Direct current (DC) microgrids (MG) constitute a research field that has gained great attention over the past few years, challenging the well-established dominance of their alternating current (AC) counterparts in Low Voltage (LV) (up to 1.5 kV) as well as Medium Voltage (MV) applications (up to 50 kV). The main reasons behind this change are: (i) the ascending amalgamation of Renewable Energy Sources (RES) and Battery Energy Storage Systems (BESS), which predominantly supply DC power to the energy mix that meets electrical power demand and (ii) the ascending use of electronic loads and other DC-powered devices by the end-users. In this sense, DC distribution provides a more efficient interface between the majority of Distributed Energy Resources (DER) and part of the total load of a MG. The early adopters of DC MGs include mostly buildings with high RES production, ships, data centers, electric vehicle (EV) charging stations and traction systems. However, the lack of expertise and the insufficient standards’ framework inhibit their wider spread. This review paper presents the state of the art of LV and MV DC MGs in terms of advantages/disadvantages over their AC counterparts, their interface with the AC main grid, topologies, control, applications, ancillary services and standardization issues. Overall, the aim of this review is to highlight the possibilities provided by DC MG architectures as well as the necessity for a solid/inclusive regulatory framework, which is their main weakness.

This paper presents a day ahead optimal dispatch method for smart grids including two-axis tracking photovoltaic (PV) panels, wind turbines (WT), a battery energy storage system (BESS) and electric vehicles (EV), which serve as additional storage systems in vehicle to grid (V2G) mode. The aim of the day ahead schedule is the minimization of fuel-based energy, imported from the main grid. The feasibility of the proposed method lies on the extensive communication network of the smart grids, including sensors and metering devices, that provide valuable information regarding the production of the distributed energy resources (DER), the energy consumption and the behavior of EV users. The day ahead optimal dispatch method is applied on a smart grid in order to showcase its effectiveness in terms of sustainability, full exploitation of DER production and ability of EVs to act as prosumers.

The increase of distributed energy resources (DERs) in low voltage (LV) distribution networks requires the ability to perform an accurate power flow analysis (PFA) in unbalanced systems. The characteristics of a well performing power flow algorithm are the production of accurate results, robustness and quick convergence. The current study proposes an improvement to an already used backward-forward sweep (BFS) power flow algorithm for unbalanced three-phase distribution networks. The proposed power flow algorithm can be implemented in large systems producing accurate results in a small amount of time using as little computational resources as possible. In this version of the algorithm, the network is represented in a tree-like structure, instead of an incidence matrix, avoiding the use of redundant computations and the storing of unnecessary data. An implementation of the method was developed in Python programming language and tested for 3 IEEE feeder test cases (the 4 bus feeder, the 13 bus feeder and the European Low Voltage test feeder), ranging from a low (4) to a very high (907) buses number, while including a wide variety of components witnessed in LV distribution networks.

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