Microgrids (MGs) have become an integral part of smart grid initiatives for future power system networks. Networked microgrids consist of several neighbouring microgrids connected in a low/medium distribution network. The primary objective of a network is to share surplus/shortage power with neighbouring microgrids to achieve mutual cost‐effective operation, utilising green energy from renewable energy resources in the network and increasing the reliability of customer service. This article classifies networked microgrids on the basis of network formation and provides an overview of recent research on control of networked microgrids. In addition, a state‐of‐the‐art review of optimisation methods is provided to solve the energy optimisation problem in networked microgrids. Furthermore, the advantages and challenges of the networked operation of microgrids are presented as for possible research directions in the future.
Summary
Smoothing grid profile plays a crucial role in dynamic operation of microgrid. This paper focuses on reducing the grid power fluctuation in a grid connected microgrid due to stochastic nature of renewable generations and its impact on the stability and quality of distribution network. To achieve this, the control strategies are designed to control the charging/discharging of battery storage system based on the difference between generations of renewable energy resources and load demand as well a battery state. Fuzzy logic controller is applied in energy management system (EMS) of microgrid by considering dramatic behavior of renewable energy resources while maintaining battery state within secure limits. A comparison with time‐based constant and variable charge/discharge control of battery presents in simulation experiment to demonstrate the effectiveness of the proposed fuzzy controller in a residential AC microgrid.
Abstract. Communications for monitoring, control and management of microgrid are very important for smart operation. This paper analyzed the information of microgrid for monitoring, control and management purposes and maps them according to power system automation standard IEC61850. IEEE 802.11g and IEEE 802.16 standard based interoperable, cost-effective and reliable wireless communication network is proposed for real time monitoring, control and management of microgrid. Multi-agent technology is adopted to define the responsibilities of different intelligent devices. Performance analysis is carried out by modeling microgrid nodes and traffic according to IEC61850 with Optimized Network Engineering Tool (OPNET). Experimental results demonstrate the performance of the proposed network for reliable operation of microgrid in both islanded and grid connected modes.
Summary
This paper presents an interlink inverter control method for providing a constant tie‐line smoothing service in a grid‐connected residential microgrid (MG) to mitigate the fluctuating nature of renewable power generation and load demand. A grid power controller is designed for an MG to keep a constant grid power on typical days of the year by maintaining the charging/discharging of the battery. To achieve this objective, the MG controller sends the reference to the interlink inverter controller based on load dynamics, average PV generation and battery capacity. Moreover, a state‐space model is developed from the dynamic model of the MG system, and an eigenvalue‐based stability analysis is performed for different system parameters. The proposed control method is verified through extensive case studies by using real irradiance and typical residential customer load data in Queensland, Australia. In addition, a comparison with a dynamic energy management‐based method that aims to achieve the same objective is presented to demonstrate the performance of the proposed control method. Results show that the proposed method provides a constant tie‐line power for a grid‐connected residential MG for typical days of the year.
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