889 resultados para Grid integration
Resumo:
This paper proposes the use of a Modular Marx Multilevel Converter, as a solution for energy integration between an offshore Wind Farm and the power grid network. The Marx modular multilevel converter is based on the Marx generator, and solves two typical problems in this type of multilevel topologies: modularity and dc capacitor voltage balancing. This paper details the strategy for dc capacitor voltage equalization. The dynamic models of the converter and power grid are presented in order to design the converter ac output voltages and the dc capacitor voltage controller. The average current control is presented and used for power flow control, harmonics and reactive power compensation. Simulation results are presented in order to show the effectiveness of the proposed (MC)-C-3 topology.
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The increasing and intensive integration of distributed energy resources into distribution systems requires adequate methodologies to ensure a secure operation according to the smart grid paradigm. In this context, SCADA (Supervisory Control and Data Acquisition) systems are an essential infrastructure. This paper presents a conceptual design of a communication and resources management scheme based on an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). The methodology is used to support the energy resource management considering all the involved costs, power flows, and electricity prices leading to the network reconfiguration. The methodology also addresses the definition of the information access permissions of each player to each resource. The paper includes a 33-bus network used in a case study that considers an intensive use of distributed energy resources in five distinct implemented operation contexts.
Resumo:
The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. On the other hand, local storage systems can be used to separate electricity availability from instantaneous generation; therefore, the effects of forecast error in the electrical system are reduced. The effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in this paper. The study has been performed in a solar house that is able to displace a residential user?s load pattern, manage local storage and estimate forecasts of electricity generation. A series of real experiments and simulations have carried out on the house. The results of this experiments show that the use of Demand Side Management (DSM) and local storage reduces to 2% the uncertainty on the energy exchanged with the grid. In the case that the photovoltaic system would operate as a pure electricity generator feeding all generated electricity into grid, the uncertainty would raise to around 40%.
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In dieser Arbeit werden verschiedene Computermodelle, Rechenverfahren und Methoden zur Unterstützung bei der Integration großer Windleistungen in die elektrische Energieversorgung entwickelt. Das Rechenmodell zur Simulation der zeitgleich eingespeisten Windenergie erzeugt Summenganglinien von beliebig zusammengestellten Gruppen von Windenergieanlagen, basierend auf gemessenen Wind- und Leistungsdaten der nahen Vergangenheit. Dieses Modell liefert wichtige Basisdaten für die Analyse der Windenergieeinspeisung auch für zukünftige Szenarien. Für die Untersuchung der Auswirkungen von Windenergieeinspeisungen großräumiger Anlagenverbünde im Gigawattbereich werden verschiedene statistische Analysen und anschauliche Darstellungen erarbeitet. Das im Rahmen dieser Arbeit entwickelte Modell zur Berechnung der aktuell eingespeisten Windenergie aus online gemessenen Leistungsdaten repräsentativer Windparks liefert wertvolle Informationen für die Leistungs- und Frequenzregelung der Netzbetreiber. Die zugehörigen Verfahren zur Ermittlung der repräsentativen Standorte und zur Überprüfung der Repräsentativität bilden die Grundlage für eine genaue Abbildung der Windenergieeinspeisung für größere Versorgungsgebiete, basierend auf nur wenigen Leistungsmessungen an Windparks. Ein weiteres wertvolles Werkzeug für die optimale Einbindung der Windenergie in die elektrische Energieversorgung bilden die Prognosemodelle, die die kurz- bis mittelfristig zu erwartende Windenergieeinspeisung ermitteln. In dieser Arbeit werden, aufbauend auf vorangegangenen Forschungsarbeiten, zwei, auf Künstlich Neuronalen Netzen basierende Modelle vorgestellt, die den zeitlichen Verlauf der zu erwarten Windenergie für Netzregionen und Regelzonen mit Hilfe von gemessenen Leistungsdaten oder prognostizierten meteorologischen Parametern zur Verfügung stellen. Die softwaretechnische Zusammenfassung des Modells zur Berechnung der aktuell eingespeisten Windenergie und der Modelle für die Kurzzeit- und Folgetagsprognose bietet eine attraktive Komplettlösung für die Einbindung der Windenergie in die Leitwarten der Netzbetreiber. Die dabei entwickelten Schnittstellen und die modulare Struktur des Programms ermöglichen eine einfache und schnelle Implementierung in beliebige Systemumgebungen. Basierend auf der Leistungsfähigkeit der Online- und Prognosemodelle werden Betriebsführungsstrategien für zu Clustern im Gigawattbereich zusammengefasste Windparks behandelt, die eine nach ökologischen und betriebswirtschaftlichen Gesichtspunkten sowie nach Aspekten der Versorgungssicherheit optimale Einbindung der geplanten Offshore-Windparks ermöglichen sollen.
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Euroopan Unionin asettamat tavoitteet uusiutuvien energialähteiden lisäämiselle sähköntuotannossa ovat johtamassa tuulivoimalla tuotetun sähkön merkittävään kasvamiseen. Suomeenkin suunnitellaan suuria, useista kymmenistä tuulivoimaloista koostuvia tuulivoimapuistoja niin maalle kuin merelle. Tuulivoimapuiston suunnittelu on kokonaisuudessaan pitkä prosessi, johon sisältyy sähköteknisen suunnittelun lisäksi myös ympäristövaikutusten arviointiohjelma ja erinäiset lupa-asiat. Tämän diplomityön tavoitteena on kehittää menetelmiä, joiden avulla suurten tuulivoimapuistojen keskijänniteverkon teknistaloudellinen suunnittelu helpottuisi. Tuulivoimapuiston keskijänniteverkon parhaan teknistaloudellisen ratkaisun löytyminen riippuu useista muuttujista. Työssä kehitettiin laskentamallipohja, jonka avulla voidaan helposti ja nopeasti tarkastella erilaisten ratkaisuiden vaikutusta kokonaisuuteen. Tavoite on optimoida teknistaloudellisessa mielessä koko tuulivoimapuiston sisäinen keskijänniteverkko. Kehitettyä laskentamallipohjaa hyödynnettiin esimerkkiprojektina olleen tuulivoimapuiston keskijänniteverkon suunnittelussa. Mallin avulla voidaan laskea nopeasti verkon kustannukset koko pitoajalta. Kustannuslaskelmissa otetaan huomioon investointi-, häviö- ja keskeytyskustannukset.
Resumo:
The application of VSC-HVDC technology throughout the world has turned out to be an efficient solution regarding a large share of wind power in different power systems. This technology enhances the overall reliability of the grid by utilization of the active and reactive power control schemes which allows to maintain frequency and voltage on busbars of the end-consumers at the required level stated by the network operator. This master’s thesis is focused on the existing and planned wind farms as well as electric power system of the Åland Islands. The goal is to analyze the wind conditions of the islands and appropriately predict a possible production of the existing and planned wind farms with a help of WAsP software program. Further, to investigate the influence of increased wind power it is necessary to develop a simulation model of the electric grid and VSC-HVDC system in PSCAD and examine grid response to different wind power production cases with respect to the grid code requirements and ensure the stability of the power system.
Resumo:
Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.
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El objetivo de este trabajo consiste en evaluar los beneficios de la utilización de sistemas de almacenamiento de energía para incrementar el valor de un parque eólico. Debido a la naturaleza aleatoria inherente a la producción eléctrica de origen eólico, su integración en red plantea importantes problemas que suponen un reto tecnológico cada vez mayor a medida que la penetración de la energía eólica en el mix de generación aumenta. A su vez, las aplicaciones de los sistemas de almacenamiento de energía representan la oportunidad de mitigar los efectos indeseables de la producción eléctrica eólica. Los conocimientos adquiridos a lo largo de este proyecto se aplicarán para determinar qué sistema de almacenamiento de energía es óptimo para implantar en el parque eólico objeto del estudio, así como para cuantificar los beneficios derivados de la hibridación. ABSTRACT The aim of this work consist of assess the benefits of the use of energy storage systems for wind farm value enhacement. Due to the random nature inherent to wind electric generation, its grid integration carry important issues that represent a technology challenge that increases as wind generation penetration within energy mix increases as well. At the same time, energy storage systems applications represent an opportunity to mitigate the undesirable effects of wind generation. The knowledge gained throughout this project will be applied to determine which energy storage system is ideally suited for implementation within the wind farm under study, as well as quantify the benefits of hybridization.
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Marine Renewable Energy Conversion systems comprise wave energy and tidal stream converters as well as offshore-wind turbines for electrical generation. These technologies are currently at different stages of development but are mostly at the pre-commercial stage and require research to be undertaken at a series of scales along the path to commercialization. However each of these technologies also needs specific research infrastructures in order to conduct this research. The aim of the MARINET initiative is to coordinate research and development at all scales (small models through to prototype scales, from laboratories through to open sea tests) and to allow access for researchers and developers to infrastructures which are not available universally in Europe, including test facilities for components such as power take-off systems, grid integration, moorings and environmental monitoring so as to ensure a focusing of activities in this area. The initiative offers researchers and developers access to 45 research facilities as well as to the associated network of expertise at all scales in Offshore Marine Renewable Energy technology research and development. The aim of this paper is to present this MARINET initiative that was started in 2011, bringing together a network of 29 partners spread across twelve countries. Details of the MARINET Transnational Access (TA) program are presented, for which over 260 applications were received throughout the 5 official calls for proposals. In particular, statistics on applications and completed projects are presented which provide an overview of the global development progress of the different offshore renewable energy conversion technologies at a European level. It also provides a good overview of the current research activity, as well as evidence of the requirement for specialised research facilities, in this burgeoning field.
Resumo:
Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.
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This paper highlights the challenges of satellite monitoring systems integration, in particular based on Grid platform, and reviews possible solutions for these problems. We describe integration issues on different levels: data integration level and task management level (job submission in terms of Grid). We show example of described technologies for integration of monitoring systems of Ukraine (National Space Agency of Ukraine, NASU) and Russia (Space Research Institute RAS, IKI RAN). Another example refers to the development of InterGrid infrastructure that integrates several regional and national Grid systems: Ukrainian Academician Grid (with Satellite data processing Grid segment) and RSGS Grid (Chinese Academy of Sciences).
Resumo:
This paper reports on design of digital control for wind turbines and its relation to the quality of power fed into the Brazilian grid on connecting to it a 192 MW wind farm equipped with doubly fed induction generators. PWM converters are deployed as vector controlled regulated current voltage sources for their rotors, for independent control of both active and reactive power of those generators. Both speed control and active power control strategies are analyzed, in the search for maximum efficiency of conversion of wind kinetic energy into electric power and enhanced quality of delivered power. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.
Using demand response to deal with unexpected low wind power generation in the context of smart grid
Resumo:
Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).
Resumo:
Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.