Decentralised control of DC microgrid based on virtual admittance to enhance DC voltage and grid frequency support

DC microgrid technology has become one of key smart grid research topics in recent years. In comparison to AC microgrids, DC microgrids are more manageable to operate in grid-connected and islanded modes, and also offering improved efficiency and better controllability. Services, such as voltages and AC system frequency support can also be potentially provided by optimally controlling the DC microgrids converter interfaces and their local distributed energy resources. These will require a good understanding of the dynamic interactions between the DC microgrid and the host AC system, and implementation of the appropriate control strategies. This paper investigates the dynamic resilience of a DC microgrid connected to an AC system under different frequency and voltage disturbances. A decentralised droop control strategy within the DC microgrid is used for fast active power control and wider system frequency support. A virtual admittance method is also utilised to enhance the local DC microgrid voltages during the AC frequency events and DC fault test scenarios. The effectiveness of the control strategy is evaluated by simulation studies in MATLAB/Simulink

Research trends on microgrid systems: a bibliometric network analysis

The numeral of academic publications in the microgrid system field has rapidly grown. A microgrid system is a group of interconnected distributed generation, loads, and energy storage operating as a single controllable entity. Many published articles recently focused on distributed generation, system control, system stability, power quality, architectures, and broader focus areas. This work analyzes microgrid: alternating current (AC), direct current (DC), and hybrid AC/DC microgrid systems with bibliometric network analysis through descriptive analysis, authors analysis, sources analysis, words analysis, and evolutionary path based on the Scopus database between 2010 and 2021. The finding helps find out the top authors and most impact sources, most relevant and frequently used in the research title, abstract, and keyword, graphically mapping the research evolved and identifying trend topic

Intelligent power sharing of DC isolated microgrid based on fuzzy sliding mode droop control

Linear droop control can realize power sharing among generators in dc microgrid (MG) without relying on critical communication links. However, the droop relationship between output power and voltage magnitude of renewable power generate system is nonlinear with uncertainties and disturbances from renewable sources and loads in practical dc MG. A novel droop scheme is proposed for an isolated dc MG to solve the nonlinear problem. The control strategy is proposed by using the Takagi-Sugeno (T-S) fuzzy model and sliding mode algorithm. The nonlinear droop characteristics can be represented by T-S model through taking advantage of locally measured output variables. The sliding mode droop controller is designed for compensating the uncertainties and disturbances to derive accurate power sharing based on T-S fuzzy model. The proposed scheme is proved to be effective under variable operating conditions through PSIM/MATLAB simulation

Proactive Monitoring, Anomaly Detection, and Forecasting of Solar Photovoltaic Systems Using Artificial Neural Networks

The world of energy sustainability landscape is witnessing high proliferation of smartgrids and microgrids, it has become significant to use intelligent tools to design, operate and maintain such crucial systems in our lives. Solar energy is an intermittent source and purely Photovoltaic (PV) based, or PV and storage based smartgrids require characterization and modelling of PV resources for an effective planning and effective operations. This dissertation familiarizes briefly the existing tools for design, monitoring, forecasting and operation of a solar system in smart electric grids infrastructure and proposes a unique application-based infrastructure to monitor, operate, forecast and troubleshoot a working PV of a smartgrid. A resilient smartgrid communication is proposed which enables monitoring and control of different elements in any PV system. This communication architecture is used to facilitate a feedback-oriented monitoring of different elements in a microgrid ecosystem and investigated thoroughly. This integrated architecture which is a combination of sensors, network elements, database and computation elements is designed specifically for solar photovoltaic (PV) powered grids on modular basis. Apart from this, the network resilience and redundancy for smooth and loss less communication is another characteristic factor in this research work. Subsequently, a deep neural network algorithm is developed to diagnose the underperformance in the generation of a PV system connected to a smartgrid. As PV generation is predominantly dependent on climatic parameters, it is necessary to have a mechanism for understanding and diagnosing performance of the system at any given instance. To address this challenge, this deep neural network architecture is presented for instantaneous performance diagnosis. The proposed architecture enabled modeling and diagnose of soiling and partial shade conditions prevalent with an accuracy of 90+%. Features of monitoring and regulating the generation and demand side of the grid were integrated through network along with feedback-based measures for effective performance in the PV system of a smartgrid or microgrid using the same network. The novelty in this work lies in real-time calculation of ideal performance and comparison for diagnosing critical performance issues of solar power generation like soiling and partial shading. Furthermore, long-short term memory (LSTM), which is a recurrent neural network model, is created for forecasting the PV solar resources, in which can assist in quantifying PV generation in various time intervals (hourly, daily, weekly). PV based smartgrids often experience expensive or inaccurate resources planning due to the lack of accurate forecasting tools where the projected methodology would eliminate such losses. This research work in its whole provides a different proposition of vertical integration which can transform into a new concept called Internet of Microgrid (IoMG). Planning, monitoring and operation form the core of smartgrids administration and if intelligent tools intertwined with network are being used as integral part in each of these aspects, then it forms a holistic view of smartgrids