Distributed control strategies for photovoltaic systems in urban environments : Versión definitiva

Este trabajo es una contribución a los sistemas fotovoltaicos (FV) con seguimiento distribuido del punto de máxima potencia (DMPPT), una topología que se caracteriza porque lleva a cabo el MPPT a nivel de módulo, al contrario de las topologías más tradicionales que llevan a cabo el MPPT para un número más elevado de módulos, pudiendo ser hasta cientos de módulos. Las dos tecnologías DMPPT que existen en el mercado son conocidos como microinversores y optimizadores de potencia, y ofrecen ciertas ventajas sobre sistemas de MPPT central como: mayor producción en situaciones de mismatch, monitorización individual de cada módulo, flexibilidad de diseño, mayor seguridad del sistema, etc. Aunque los sistemas DMPPT no están limitados a los entornos urbanos, se ha enfatizado en el título ya que es su mercado natural, siendo difícil una justificación de su sobrecoste en grandes huertas solares en suelo. Desde el año 2010 el mercado de estos sistemas ha incrementado notablemente y sigue creciendo de una forma continuada. Sin embargo, todavía falta un conocimiento profundo de cómo funcionan estos sistemas, especialmente en el caso de los optimizadores de potencia, de las ganancias energéticas esperables en condiciones de mismatch y de las posibilidades avanzadas de diagnóstico de fallos. El principal objetivo de esta tesis es presentar un estudio completo de cómo funcionan los sistemas DMPPT, sus límites y sus ventajas, así como experimentos varios que verifican la teoría y el desarrollo de herramientas para valorar las ventajas de utilizar DMPPT en cada instalación. Las ecuaciones que modelan el funcionamiento de los sistemas FVs con optimizadores de potencia se han desarrollado y utilizado para resaltar los límites de los mismos a la hora de resolver ciertas situaciones de mismatch. Se presenta un estudio profundo sobre el efecto de las sombras en los sistemas FVs: en la curva I-V y en los algoritmos MPPT. Se han llevado a cabo experimentos sobre el funcionamiento de los algoritmos MPPT en situaciones de sombreado, señalando su ineficiencia en estas situaciones. Un análisis de la ventaja del uso de DMPPT frente a los puntos calientes es presentado y verificado. También se presenta un análisis sobre las posibles ganancias en potencia y energía con el uso de DMPPT en condiciones de sombreado y este también es verificado experimentalmente, así como un breve estudio de su viabilidad económica. Para ayudar a llevar a cabo todos los análisis y experimentos descritos previamente se han desarrollado una serie de herramientas software. Una siendo un programa en LabView para controlar un simulador solar y almacenar las medidas. También se ha desarrollado un programa que simula curvas I-V de módulos y generador FVs afectados por sombras y este se ha verificado experimentalmente. Este mismo programa se ha utilizado para desarrollar un programa todavía más completo que estima las pérdidas anuales y las ganancias obtenidas con DMPPT en instalaciones FVs afectadas por sombras. Finalmente, se han desarrollado y verificado unos algoritmos para diagnosticar fallos en sistemas FVs con DMPPT. Esta herramienta puede diagnosticar los siguientes fallos: sombras debido a objetos fijos (con estimación de la distancia al objeto), suciedad localizada, suciedad general, posible punto caliente, degradación de módulos y pérdidas en el cableado de DC. Además, alerta al usuario de las pérdidas producidas por cada fallo y no requiere del uso de sensores de irradiancia y temperatura. ABSTRACT This work is a contribution to photovoltaic (PV) systems with distributed maximum power point tracking (DMPPT), a system topology characterized by performing the MPPT at module level, instead of the more traditional topologies which perform MPPT for a larger number of modules. The two DMPPT technologies available at the moment are known as microinverters and power optimizers, also known as module level power electronics (MLPE), and they provide certain advantages over central MPPT systems like: higher energy production in mismatch situations, monitoring of each individual module, system design flexibility, higher system safety, etc. Although DMPPT is not limited to urban environments, it has been emphasized in the title as it is their natural market, since in large ground-mounted PV plants the extra cost is difficult to justify. Since 2010 MLPE have increased their market share steadily and continuing to grow steadily. However, there still lacks a profound understanding of how they work, especially in the case of power optimizers, the achievable energy gains with their use and the possibilities in failure diagnosis. The main objective of this thesis is to provide a complete understanding of DMPPT technologies: how they function, their limitations and their advantages. A series of equations used to model PV arrays with power optimizers have been derived and used to point out limitations in solving certain mismatch situation. Because one of the most emphasized benefits of DMPPT is their ability to mitigate shading losses, an extensive study on the effects of shadows on PV systems is presented; both on the I-V curve and on MPPT algorithms. Experimental tests have been performed on the MPPT algorithms of central inverters and MLPE, highlighting their inefficiency in I-V curves with local maxima. An analysis of the possible mitigation of hot-spots with DMPPT is discussed and experimentally verified. And a theoretical analysis of the possible power and energy gains is presented as well as experiments in real PV systems. A short economic analysis of the benefits of DMPPT has also been performed. In order to aide in the previous task, a program which simulates I-V curves under shaded conditions has been developed and experimentally verified. This same program has been used to develop a software tool especially designed for PV systems affected by shading, which estimates the losses due to shading and the energy gains obtained with DMPPT. Finally, a set of algorithms for diagnosing system faults in PV systems with DMPPT has been developed and experimentally verified. The tool can diagnose the following failures: fixed object shading (with distance estimation), localized dirt, generalized dirt, possible hot-spots, module degradation and excessive losses in DC cables. In addition, it alerts the user of the power losses produced by each failure and classifies the failures by their severity and it does not require the use of irradiance or temperature sensors.

Development of a human movement monitoring system based on wearable devices

It is essential to remotely and continuously monitor the movements of individuals in many social areas, for example, taking care of aging people, physical therapy, athletic training etc. Many methods have been used, such as video record, motion analysis or sensor-based methods. Due to the limitations in remote communication, power consumption, portability and so on, most of them are not able to fulfill the requirements. The development of wearable technology and cloud computing provides a new efficient way to achieve this goal. This paper presents an intelligent human movement monitoring system based on a smartwatch, an Android smartphone and a distributed data management engine. This system includes advantages of wide adaptability, remote and long-term monitoring capacity, high portability and flexibility. The structure of the system and its principle are introduced. Four experiments are designed to prove the feasibility of the system. The results of the experiments demonstrate the system is able to detect different actions of individuals with adequate accuracy.

Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Development of the infrastructure for a multi-agent traffic management system simulation

This document contains detailed description of the design and the implementation of a multi-agent application controlling traffic lights in a city together with a system for simulating traffic and testing. The goal of this thesis is to design and build a simplified intelligent and distributed solution to the problem with the traffic in the big cities following different good practices in order to allow future refining of the model of the real world. The problem of the traffic in the big cities is still a problem that cannot be solved. Not only is the increasing number of cars a reason for the traffic jams, but also the way the traffic is organized. Usually, the intersections with traffic lights are replaced by roundabouts or interchanges to increase the number of cars that can cross the intersection in certain time. But still there are places where the infrastructure cannot be changed and the traffic light semaphores are the only way to control the car flows. In real life, the traffic lights have a predefined plan for change or they receive information from a centralized system when and how they have to change. But what if the traffic lights can cooperate and decide on their own when and how to change? Using this problem, the purpose of the thesis is to explore different agent-based software engineering approaches to design and build a non-conventional distributed system. From the software engineering point of view, the goal of the thesis is to apply the knowledge and use the skills, acquired during the various courses of the master program in Software Engineering, while solving a practical and complex problem such as the traffic in the cities.

Context-awareness in task automation services by distributed event processing

Everybody has to coordinate several tasks everyday, usually in a manual manner. Recently, the concept of Task Automation Services has been introduced to automate and personalize the task coordination problem. Several user centered platforms and applications have arisen in the last years, that let their users configure their very own automations based on third party services. In this paper, we propose a new system architecture for Task Automation Services in a heterogeneous mobile, smart devices, and cloud services environment. Our architecture is based on the novel idea to employ distributed Complex Event Processing to implement innovative mixed execution profiles. The major advantage of the approach is its ability to incorporate context-awareness and real-time coordination in Task Automation Services.

Hardware timestamping for image acquisition system based on FlexRIO and IEEE 1588 v2 Standard

Current fusion devices consist of multiple diagnostics and hundreds or even thousands of signals. This situation forces on multiple occasions to use distributed data acquisition systems as the best approach. In this type of distributed systems, one of the most important issues is the synchronization between signals, so that it is possible to have a temporal correlation as accurate as possible between the acquired samples of all channels. In last decades, many fusion devices use different types of video cameras to provide inside views of the vessel during operations and to monitor plasma behavior. The synchronization between each video frame and the rest of the different signals acquired from any other diagnostics is essential in order to know correctly the plasma evolution, since it is possible to analyze jointly all the information having accurate knowledge of their temporal correlation. The developed system described in this paper allows timestamping image frames in a real-time acquisition and processing system using 1588 clock distribution. The system has been implemented using FPGA based devices together with a 1588 synchronized timing card (see Fig.1). The solution is based on a previous system [1] that allows image acquisition and real-time image processing based on PXIe technology. This architecture is fully compatible with the ITER Fast Controllers [2] and offers integration with EPICS to control and monitor the entire system. However, this set-up is not able to timestamp the frames acquired since the frame grabber module does not present any type of timing input (IRIG-B, GPS, PTP). To solve this lack, an IEEE1588 PXI timing device its used to provide an accurate way to synchronize distributed data acquisition systems using the Precision Time Protocol (PTP) IEEE 1588 2008 standard. This local timing device can be connected to a master clock device for global synchronization. The timing device has a buffer timestamp for each PXI trigger line and requires tha- a software application assigns each frame the corresponding timestamp. The previous action is critical and cannot be achieved if the frame rate is high. To solve this problem, it has been designed a solution that distributes the clock from the IEEE 1588 timing card to all FlexRIO devices [3]. This solution uses two PXI trigger lines that provide the capacity to assign timestamps to every frame acquired and register events by hardware in a deterministic way. The system provides a solution for timestamping frames to synchronize them with the rest of the different signals.

System failure prediction through rare-events elastic-net logistic regression

Predicting failures in a distributed system based on previous events through logistic regression is a standard approach in literature. This technique is not reliable, though, in two situations: in the prediction of rare events, which do not appear in enough proportion for the algorithm to capture, and in environments where there are too many variables, as logistic regression tends to overfit on this situations; while manually selecting a subset of variables to create the model is error- prone. On this paper, we solve an industrial research case that presented this situation with a combination of elastic net logistic regression, a method that allows us to automatically select useful variables, a process of cross-validation on top of it and the application of a rare events prediction technique to reduce computation time. This process provides two layers of cross- validation that automatically obtain the optimal model complexity and the optimal mode l parameters values, while ensuring even rare events will be correctly predicted with a low amount of training instances. We tested this method against real industrial data, obtaining a total of 60 out of 80 possible models with a 90% average model accuracy.

Multi-distributed wireless sensors for monitoring a long distance transport in a reefer container

The study of the temperature gradients in cold stores and containers is a critical issue in the food industry for the quality assurance of products during transport and for minimising losses. This work presents an analysis of the temperatures during the refrigerated transport of 4,320 kg of blueberries in a reefer (set point temperature at ?1ºC) on a container ship from Montevideo (Uruguay) to Verona (Italy). The monitoring was performed by using semi-passive RFID loggers (TurboTag cards). The objective was to carry out a multi-distributed supervision using low-cost, wireless and autonomous sensors for the characterisation of the distribution and spatial gradients of temperatures during a long distance transport. Data analysis shows spatial (phase space) and temporal sequencing diagrams and reveals a significant heterogeneity of temperature at different locations in the container, which highlights the ineffectiveness of a temperature control system based on a single sensor, as is usually done.

Agreement Abstractions in Anonymous and Homonymous Distributed Systems Prone to Failures

The distributed computing models typically assume every process in the system has a distinct identifier (ID) or each process is programmed differently, which is named as eponymous system. In such kind of distributed systems, the unique ID is helpful to solve problems: it can be incorporated into messages to make them trackable (i.e., to or from which process they are sent) to facilitate the message transmission; several problems (leader election, consensus, etc.) can be solved without the information of network property in priori if processes have unique IDs; messages in the register of one process will not be overwritten by others process if this process announces; it is useful to break the symmetry. Hence, eponymous systems have influenced the distributed computing community significantly either in theory or in practice. However, every thing in the world has its own two sides. The unique ID also has disadvantages: it can leak information of the network(size); processes in the system have no privacy; assign unique ID is costly in bulk-production(e.g, sensors). Hence, homonymous system is appeared. If some processes share the same ID and programmed identically is called homonymous system. Furthermore, if all processes shared the same ID or have no ID is named as anonymous system. In homonymous or anonymous distributed systems, the symmetry problem (i.e., how to distinguish messages sent from which process) is the main obstacle in the design of algorithms. This thesis is aimed to propose different symmetry break methods (e.g., random function, counting technique, etc.) to solve agreement problem. Agreement is a fundamental problem in distributed computing including a family of abstractions. In this thesis, we mainly focus on the design of consensus, set agreement, broadcast algorithms in anonymous and homonymous distributed systems. Firstly, the fault-tolerant broadcast abstraction is studied in anonymous systems with reliable or fair lossy communication channels separately. Two classes of anonymous failure detectors AΘ and AP∗ are proposed, and both of them together with a already proposed failure detector ψ are implemented and used to enrich the system model to implement broadcast abstraction. Then, in the study of the consensus abstraction, it is proved the AΩ′ failure detector class is strictly weaker than AΩ and AΩ′ is implementable. The first implementation of consensus in anonymous asynchronous distributed systems augmented with AΩ′ and where a majority of processes does not crash. Finally, a general consensus problem– k-set agreement is researched and the weakest failure detector L used to solve it, in asynchronous message passing systems where processes may crash and recover, with homonyms (i.e., processes may have equal identities), and without a complete initial knowledge of the membership.

Agreement Abstractions in Anonymous and Homonymous Distributed Systems Prone to Failures

The distributed computing models typically assume every process in the system has a distinct identifier (ID) or each process is programmed differently, which is named as eponymous system. In such kind of distributed systems, the unique ID is helpful to solve problems: it can be incorporated into messages to make them trackable (i.e., to or from which process they are sent) to facilitate the message transmission; several problems (leader election, consensus, etc.) can be solved without the information of network property in priori if processes have unique IDs; messages in the register of one process will not be overwritten by others process if this process announces; it is useful to break the symmetry. Hence, eponymous systems have influenced the distributed computing community significantly either in theory or in practice. However, every thing in the world has its own two sides. The unique ID also has disadvantages: it can leak information of the network(size); processes in the system have no privacy; assign unique ID is costly in bulk-production(e.g, sensors). Hence, homonymous system is appeared. If some processes share the same ID and programmed identically is called homonymous system. Furthermore, if all processes shared the same ID or have no ID is named as anonymous system. In homonymous or anonymous distributed systems, the symmetry problem (i.e., how to distinguish messages sent from which process) is the main obstacle in the design of algorithms. This thesis is aimed to propose different symmetry break methods (e.g., random function, counting technique, etc.) to solve agreement problem. Agreement is a fundamental problem in distributed computing including a family of abstractions. In this thesis, we mainly focus on the design of consensus, set agreement, broadcast algorithms in anonymous and homonymous distributed systems. Firstly, the fault-tolerant broadcast abstraction is studied in anonymous systems with reliable or fair lossy communication channels separately. Two classes of anonymous failure detectors AΘ and AP∗ are proposed, and both of them together with a already proposed failure detector ψ are implemented and used to enrich the system model to implement broadcast abstraction. Then, in the study of the consensus abstraction, it is proved the AΩ′ failure detector class is strictly weaker than AΩ and AΩ′ is implementable. The first implementation of consensus in anonymous asynchronous distributed systems augmented with AΩ′ and where a majority of processes does not crash. Finally, a general consensus problem– k-set agreement is researched and the weakest failure detector L used to solve it, in asynchronous message passing systems where processes may crash and recover, with homonyms (i.e., processes may have equal identities), and without a complete initial knowledge of the membership.

Methodology for Dynamic Stability and Robustness Analysis of Commercial-Power-Module-Based DC-Distributed Systems

El propósito de esta tesis es presentar una metodología para realizar análisis de la dinámica en pequeña señal y el comportamiento de sistemas de alimentación distribuidos de corriente continua (CC), formados por módulos comerciales. Para ello se hace uso de un método sencillo que indica los márgenes de estabilidad menos conservadores posibles mediante un solo número. Este índice es calculado en cada una de las interfaces que componen el sistema y puede usarse para obtener un índice global que indica la estabilidad del sistema global. De esta manera se posibilita la comparación de sistemas de alimentación distribuidos en términos de robustez. La interconexión de convertidores CC-CC entre ellos y con los filtros EMI necesarios puede originar interacciones no deseadas que dan lugar a la degradación del comportamiento de los convertidores, haciendo el sistema más propenso a inestabilidades. Esta diferencia en el comportamiento se debe a interacciones entre las impedancias de los diversos elementos del sistema. En la mayoría de los casos, los sistemas de alimentación distribuida están formados por módulos comerciales cuya estructura interna es desconocida. Por ello los análisis presentados en esta tesis se basan en medidas de la respuesta en frecuencia del convertidor que pueden realizarse desde los terminales de entrada y salida del mismo. Utilizando las medidas de las impedancias de entrada y salida de los elementos del sistema, se puede construir una función de sensibilidad que proporciona los márgenes de estabilidad de las diferentes interfaces. En esta tesis se utiliza el concepto del valor máximo de la función de sensibilidad (MPC por sus siglas en inglés) para indicar los márgenes de estabilidad como un único número. Una vez que la estabilidad de todas las interfaces del sistema se han evaluado individualmente, los índices obtenidos pueden combinarse para obtener un único número con el que comparar la estabilidad de diferentes sistemas. Igualmente se han analizado las posibles interacciones en la entrada y la salida de los convertidores CC-CC, obteniéndose expresiones analíticas con las que describir en detalle los acoplamientos generados en el sistema. Los estudios analíticos realizados se han validado experimentalmente a lo largo de la tesis. El análisis presentado en esta tesis se culmina con la obtención de un índice que condensa los márgenes de estabilidad menos conservativos. También se demuestra que la robustez del sistema está asegurada si las impedancias utilizadas en la función de sensibilidad se obtienen justamente en la entrada o la salida del subsistema que está siendo analizado. Por otra parte, la tesis presenta un conjunto de parámetros internos asimilados a impedancias, junto con sus expresiones analíticas, que permiten una explicación detallada de las interacciones en el sistema. Dichas expresiones analíticas pueden obtenerse bien mediante las funciones de transferencia analíticas si se conoce la estructura interna, o utilizando medidas en frecuencia o identificación de las mismas a través de la respuesta temporal del convertidor. De acuerdo a las metodologías presentadas en esta tesis se puede predecir la estabilidad y el comportamiento de sistemas compuestos básicamente por convertidores CC-CC y filtros, cuya estructura interna es desconocida. La predicción se basa en un índice que condensa la información de los márgenes de estabilidad y que permite la obtención de un indicador de la estabilidad global de todo el sistema, permitiendo la comparación de la estabilidad de diferentes arquitecturas de sistemas de alimentación distribuidos. ABSTRACT The purpose of this thesis is to present dynamic small-signal stability and performance analysis methodology for dc-distributed systems consisting of commercial power modules. Furthermore, the objective is to introduce simple method to state the least conservative margins for robust stability as a single number. In addition, an index characterizing the overall system stability is obtained, based on which different dc-distributed systems can be compared in terms of robustness. The interconnected systems are prone to impedance-based interactions which might lead to transient-performance degradation or even instability. These systems typically are constructed using commercial converters with unknown internal structure. Therefore, the analysis presented throughout this thesis is based on frequency responses measurable from the input and output terminals. The stability margins are stated utilizing a concept of maximum peak criteria, derived from the behavior of impedance-based sensitivity function that provides a single number to state robust stability. Using this concept, the stability information at every system interface is combined to a meaningful number to state the average robustness of the system. In addition, theoretical formulas are extracted to assess source and load side interactions in order to describe detailed couplings within the system. The presented theoretical analysis methodologies are experimentally validated throughout the thesis. In this thesis, according to the presented analysis, the least conservative stability margins are provided as a single number guaranteeing robustness. It is also shown that within the interconnected system the robust stability is ensured only if the impedance-based minor-loop gain is determined at the very input or output of each subsystem. Moreover, a complete set of impedance-type internal parameters as well as the formulas according to which the interaction sensitivity can be fully explained and analyzed, is provided. The given formulation can be utilized equally either based on measured frequency responses, time-domain identified internal parameters or extracted analytic transfer functions. Based on the analysis methodologies presented in this thesis, the stability and performance of interconnected systems consisting of converters with unknown internal structure, can be predicted. Moreover, the provided concept to assess the least conservative stability margins enables to obtain an index to state the overall robust stability of distributed power architecture and thus to compare different systems in terms of stability.

On the controllability of distributed systems

To “control” a system is to make it behave (hopefully) according to our “wishes,” in a way compatible with safety and ethics, at the least possible cost. The systems considered here are distributed—i.e., governed (modeled) by partial differential equations (PDEs) of evolution. Our “wish” is to drive the system in a given time, by an adequate choice of the controls, from a given initial state to a final given state, which is the target. If this can be achieved (respectively, if we can reach any “neighborhood” of the target) the system, with the controls at our disposal, is exactly (respectively, approximately) controllable. A very general (and fuzzy) idea is that the more a system is “unstable” (chaotic, turbulent) the “simplest,” or the “cheapest,” it is to achieve exact or approximate controllability. When the PDEs are the Navier–Stokes equations, it leads to conjectures, which are presented and explained. Recent results, reported in this expository paper, essentially prove the conjectures in two space dimensions. In three space dimensions, a large number of new questions arise, some new results support (without proving) the conjectures, such as generic controllability and cases of decrease of cost of control when the instability increases. Short comments are made on models arising in climatology, thermoelasticity, non-Newtonian fluids, and molecular chemistry. The Introduction of the paper and the first part of all sections are not technical. Many open questions are mentioned in the text.

Spontaneous inflammatory demyelinating disease in transgenic mice showing central nervous system-specific expression of tumor necrosis factor alpha.

Cytokines are now recognized to play important roles in the physiology of the central nervous system (CNS) during health and disease. Tumor necrosis factor alpha (TNF-alpha) has been implicated in the pathogenesis of several human CNS disorders including multiple sclerosis, AIDS dementia, and cerebral malaria. We have generated transgenic mice that constitutively express a murine TNF-alpha transgene, under the control of its own promoter, specifically in their CNS and that spontaneously develop a chronic inflammatory demyelinating disease with 100% penetrance from around 3-8 weeks of age. High-level expression of the transgene was seen in neurons distributed throughout the brain. Disease is manifested by ataxia, seizures, and paresis and leads to early death. Histopathological analysis revealed infiltration of the meninges and CNS parenchyma by CD4+ and CD8+ T lymphocytes, widespread reactive astrocytosis and microgliosis, and focal demyelination. The direct action of TNF-alpha in the pathogenesis of this disease was confirmed by peripheral administration of a neutralizing anti-murine TNF-alpha antibody. This treatment completely prevented the development of neurological symptoms, T-cell infiltration into the CNS parenchyma, astrocytosis, and demyelination, and greatly reduced the severity of reactive microgliosis. These results demonstrate that overexpression of TNF-alpha in the CNS can cause abnormalities in nervous system structure and function. The disease induced in TNF-alpha transgenic mice shows clinical and histopathological features characteristic of inflammatory demyelinating CNS disorders in humans, and these mice represent a relevant in vivo model for their further study.

Retrograde axonal transport of glial cell line-derived neurotrophic factor in the adult nigrostriatal system suggests a trophic role in the adult.

The recently cloned, distant member of the transforming growth factor beta (TGF-beta) family, glial cell line-derived neurotrophic factor (GDNF), has potent trophic actions on fetal mesencephalic dopamine neurons. GDNF also has protective and restorative activity on adult mesencephalic dopaminergic neurons and potently protects motoneurons from axotomy-induced cell death. However, evidence for a role for endogenous GDNF as a target-derived trophic factor in adult midbrain dopaminergic circuits requires documentation of specific transport from the sites of synthesis in the target areas to the nerve cell bodies themselves. Here, we demonstrate that GDNF is retrogradely transported by mesencephalic dopamine neurons of the nigrostriatal pathway. The pattern of retrograde transport following intrastriatal injections indicates that there may be subpopulations of neurons that are GDNF responsive. Retrograde axonal transport of biologically active 125I-labeled GDNF was inhibited by an excess of unlabeled GDNF but not by an excess of cytochrome c. Specificity was further documented by demonstrating that another TGF-beta family member, TGF-beta 1, did not appear to affect retrograde transport. Retrograde transport was also demonstrated by immunohistochemistry by using intrastriatal injections of unlabeled GDNF. GDNF immunoreactivity was found specifically in dopamine nerve cell bodies of the substantia nigra pars compacta distributed in granules in the soma and proximal dendrites. Our data implicate a specific receptor-mediated uptake mechanism operating in the adult. Taken together, the present findings suggest that GDNF acts endogenously as a target-derived physiological survival/maintenance factor for dopaminergic neurons.

Fault location in power distribution networks with distributed generation.

This research presents the development and implementation of fault location algorithms in power distribution networks with distributed generation units installed along their feeders. The proposed algorithms are capable of locating the fault based on voltage and current signals recorded by intelligent electronic devices installed at the end of the feeder sections, information to compute the loads connected to these feeders and their electric characteristics, and the operating status of the network. In addition, this work presents the study of analytical models of distributed generation and load technologies that could contribute to the performance of the proposed fault location algorithms. The validation of the algorithms was based on computer simulations using network models implemented in ATP, whereas the algorithms were implemented in MATLAB.