Intelligent voltage dip mitigation in power networks with distributed generation

Includes bibliographical references.The need for ensuring good power quality (PQ) cannot be over-emphasized in electrical power system operation and management. PQ problem is associated with any electrical distribution and utilization system that experiences any voltage, current or frequency deviation from normal operation. In the current power and energy scenario, voltage-related PQ disturbances like voltage dips are a fact which cannot be eliminated from electrical power systems since electrical faults, and disturbances are stochastic in nature. Voltage dip tends to lead to malfunction or shut down of costly and mandatory equipment and appliances in consumers’ systems causing significant financial losses for domestic, commercial and industrial consumers. It accounts for the disruption of both the performance and operation of sensitive electrical and electronic equipment, which reduces the efficiency and the productivity of power utilities and consumers across the globe. Voltage dips are usually experienced as a result of short duration reduction in the r.m.s. (r.m.s.- root mean square) value of the declared or nominal voltage at the power frequency and is usually followed by recovery of the voltage dip after few seconds. The IEEE recommended practice for monitoring electric power quality (IEEE Std. 1159-2009, revised version of June 2009), provides definitions to label an r.m.s. voltage disturbance based upon its duration and voltage magnitude. These disturbances can be classified into transient events such as voltage dips, swells and spikes. Other long duration r.m.s. voltage variations are mains failures, interruption, harmonic voltage distortion and steady-state overvoltages and undervoltages. This PhD research work deals with voltage dip phenomena only. Initially, the present power network was not designed to accommodate renewable distributed generation (RDG) units. The advent and deployment of RDG over recent years and high penetration of RDG has made the power network more complex and vulnerable to PQ disturbances. It is a well-known fact that the degree of newly introduced RDG has increased rapidly and growing further because of several reasons, which include the need to reduce environmental pollution and global warming caused by emission of carbon particles and greenhouse gases, alleviating transmission congestion and loss reduction. RDG ancillary services support especially voltage and reactive power support in electricity networks are currently being recognized, researched and found to be quite useful in voltage dip mitigation

Sag effects on protection system in distributed generation grids

Distributed Generators (DGs) are sensible to voltage sags, so the protection devices must trip fast to disconnect the faulted part of the grid. The DG disconnection will not be desirable in the near future with a large penetration, so it will be necessary to lay down new requirements that should be based on avoiding unnecessary disconnections. Therefore, to prevent unnecessary tripping when inverter-based DGs are connected to the Medium Voltage (MV) grid, reliable and effective protection strategies need to be developed, considering the limited short-circuit current contribution of DG. The initial goal of this study is to employ different possible control strategies for a grid-connected inverter according to the Spanish grid code and to analyze the output voltage behavior during symmetrical and unsymmetrical voltage sags. The analytical development of the proposed strategies shows the impacts of the sag on currents, voltages, active and reactive powers. Another goal of this research is to propose a protection strategy based on Artificial Intelligence for a radial or ring distribution system with high DG penetration. The protection strategy is based on three different algorithms to develop a more secure, redundant, and reliable protection system to ensure supply continuity during disturbances in ring and radial grids without compromising system stability. In order to classify, locate and distinguish between permanent or transient faults, new protection algorithms based on artificial intelligence are proposed in this research, allowing network availability improvement disconnecting only the faulted part of the system. This research introduces the innovative use of directional relay based on a communication system and Artificial Neural Network (ANN). The first algorithm, Centralize algorithm (CE), collects the data from all the PDs in the grid in the centralized controller. This algorithm detects the power flow direction and calculates the positive-sequence current of all the PDs in the grid. Significant benefits of this system are that it consolidates the entire systems security into a single device, which can facilitate system security control. However, the CE will not pinpoint the exact location of the fault if there is any loss of information due to poor communication. Therefore, the systems redundancy can be improved by cooperating with a second algorithm, the Zone algorithm (ZO). ZO algorithm is based on zone control using peer-to-peer connectivity in the same line. The faulty line in that zone may be identified by combining the two PDs data on the same line. The most relevant advantage of this algorithm is its flexibility to adapt to any grid modification or disturbance, even if they are just temporary, unlike the CE, which is fixed to the existing grid configuration. The third protection algorithm, Local algorithm (LO), has been proposed without depending on the communication between the PDs; then, the protection system can work properly in case of a total loss of communication. Each PD should be able to detect if the fault is located in the protected line or another line by using only the local information of the PD. According to the type of fault and based on local measurements at each PD of abc voltages and currents, different algorithms will be applied depending on the calculation of the sequence components. The main advantage of this algorithm is the separate decision of each PD, and avoiding communication problems. In case of radial grids, both mechanical breakers and Solid State Relays (SSRs) are used to verify the protection strategies, and in the case of ring grids, mechanical breakers are used, due to the limitations in required voltage difference of SSR. The proposed protection algorithms are compared with conventional protections (Overcurrent and Differential) protections to validate the contribution of the proposed algorithms, especially in reconfigurable smart grids.El objetivo inicial de este estudio es emplear diferentes estrategias de control posibles para un inversor conectado a la red segun el código de red español y analizar el comportamiento de la tensión de salida durante caídas de tensión simétricas y asimétricas. El desarrollo analítico de las estrategias propuestas muestra los impactos de los huecos de tensión en las corrientes, tensiones, potencias activas y reactivas. Otro objetivo de esta investigación es proponer una estrategia de protecclón basada en lnteligencia Artificial para una red del Sistema de Distribución, radial o en anillo, con elevada penetración de Generación Distribuida. La estrategia de protección se basa en tres algoritmos diferentes para desarrollar un sistema de protección más seguro, redundante, y fiable, que asegure la continuidad de suministro durante perturbaciones en redes radiales o en anillo sin comprometer la estabilidad del sistema. Para clasificar, localizar y distinguir entre faltas permanentes o transitorias, se proponen en este trabajo nuevos algoritmos de protección basados en inteligencia artificial, permitiendo la mejora de la disponibilidad de la red, al desconectar sólo la parte del sistema en falta. Esta investigación introduce la innovación del uso del rele direccional basado en un sistema de comunicación y Redes Neuronales Artificiales (ANN). El primer algoritmo, Algoritmo Central (CE), recibe los datos de todos los PDs de la red en un control central. Este algoritmo detecta la dirección de flujo de cargas y calcula la corriente de secuencia positiva de todos los PDs de la red. El entrenamiento de ANNs incluye variaciones en la corriente de cortocircuito y la dirección del flujo de potencia en cada PD. Los beneficios mas significativos de este sistema son que concentra la seguridad total del sistema en un único dispositivo, lo que puede facilitar el control de la seguridad del sistema. Sin embargo, el CE no determinara con precisión la localización exacta de la falta si hay alguna perdida de información debida a una pobre comunicación. Por lo tanto, la redundancia del sistema se puede mejorar cooperando con un segundo algoritmo, el algoritmo de Zona (ZO). El algoritmo ZO se basa en un control de zona usando la conectividad entre dispositivos de protección de una misma línea. La línea en falta en esa zona puede identificarse combinando los datos de los dos PDs de la misma línea.. La ventaja mas relevante de este algoritmo es su flexibilidad para adaptarse a cualquier modificación de la red o perturbación, incluso si sólo son temporales, a diferencia del CE, que se ha adaptado para la configuración de la red existente. El tercer algoritmo de protección, algoritmo Local (LO), ha sido propuesto sin dependencia de la comunicación entre PDs; por lo tanto, el sistema de protección puede operar correctamente en el caso de una pérdida total de comunicación. Cada PD debe poder detectar si la falta esta ubicada en la línea protegida o en otra línea, utilizando sóIo la información local del PD. Según el tipo de falta, y en base a medidas locales en cada PD, de tensiones y corrientes abc, se aplican diferentes algoritmos en función del cálculo de las componentes simétricas. La principal ventaja de este algoritmo es la actuación por separado de cada PD, evitando los problemas de comunicación. En el caso de las redes radiales, se utilizan tanto interruptores mecánicos como réles de estado sóIido (SSR) para verificar las estrategias de protección, y en el caso de las redes en anillo se utilizan interruptores mecánicos, debido a las limitaciones de tensión para su conexión. Los algoritmos de protección propuestos se comparan con protecciones convencionales (Sobrecorriente y Diferencial) para validar la contribución de los algoritmos propuestos, especialmente en redes inteligentes reconfigurables.Postprint (published version

AI Applications to Power Systems

Today, the flow of electricity is bidirectional, and not all electricity is centrally produced in large power plants. With the growing emergence of prosumers and microgrids, the amount of electricity produced by sources other than large, traditional power plants is ever-increasing. These alternative sources include photovoltaic (PV), wind turbine (WT), geothermal, and biomass renewable generation plants. Some renewable energy resources (solar PV and wind turbine generation) are highly dependent on natural processes and parameters (wind speed, wind direction, temperature, solar irradiation, humidity, etc.). Thus, the outputs are so stochastic in nature. New data-science-inspired real-time solutions are needed in order to co-develop digital twins of large intermittent renewable plants whose services can be globally delivered

Modeling and Integration of Demand Response and Demand Side Resources for Smart Grid Application in Distribution Systems

Today\u27s electric grid is undergoing drastic changes to evolve into a smart grid. Deregulation of the integrated and monopolistic power system into genco, transco and disco has led to tremendous competition among these players. These entities are in the process of developing innovative smart grid strategies that can improve their reliability and profit. In this thesis work, some of the smart grid initiatives by discos have been explored.;This thesis work is driven by two major objectives. The primary objective is to explore Demand Response (DR), develop its comprehensive model and to analyze various effects and implications of DR on distribution networks. The second major objective of the thesis is to integrate the developed demand response model into a microgrid market optimization. A microgrid network is a real world demonstration of smart grid that integrates and coordinates various demand side resources into its operation. For this reason, a microgrid has been chosen in this work so that it offers a broader scope where in addition to DR models, Battery Energy Storage System (BESS) and Distributed Energy Resources (DER) or Distributed Generation (DG) can also be modeled and integrated.;This thesis develops a model for DR by utilizing consumer behavior modeling considering different scenarios and levels of consumer rationality. Consumer behavior modeling has been done by developing extensive demand-price elasticity matrices for different types of consumers. These Price Elasticity Matrices (PEMs) are utilized to calculate the level of demand response for a given consumer. DR thus obtained is applied to a real world distribution network considering a day-ahead real time pricing scenario to study the effects of demand reduction and redistribution on system voltage and losses. Results show considerable boost in system voltage that paves way for further demand curtailment through demand side management techniques like Volt/Var Control (VVC).;Following this, the thesis develops a market optimization model for an islanded microgrid that includes Smart Grid elements namely DR, DERs and BESS. Comprehensive models for DR and BESS have been developed and integrated into the optimization program. Demand Side Bidding (DSB) by DR Aggregators is introduced into the proposed double sided microgrid energy market by utilizing the DR models developed. The optimization program uses Linear Programming (LP) technique to determine the dispatch schedule of DERs, BESS and the level of DR to minimize the operating cost of the microgrid market. A time series simulation of a large microgrid test system is performed to show the feasibility of the proposed market optimization

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

A comprehensive review and performance evaluation in solar (PV) systems fault classification and fault detection techniques

The renewable energy industry is growing faster than ever before and in particular solar systems have significantly expanded. Abnormal conditions lead to a reduction in the maximum available power from solar (photovoltaic) systems. Thus, it is necessary to identification, detection, and monitoring of various faults in the PV system that they are the key factors to increase the efficiency, reliability, and lifetime of these systems. Up to now, faults on PV components and systems have been identified; some of them have physical damage on PV systems and some of them are electrical faults that occur on the DC side or AC side of the PV system. Here, the faults will be divided into groups based on their location of occurrence. This paper provides a comprehensive review of almost all PV system faults and fault detection techniques of PV system proposed in recent literature

Application of Power Electronics Converters in Smart Grids and Renewable Energy Systems

This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller

Reliability and Maintenance

Amid a plethora of challenges, technological advances in science and engineering are inadvertently affecting an increased spectrum of today’s modern life. Yet for all supplied products and services provided, robustness of processes, methods, and techniques is regarded as a major player in promoting safety. This book on systems reliability, which equally includes maintenance-related policies, presents fundamental reliability concepts that are applied in a number of industrial cases. Furthermore, to alleviate potential cost and time-specific bottlenecks, software engineering and systems engineering incorporate approximation models, also referred to as meta-processes, or surrogate models to reproduce a predefined set of problems aimed at enhancing safety, while minimizing detrimental outcomes to society and the environment