Microgrids are moving toward electric power systems in a sort of an internet of energy (IoE) where a large number of generators can be connected anywhere. In this regard, to realize the envisioned IoE, information and communication technologies (ICT) are crucial for developing innovative applications and services as well as achieving high levels of efficiency in microgrids. However, due to the variety of ICT, there is not a de facto standard solution to implement IoE platforms. Moreover, standards for the current Internet of Things (IoT) platforms are not optimal for developing IoE platforms, which present more demanding challenges. In such context, this paper presents an embedded IoE platform for management of smart microgrids. The performance of this platform has been tested in an experimental microgrid. Results show that the proposed platform fulfills the microgrids requirements and it is able to manage the energy flows, the safety issues, etc. in microgrids.

Peer-to-Peer (P2P) overlay communications networks have emerged as a new paradigm for implementing distributed services in microgrids due to their potential benefits: they are robust, scalable, fault-tolerant, and they can route messages even when a large number of nodes are frequently entering or leaving the network. However, current P2P systems have been mainly developed for file sharing or cycle sharing applications where the processes of searching and managing resources are not optimized. Locality algorithms have gained a lot of attention due to their potential to provide an optimized path to groups with similar interests for routing messages in order to achieve better network performance. This paper develops a fully functional decentralized communication architecture with a new P2P locality algorithm and a specific protocol for monitoring and control of microgrids. Experimental results show that the proposed locality algorithm reduces the number of lookup messages and the lookup delay time. Moreover, the proposed communication architecture heavily depends of the lookup used algorithm as well as the placement of the communication layers within the architecture. Experimental results will show that the proposed techniques meet the network requirements of smart microgrids, even with a large number of nodes on stream.

The results concerning the integration of a set of power management strategies and serial communications for the efficient coordination of the power converters composing an experimental DC microgrid is presented. The DC microgrid operates in grid connected mode by means of an interlinking converter. The overall control is carried out by means of a centralized microgrid controller implemented on a Texas Instruments TMS320F28335 DSP. The main objectives of the applied control strategies are to ensure the extract/inject power limits established by the grid operator as well as the renewable generation limits if it is required; to devise a realistic charging procedure of the energy storage batteries as a function of the microgrid status; to manage sudden changes of the available power from the photovoltaic energy sources, of the load power demand and of the power references established by the central controller; and to implement a load shedding functionality. The experimental results demonstrate that the proposed power management methodology allows the control of the power dispatch inside the DC microgrid properly.

In order to integrate a large number of distributed energy resources in distribution grids a robust decentralized information and communication control structure is required. This paper proposes an overlay peer-to-peer (P2P) architecture for controlling and monitoring microgrids in real time, which has a great capacity of adaptation to the demanding network requirements of these environments. The proposed concept has been implemented and experimentally tested on a microgrid. Real data analysis demonstrates that the system meets with the network performance parameters proposed for microgrids, such as latency and bandwidth, showing that peer-to-peer overlay networks are useful for energy grids in practice.

This study is focused on two areas: the design of a Battery Energy Storage System (BESS) for a grid-connected DC Microgrid and the power management of that microgrid. The power management is performed by a Microgrid Central Controller (MGCC). A Microgrid operator provides daily information to the MGCC about the photovoltaic generation profile, the load demand profile, and the real-time prices of the electricity in order to plan the power interchange between the BESS and the main grid, establishing the desired state of charge (SOC) of the batteries at any time. The main goals of the power management strategy under study are to minimize the cost of the electricity that is imported from the grid and to maximize battery life by means of an adequate charging procedure, which sets the charging rate as a function of the MG state. Experimental and simulation results in many realistic scenarios demonstrate that the proposed methodology achieves a proper power management of the DC microgrid.