11 research outputs found

    Estratégia de Controle Cooperativo em Unidades de Geração Distribuídas Integrada a Sistemas de Armazenamento de Energia Elétrica / Cooperative Control Strategy in Distributed Generation Units Distributed Generation Units Integrated with Power Storage Systems

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    O aumento do nível de penetração de fontes re[1]nováveis conectadas a rede elétrica através de conversores de potência, pode provocar instabilidades em microrredes CA devido à natureza não-despachável em potência desses sistemas. A integração de sistemas de armazenamento de energia elétrica ao inversor do gerador distribuído pode suavizar a injeção de potência no ponto de acoplamento comum (PAC), contribuindo para a estabilidade de tensão e de frequência do sistema de potência. Neste trabalho, propõe-se uma estratégia de controle cooperativo para regular a tensão do barramento CC integrada a uma estrutura de armazenamento de um sistema de geração distribuída para minimizar eventuais flutuações de tensão e de frequência no PAC. Comparações com métodos tradicionais de controle são realizados para avaliar a efetividade do método proposto. A validação da estratégia de controle é realizada por meio de resultados experimentais

    Variable Voltage Control of a Hybrid Energy Storage System for Firm Frequency Response in the UK

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    A Comprehensive Inertial Control Strategy for Hybrid AC/DC Microgrid with Distributed Generations

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    Mini/Micro-Grid Adaptive Voltage and Frequency Stability Enhancement Using Q-learning Mechanism

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    This paper develops an adaptive control method for controlling frequency and voltage of an islanded mini/micro grid (M/µG) using reinforcement learning method. Reinforcement learning (RL) is one of the branches of the machine learning, which is the main solution method of Markov decision process (MDPs). Among the several solution methods of RL, the Q-learning method is used for solving RL in this paper because it is a model-free strategy and has a simple structure. The proposed control mechanism is consisting of two main parts. The first part is a classical PID controller which is fixed tuned using Salp swarm algorithm (SSA). The second part is a Q-learning based control strategy which is consistent and updates it's characteristics according to the changes in the system continuously. Eventually, the dynamic performance of the proposed control method is evaluated in a real M/µG compared to fuzzy PID and classical PID controllers. The considered M/µG is a part of Denmark distribution system which is consist of three combined heat and power (CHP) and three WTGs. Simulation results indicate that the proposed control strategy has an excellent dynamic response compared to both intelligent and traditional controllers for damping the voltage and frequency oscillations

    Functional Analysis of the Microgrid Concept Applied to Case Studies of the Sundom Smart Grid

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    The operation of microgrids is a complex task because it involves several stakeholders and controlling a large number of different active and intelligent resources or devices. Management functions, such as frequency control or islanding, are defined in the microgrid concept, but depending on the application, some functions may not be needed. In order to analyze the required functions for network operation and visualize the interactions between the actors operating a particular microgrid, a comprehensive use case analysis is needed. This paper presents the use case modelling method applied for microgrid management from an abstract or concept level to a more practical level. By utilizing case studies, the potential entities can be detected where the development or improvement of practical solutions is necessary. The use case analysis has been conducted from top-down until test use cases by real-time simulation models. Test use cases are applied to a real distribution network model, Sundom Smart Grid, with measurement data and newly developed controllers.. The functional analysis provides valuable results when studying several microgrid functions operating in parallel and affecting each other. For example, as shown in this paper, ancillary services provided by an active customer may mean that both the active power and reactive power from customer premises are controlled at the same time by different stakeholders.© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

    Development of a Converter-Based Testing Platform and Battery Energy Storage System (BESS) Emulator for Microgrid Controller Function Evaluation

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    The microgrid has attracted increasing research attention in the last two decades. Due to the development of renewable energy resources and power electronics technologies, the future microgrid will trend to be smarter and more complicated. The microgrid controller performs a critical role in the microgrid operation, which will also become more and more sophisticated to support the future microgrid. Before final field deployment and test, the evaluation and testing of the controller is an indispensable step in the controller development, which requires a proper testing platform. However, existing simulation-based platforms have issues with potential numerical oscillation and may require huge computation resources for complex microgrid controllers. Meanwhile, field test-based controller evaluation is limited to the test conditions. Existing digital simulation-based platforms and field test-based platforms have limitations for microgrid controller testing. To provide a practical and flexible controller evaluation, a converter-based microgrid hardware testbed is designed and implemented considering the actual microgrid architecture and topology information. Compared with the digital simulation-based platforms, the developed microgrid testing platform can provide a more practical testing environment. Compared to the direct field test, the developed platform is more flexible to emulate different microgrids. As one of the key components, a converter-based battery energy storage system (BESS) emulator is proposed to complete the developed testing platform based on the testing requirements of microgrid controller functions. Meanwhile, the microgrid controller testing under different microgrid conditions is also considered. Two controllers for the microgrid with dynamic boundaries are tested to demonstrate the capability of the developed platform as well as the BESS emulator. Different testing cases are designed and tested to evaluate the controller performance under different microgrid conditions

    Demand-side management in industrial sector:A review of heavy industries

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