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.2 of 25 highly stable, even in the case of low quality distribution grids [8]. When the distribution grid fails, the microgrid must regulate the DC bus voltage without the ILC. Some control methods have been developed and proposed in the literature [9][10][11] for reaching this goal. The typical objectives of the DC microgrid in grid-connected mode are: to minimize the cost of the imported energy from the main grid, to optimize the power dispatch among the converters and the DC bus and to regulate the DC bus voltage [12]. For the optimization of the power dispatch, communications between the devices of the MG and the grid operator are necessary [13,14].Regarding the control system, one of the main challenges in MGs is how to maintain the generation and consumption energy balance [15]. Power imbalance is a common scenario in MGs, which is caused by the discontinuous power generation availability caused in turn by the intermittent nature of renewables and the variable power demand of the loads connected to the MG, among other factors. These imbalances should be managed fast, safely and effectively by the MG control in order to avoid electrical transients, which can damage or destabilize the system [6][7][8]. Therefore, proper power management control strategies have been developed. These strategies are aimed mainly at: (i) controlling the connected DGs and energy storage system, (ii) regulating the DC bus voltage, (iii) optimizing the power dispatch between DC/DC converters and the DC bus voltage to minimize the cost of imported energy from the main grid, (iv) managing and optimizing the ESS operation, and (v) managing current sharing between parallel converters [16,17]. At present, the major control strategies to maintain power balance in DC microgrids are the well-known droop control methods [14][15][16][17][18], which don't require any communication infrastructure, or other solutions using communications [2...

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In this paper, a centralized control strategy for the efficient power management of power converters composing a hybrid AC/DC microgrid is explained. The study is focused on the converters connected to the DC bus. The proposed power management algorithm is implemented in a microgrid central processor which is based on assigning several operation functions to each of the generators, loads and energy storage systems in the microgrid. The power flows between the DC and AC buses are studied in several operational scenarios to verify the proposed control. Experimental and simulation results demonstrate that the algorithm allows control of the power dispatch inside the microgrid properly by performing the following tasks: communication among power converters, the grid operator and loads; connection and disconnection of loads; control of the power exchange between the distributed generators and the energy storage system and, finally, supervision of the power dispatch limit set by the grid operator.

Microgrids are moving towards large-scale smart distributed networks which demand an efficient and reliable communication infrastructure to manage, control and monitor energy resources. With regard to this, publisher/subscriber event-based middleware has become relevant for large-scale distributed time applications because it allows decouple time and space between senders and receivers. Particularly the content publish/subscribe systems over structured peer-to-peer (P2P) networks has emerged to enhance scalability and dynamism of notification middleware systems. However, this type of systems use multicast routing schemes that still generate much network traffic and as a consequence an overload of the communication channel is produced. This results in inefficient network utilization and rapid depletion of network resources leading to unreliable operations, degradation of system performance and even instability of the microgrid. In this paper, a new contentbased publish/subscribe notification middleware over structured P2P systems is proposed, such that smart microgrid communication requirements are met. This proposed system organizes the publications and subscriptions in a one dimensional representation using the Hilbert space filling curve. Through this representation, an innovative routing and matching algorithms are developed. Experimental results demonstrate that the proposed publisher/subscribe system significantly enhance efficiency of the system, network performance and the use of computational resources.

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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.