataflows to support the modeling of mixed systems containing both reactive parts and data processing operations. Inheriting the features of the parent IOPT Petri net class, including an external interface composed of input and output signals and events, the addition of dataflow operations brings enhanced modeling capabilities to specify mathematical data transformations and graphically express the dependencies between signals. Data-centric systems, that do not require reactive controllers, are designed using pure dataflow models. Component based model composition enables reusing existing components, create libraries of previously tested components and hierarchically decompose complex systems into smaller sub-systems. A precise execution semantics was defined, considering the relationship between dataflow and Petri net nodes, providing an abstraction to define the interface between reactive controllers and input and output signals, including analog sensors and actuators. The new formalism is supported by the IOPT-Flow Web based tool framework, offering tools to design and edit models, simulate model execution on the Web browser, plus model-checking and software/hardware automatic code generation tools to implement controllers running on embedded devices (C,VHDL and JavaScript). A new communication protocol was created to permit the automatic implementation of distributed cyber-physical systems composed of networks of remote components communicating over the Internet. The editor tool connects directly to remote embedded devices running DS-Pnet models and may import remote components into new models, contributing to simplify the creation of distributed cyber-physical applications, where the communication between distributed components is specified just by drawing arcs. Several application examples were designed to validate the proposed formalism and the associated framework, ranging from hardware solutions, industrial applications to distributed software applications

Surface Modification of Pillar Array Systems for Chromatography and Fluorescence Enhancement

Thin-layer chromatography offers many advantages in the world of chemical separations due to its ease of use, high sensitivity, range of applicability, and multiplex capability. However, this technique is succeptible to band broadening effects that limit its efficiency. Attempting to resolve these effects by decreasing particle size causes a decrease in mobile phase velocity which creates its own band broadening via longitudinal diffusion. However, pillar array systems on the micro- and nanoscale have been shown as useful analogues to thin-layer chromatography which mitigate the efficiency concerns associated with the method. The work within this dissertation is concerned with the modification of pillar array surfaces for both chromatographic and spectroscopic purposes. The first aim is to increase the surface area of the pillars for chromatography by depositing porous phases such as petal-like carbon and porous silicon oxide. The usefulness of pillar arrays as separations systems is moderated by their limited native surface area. Increasing the surface area of a stationary phase can increase the retention of analyte by the system without negatively affecting its efficiency. While we found that petal-like carbon has several properties that made it unsuitable for these pillar array systems in their current form, porous silicon oxide showed great promise as a porous phase which increased the surface area of the pillars and the retention of analytes within them. The second aim was to immobilize fluorescent molecules at the pillar surface for signal enhancement. Pillars in the nanoscale have been shown to exhibit a field effect which amplifies fluorescence signal. To this end, we developed wet chemistry methods to functionalize the pillar surface with two different immobilizing resins, one using a uranium-capturing compound, and the other a biotin-avidin complex to sequester DNA. In both cases, we created high-throughput methods which retained high sensitivity while using only minimal amounts of sample

Broadband Power Line Communication in Railway Traction Lines: A Survey

Power line communication (PLC) is a technology that exploits existing electrical transmission and distribution networks as guiding structures for electromagnetic signal propagation. This facilitates low-rate data transmission for signaling and control operations. As the demand in terms of data rate has greatly increased in the last years, the attention paid to broadband PLC (BPLC) has also greatly increased. This concept also extended to railways as broadband traction power line communication (BTPLC), aiming to offer railway operators an alternative data network in areas where other technologies are lacking. However, BTPLC implementation faces challenges due to varying operating scenarios like urban, rural, and galleries. Hence, ensuring coverage and service continuity demands the suitable characterization of the communication channel. In this regard, the scientific literature, which is an indicator of the body of knowledge related to BTPLC systems, is definitely poor if compared to that addressed to BPLC systems installed on the electrical transmission and distribution network. The relative papers dealing with BTPLC systems and focusing on the characterization of the communication channel show some theoretical approaches and, rarely, measurements guidelines and experimental results. In addition, to the best of the author's knowledge, there are no surveys that comprehensively address these aspects. To compensate for this lack of information, a survey of the state of the art concerning BTPLC systems and the measurement methods that assist their installation, assessment, and maintenance is presented. The primary goal is to provide the interested readers with a thorough understanding of the matter and identify the current research gaps, in order to drive future research towards the most significant issues

Trajectory Tracking Control of an Autonomous Ground Vehicle

This thesis proposes a solution to the problem of making an autonomous nonholonomic ground vehicle track a special trajectory while following a reference velocity profile. The proposed strategies have been analyzed, simulated and eventually implemented and verified in Alice, Team Caltech's contribution to the 2007 DARPA Urban Challenge competition for autonomous vehicles. The system architecture of Alice is reviewed. A kinematic vehicle model is derived. Lateral and longitudinal controllers are proposed and analyzed, with emphasis on the nonlinear state feedback lateral controller. Relevant implementation aspects and contingency management is discussed. Finally, results from simulation and field tests are presented and discussed

Machine Learning and Data Mining Applications in Power Systems

This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries

Control strategies for Brushless DC motors

Tato diplomová práce se zabývá strategiemi řízení, které jsou dostupné pro bezkartáčové DC motory, a které mohou být použity pro řízení rychlosti pohonů elektrických vozidel. Úkolem práce je studium rozličných řídicích algoritmů, nalezení způsobů, jak optimalizovat jejich výkon, a zároveň simulovat jejich chování pro ověření jejich vlastností. Závěrečná etapa práce spočívá v přípravě implementovatelného řídicího algoritmu, který je poté spuštěn na laboratorním stanovišti s aktivním řídicím systémem založeným na zpětné vazbě PID regulátoru a uživatelského rozhraní (HMI) pro snadnou interakci v průběhu testu.Master's Thesis researching the various control strategies available for BLDC motor control that can then be employed in the speed control of electric vehicle drive systems. The task involved studying the various control algorithms, finding ways to optimize their performance and simulate them as a proof of concept. The final stage of the thesis involved the preparation of an implementable control algorithm that was then run on a test bench with an active PID feedback-based control system and HMI for easy interaction in runtime