DC power systems are gaining an increasing interest in renewable energy applications because of the good matching with dc output type sources such as photovoltaic (PV) systems and secondary batteries. In this paper, several distributed generators (DGs) have been merged together with a pair of batteries and loads to form an autonomous dc Microgrid (MG). To overcome the control challenge associated with coordination of multiple batteries within one stand-alone MG, a double-layer hierarchical control strategy was proposed; 1) The unit-level primary control layer was established by an adaptive voltage-droop (VD) method aimed to regulate the common bus voltage and to sustain the states of charge (SOCs) of batteries close to each other during moderate replenishment. The control of every unit was expanded with unit-specific algorithm, i.e. finish-of-charging for batteries and maximum power point tracking (MPPT) for renewable energy sources (RESs), with which a smooth on-line overlap was designed; 2) the supervisory control layer was designed to use the low bandwidth communication interface between the central controller and sources in order to collect data needed for adaptive calculation of virtual resistances (VRs) as well as transit criteria for changing unit-level operating modes. A smallsignal stability for the whole range of VRs. The performance of developed control was assessed through experimental results.

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Changes in the electricity business environment, dictated mostly by the increasing integration of renewable energy sources characterised by variable and uncertain generation, create new challenges especially in the liberalised market environment. The role of energy storage systems (ESS) is recognised as a mean to provide additional system security, reliability and flexibility to respond to changes that are still difficult to accurately forecast. However, there are still open questions about benefits these units bring to the generation side, system operators and the consumers. This study provides a comprehensive overview of the current research on ESS allocation (ESS sizing and siting), giving a unique insight into issues and challenges of integrating ESS into distribution networks and thus giving framework guidelines for future ESS research.

Abstract-This paper describes a robust optimization approach to minimize the total cost of supplying a remote telecommunication station exclusively by renewable energy sources (RES). Due to intermittent nature of RES, such as photovoltaic (PV) panels and small wind turbines, they are normally supported by a central energy storage system (ESS), consisting of a battery and a fuel cell. The optimization is carried out as a robust mixed-integer linear program (RMILP), and results in different optimal solutions, depending on budgets of uncertainty, each of which yields different RES and storage capacities. These solutions are then tested against a set of possible outcomes, thus simulating the future operation of the system. Since battery cycling is inevitable in this application, an algorithm that counts the number of cycles and associated depths of discharges (DoD) is applied to the optimization results. The annual capacity reduction that results from these cycles is calculated for two types of battery technologies, i.e. valve-regulated lead-acid (VRLA) and lithium-ion (Li-Ion), and treated as an additional cost. Finally, all associated costs are added up and the ideal configuration is proposed.Index Terms-Autonomous power facility, batteries, energy storage system, renewable energy sources, robust mixed-integer linear programming. (t) electricity discharged form the battery (kW), NOMENCLATUREwind turbine generation (kW),curtailed RES output, n hyd number of hydrogen storage replacements,consumed hydrogen (l), x ch bat (t) binary variable equal to 1 if battery is being charged at time period t, and 0 otherwise, x dis bat (t) binary variable equal to 1 if battery is being discharged at time period t, and 0 otherwise.

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