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In the recently deregulated power system scenario, the growing number of distributed generation sources should be considered as an opportunity to improve stability and power quality along the grid. To make progress in this direction, this work proposes a reactive current injection control scheme for distributed inverters under voltage sags. During the sag, the inverter injects, at least, the minimum amount of reactive current required by the grid code. The flexible reactive power injection ensures that one phase current is maintained at its maximum rated value, providing maximum support to the most faulted phase voltage. In addition, active power curtailment occurs only to satisfy the grid code reactive current requirements. As well as, a voltage control loop is implemented to avoid overvoltage in non‐faulty phases, which otherwise would probably occur due to the injection of reactive current into an inductive grid. The controller is proposed for low‐power rating distributed inverters where conventional voltage support provided by large power plants is not available. The implementation of the controller provides a low computational burden because conventional PI‐based control loops may apply. Selected experimental results are reported in order to validate the effectiveness of the proposed control scheme.

This paper proposes an effective dc voltage and power-sharing control structure for multiterminal dc (MTDC) grids based on an optimal power flow (OPF) procedure and voltage-droop control implemented in the different hierarchical layers. In the proposed approach, an OPF algorithm is executed at the secondary control level of the MTDC grid to find the optimal reference values for the dc voltages and active power of the voltage-regulating converters. Then, at the primary control level, the voltage-droop characteristics of the voltage-regulating converters are tuned based upon the OPF results. In this control structure, the optimally-tuned voltage-droop controllers lead to the optimal operation of the MTDC grid. In case of variation in load or generation of the grid, a new stable operating point is achieved based on the voltage-droop characteristics. Then by executing a new OPF, the voltage-droop characteristics are returned for optimal operation of the MTDC grid after the load or generation variations. This paper also considers the integration of frequency support loop in the proposed control framework in case of connection of weak ac grids. The simulations performed on a study case inspired by the CIGRE B4 dc grid test system demonstrate the efficient grid performance under the proposed control strategy. Peer Reviewed

© Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ The proper sequencing and optimal loading of chillers is one of the major avenues for energy efficiency improvement in existing heating, ventilating and air conditioning installations. The main enabler for the success of such applications is the access to accurate chiller performance maps that allow to operate the equipment in optimal conditions. However, current solutions are excessively reliant on maps obtained through suboptimal means, such as manufacturer datasheets, extensive instrumentation campaigns or burdensome modelling and simulation methodologies. Furthermore, recent studies show that strategies based on model-predictive control may lead to increased savings by anticipating the future cooling demand and scheduling the operation of the chillers, selecting the optimal operation configuration and extending the remaining life by reducing switching. In this regard, this study presents a novel data-driven and multi-criteria chiller orchestration strategy that combines a chiller performance characterization stage for obtaining performance maps based on a neural network-based learning methodology and a state-of-the-art hybrid load forecasting scheme for calculating the future load profiles. The effectiveness of the proposed methodology is tested with experimental data from a multi-chiller installation in a tertiary sector building, where nearly a 20% average performance increase is achieved compared to the standard real-time controller of the HVAC installation. Peer Reviewed

Master-Slave configuration is a suitable alternative to droop control method used in microgrids. In this configuration, only one inverter is the master, while the others are slaves. The slave inverters are always current controlled whereas the master inverter should have two selectable operation modes: current controlled, when the microgrid is connected to the grid; and voltage controlled, when it is operating in island mode. In gridconnected mode, the master needs a synchronization system to perform the accurate control of its delivered power, and, in island mode, it needs a voltage reference oscillator that serves as a reference to the slave inverters. Based on the master-slave concept, this paper proposes a single system that perform both functions, i.e., it can act as a synchronization system or as a voltage reference oscillator depending on an input selector. Moreover, the system ensures a smoothly transition between the two operation modes, guaranteeing the safety operation of the microgrid. Experimental results are provided to confirm the effectiveness of the proposed system. Peer Reviewed

Today, environmental impact associated with pollution treatment is a matter of great concern. A method is proposed for evaluating environmental risk associated with Advanced Oxidation Processes (AOPs) applied to wastewater treatment. The method is based on the type of pollution (wastewater, solids, air or soil) and on materials and energy consumption. An Environmental Risk Index (E), constructed from numerical criteria provided, is presented for environmental comparison of processes and/or operations. The Operation Environmental Risk Index (EOi) for each of the unit operations involved in the process and the Aspects Environmental Risk Index (EAj) for process conditions were also estimated. Relative indexes were calculated to evaluate the risk of each operation (E/NOP) or aspect (E/NAS) involved in the process, and the percentage of the maximum achievable for each operation and aspect was found. A practical application of the method is presented for two AOPs: photo-Fenton and heterogeneous photocatalysis with suspended TiO2 in Solarbox. The results report the environmental risks associated with each process, so that AOPs tested and the operations involved with them can be compared.

Machine-to-Machine (M2M) area networks must provide connectivity between an M2M gateway and a large number of energy-constrained M2M devices. Attaining high energy efficiency is essential in order to prolong devices lifetime. In this paper, we consider a wireless M2M area network composed of hundreds or even thousands of dormant devices that wake up periodically to transmit data upon request from a gateway. We theoretically analyze the energy efficiency of a Medium Access Control (MAC) protocol that uses a tree-splitting algorithm to resolve the collisions among devices: the Distributed Queuing (DQ) access. Computer-based simulations have been carried out to validate the accuracy of the analytical model and to evaluate and compare the energy consumption of devices using also a basic Contention Tree Algorithm (CTA) and Frame Slotted-ALOHA (FSA). Results show that DQ can reduce energy consumption in more than 35% with respect to CTA and in more than 80% with respect to FSA in dense M2M area networks with devices in compliance with the IEEE 802.15.4 physical layer. Peer Reviewed