924 research outputs found

    Electric Power Conversion and Micro-Grids

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    This edited volume is a collection of reviewed and relevant research chapters offering a comprehensive overview of recent achievements in the field of micro-grids and electric power conversion. The book comprises single chapters authored by various researchers and is edited by a group of experts in such research areas. All chapters are complete in themselves but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on electric power conversion, micro-grids, and their up-to-the-minute technological advances and opens new possible research paths for further novel developments

    Primary control of a microgrid operating in islanded mode

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    This study focuses in the primary frequency control of a generic microgrid. This microgrid consists of a Photovoltaic (PV), an Energy Storage System (ESS), a battery and a Diesel Generator (DG) which account for the majority of systems installed today, specially in remote areas, such as islands.This thesis addresses the development of the primary frequency control of the microgrid. The battery’s convertor is operated as a grid forming and it’s connected in parallel with the diesel generator. The PV’s converter is operated as a grid feeding. The control is handed as a distributed approach between the different elements of the system. Through this work, this control is analysed, through a simulation model implemented in PLECS® which is a Matlab blockset. The simulation model developed shows the operation of the control droop in different operating conditions, such as load and generation changes

    Management of Islanded Operation of Microgirds

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    Distributed generations with continuously growing penetration levels offer potential solutions to energy security and reliability with minimum environmental impacts. Distributed Generations when connected to the area electric power systems provide numerous advantages. However, grid integration of distributed generations presents several technical challenges which has forced the systems planners and operators to account for the repercussions on the distribution feeders which are no longer passive in the presence of distributed generations. Grid integration of distributed generations requires accurate and reliable islanding detection methodology for secure system operation. Two distributed generation islanding detection methodologies are proposed in this dissertation. First, a passive islanding detection technique for grid-connected distributed generations based on parallel decision trees is proposed. The proposed approach relies on capturing the underlying signature of a wide variety of system events on a set of critical system parameters and utilizes multiple optimal decision tress in a parallel network for classification of system events. Second, a hybrid islanding detection method for grid-connected inverter based distributed generations combining decision trees and Sandia frequency shift method is also proposed. The proposed method combines passive and active islanding detection techniques to aggregate their individual advantages and reduce or eliminate their drawbacks. In smart grid paradigm, microgrids are the enabling engine for systematic integration of distributed generations with the utility grid. A systematic approach for controlled islanding of grid-connected microgrids is also proposed in this dissertation. The objective of the proposed approach is to develop an adaptive controlled islanding methodology to be implemented as a preventive control component in emergency control strategy for microgrid operations. An emergency power management strategy for microgrid autonomous operation subsequent to inadvertent islanding events is also proposed in this dissertation. The proposed approach integrates microgrid resources such as energy storage systems, demand response resources, and controllable micro-sources to layout a comprehensive power management strategy for ensuring secure and stable microgrid operation following an unplanned islanding event. In this dissertation, various case studies are presented to validate the proposed methods. The simulation results demonstrate the effectiveness of the proposed methodologies

    Techniques for a Wind Energy System Integration with an Islanded Microgrid

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    This paper presents two different techniques of a wind energy conversion system (WECS) integration with an islanded microgrid (MG). The islanded microgrid operates in a frequency droop control where its frequency can vary around 50 Hz. The permanent magnet synchronous generator (PMSG) based variable speed WECS is considered, which converts wind energy to a low frequency ac power. Therefore it needs to be connected to the microgrid through a back to back (B2B) converter system. One way of interconnection is to synchronize the MG side converter with the MG bus at which it is connected. In this case, this converter runs at the MG frequency. The other approach is to bring back the MG frequency to 50 Hz using the isochronization concept. In this case, the MG side converter operates at 50 Hz. Both these techniques are developed in this paper. The proposed techniques are validated through extensive PSCAD/EMTDC simulation studies

    Smart Microgrids: Overview and Outlook

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    The idea of changing our energy system from a hierarchical design into a set of nearly independent microgrids becomes feasible with the availability of small renewable energy generators. The smart microgrid concept comes with several challenges in research and engineering targeting load balancing, pricing, consumer integration and home automation. In this paper we first provide an overview on these challenges and present approaches that target the problems identified. While there exist promising algorithms for the particular field, we see a missing integration which specifically targets smart microgrids. Therefore, we propose an architecture that integrates the presented approaches and defines interfaces between the identified components such as generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid Worksho

    Adaptive Energy Storage System Control for Microgrid Stability Enhancement

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    Microgrids are local power systems of different sizes located inside the distribution systems. Each microgrid contains a group of interconnected loads and distributed energy resources that acts as a single controllable entity with respect to the grid. Their islanding operation capabilities during emergencies improve the resiliency and reliability of the electric energy supply. Due to its low kinetic energy storage capacity, maintaining microgrid stability is challenging under system contingencies and unpredictable power generation from renewable resources. This dissertation highlights the potential benefits of flexibly utilizing the battery energy storage systems to enhance the stability of microgrids. The main contribution of this research consists in the development of a storage converter controller with an additional stability margin that enables it to improve microgrid frequency and voltage regulation as well as its induction motor post-fault speed recovery. This new autonomous control technique is implemented by adaptively setting the converter controller parameters based on its estimated phase-locked loop frequency deviation and terminal voltage magnitude measurement. This work also assists in the microgrid design process by determining the normalized minimum storage converter sizing under a wide range of microgrid motor inertia, loading and fault clearing time with both symmetrical and asymmetrical fault types. This study evaluates the expandability of the proposed control methodologies under an unbalanced meshed microgrid with fault-induced feeder switching and multiple contingencies in addition to random power output from renewable generators. The favorable results demonstrate the robust storage converter controller performance under a dynamic changing microgrid environment
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