Salvador Segui-Chilet

Objective: The objective of this paper is to explore technology trends and prospects for efficient energy management in microgrids by identifying and analyzing distinct research lines in this field. Method: A Scopus search was conducted using keywords such as "microgrids" and "new technologies." The gathered information was processed using Bibliometrix software to cluster the data. This analysis identified five distinct research lines related to microgrids and energy management. Results and Discussion: The analysis revealed five distinct research lines: (1) microgrids related to energy generation and storage, (2) electric power system control, (3) electric power transmission networks, (4) optimization, and (5) power markets. The paper develops and explains these research lines comprehensively, detailing technology trends and prospects for efficient energy management. Additionally, a combined analysis of relevance and development classifies the research lines as either emerging or declining and determines whether they represent basic or motor themes. Research Implications: The findings provide insights into current and future trends in microgrid technology, offering valuable information for researchers, practitioners, and policymakers. Understanding these trends can help guide future research, development, and implementation strategies for efficient energy management in microgrids. Originality/Value: This paper offers a comprehensive analysis of technology trends and prospects in microgrids, utilizing advanced bibliometric tools to identify and classify research lines. The study provides a unique perspective on the development and relevance of different aspects of microgrid technology, contributing valuable insights to the field.

Model predictive control (MPC) is widely used in resource optimization problems because it naturally deals with bounded controls and states and allows predictive information to be included. However, at each sampling instant, an optimization problem must be solved. Resource optimization problems with switching control actions naturally lead to optimization problems with integer decision variables, which are computationally costly, particularly when the number of variables is large. As a result, the approach of directly discretizing (DD) the problem to derive a mixed-integer linear program (MILP) sets fundamental limitations on the MPC sampling rate owing to the computational time required to solve the optimization problem. In this paper, we propose a two-scale optimization algorithm (TSOA) for MPC. On the first-scale, the entire prediction horizon is considered and the algorithm provides the optimal resources to be used at each interval with a constant weighting cost. This optimization problem may be cast as a linear program (LP); thus, it is computationally tractable even for a large number of variables and constraints. In the second-scale, the switching nature of the decision variable is recovered by posing an MILP to deploy the optimal resources computed in the previous scale. In this manner, the MILP is solved for a shorter time interval than the entire prediction horizon, thus reducing the number of variables in the optimization problem. The simulation results demonstrate the computational advantages of the proposed algorithm compared to direct problem discretization and optimization.

This article deals with the analysis of energy efficiency optimization in battery-based photovoltaic pumping schemes. The study builds on previous findings derived from the comparison between a direct photovoltaic water pumping system (DPVWPS) and the equivalent system including a lithium-ion battery (LIB). The initial experimental results of the battery-based photovoltaic water pumping system (PVWPS+LIB) were obtained with the motor-pump group operating at its rated condition of 50 Hz. In the present work, an analysis of the efficiency and the performance ratio of the variable speed drive (VSD) and the motor-pump group, showed that both parameters improve when operating in the low frequency range of the VSD and far from the rated frequency where the flow rate is maximized. Several fitting models were performed with the data obtained with the monitoring system and it was concluded that an overall energy efficiency optimization can be achieved with a VSD frequency equal to 37 Hz. A comparison of the experimental results obtained with the VSD working in the direct mode and with the battery-based solution (setting different VSD frequencies – 50 Hz, 37 Hz, and a combination of the two frequencies designed as 37/50/37 Hz) was made to determine the efficiency and performance ratios in each case. The results presented in this study also establish criteria for improving efficiencies in the LIB charging and discharging processes.

The one-cycle current control is a non-linear technique based on the cycle-by-cycle calculation of the ON time of the power converter switches. Its application is not common in tracking fast-changing reference currents, due to the necessity of fast and accurate measurements, and high-speed computing. In a previous study, a one-cycle digital current controller based on the minimization of the integral error of the current was developed and applied to the control of a three-phase shunt active power filter. In the present work, the one-cycle controller has been improved by proposing a new switching pattern. It allows an easy implementation that reduces the critical computational cost and avoids the main drawbacks of the previous implementation. The controller has been applied in a three-leg four-wire shunt active power filter, including a stability analysis considering the proposed switching pattern. Simulated and experimental results are presented to validate the proposed controller.

This work presents the conversion of a photovoltaic water pumping system (PVWPS) to its corresponding battery-based solution, while maintaining the components of the PVWPS facility and adding the power converter needed to manage the operation of a lithium-ion battery. A complete analysis of the direct PVWPS is performed based on the values obtained by the monitoring system developed for the installation. The efficiencies and performance ratios of the various elements of the facility are calculated, as well as other relevant factors (such as irradiance thresholds). The dependence of some variables on the solar resource is analyzed to model the system. A similar study is carried out in the battery-based solution and a comparative analysis of the two modes of operation is then performed to find which aspects could be improved in the battery-based solution to increase the pumping time and total daily pumped volume. The results presented demonstrate the benefits of including a battery (reduction in start/stop cycles and improved performance on cloudy days). Aspects that can be improved to make the battery-based solution more efficient and achieve better results are suggested.

The development of photovoltaic (PV) technology is now a reality. The inclusion of lithium-ion batteries in grid-connected PV systems is growing, and the sharp drop in prices for these batteries will enable their use in applications such as PV water pumping schemes (PVWPS). A technical solution for the monitoring and tracking of PV systems is shown in this work, and a novel quasi-real-time monitoring system for a PVWPS with a Li-ion battery is proposed in which open-source Internet of Things (IoT) tools are used. The purpose of the monitoring system is to provide a useful tool for the operation, management, and development of these facilities. The experimental facility used to test the monitoring system includes a 2.4 kW_pk photovoltaic field, a 3.6 kVA hybrid inverter, a 3.3 kWh/3 kW lithium-ion battery, a 2.2 kVA variable speed driver, and a 1.5 kW submersible pump. To address this study, data acquisition is performed using commercial hardware solutions that communicate using a Modbus-RTU protocol over an RS485 bus and open software. A Raspberry Pi is used in the data gateway stage, including a PM2 free open-source process manager to increase the robustness and reliability of the monitoring system. Data storage is performed in a server using InfluxDB for open-source database storage and Grafana as open-source data visualization software. Data processing is complemented with a configurable data exporter program that enables users to select and copy the data stored in InfluxDB. Excel or .csv files can be created that include the desired variables with a defined time interval and with the desired data granularity. Finally, the initial results of the monitoring system are presented, and the possible uses of the acquired data and potential users of the system are identified and described.

Current control has, for decades, been one of the more challenging research fields in the development of power converters. Simple and robust nonlinear methods like hysteresis or sigma-delta controllers have been commonly used, while sophisticated linear controllers based on classical control theory have been developed for PWM-based converters. The one-cycle current control technique is a nonlinear technique based on cycle-by-cycle calculation of the ON time of the converter switches for the next switching period. This kind of controller requires accurate measurement of voltages and currents in order achieve a precise current tracking. These techniques have been frequently used in the control of power converters generating low-frequency currents, where the reference varies slowly compared with the switching frequency. Its application is not so common in active power filter current controllers due to the fast variation of the references that demands not only accurate measurements but also high-speed computing. This paper proposes a novel one-cycle digital current controller based on the minimization of the integral error of the current. Its application in a three-leg four-wire shunt active power filter is presented, including a stability analysis considering the switching pattern selection. Furthermore, simulated and experimental results are presented to validate the proposed controller.

Means and modes of transport in urban environments are changing. The emergence of new means of personal transport, such as e-scooters or e-bikes, combined with new concepts such as ‘vehicle sharing’ are changing urban transport. A greater social awareness of the harmful effects of polluting gases is leading to the adoption of new e-mobility solutions. A sustainable e-scooter recharging dock has been designed, built, and put into operation in a small town north of the city of Valencia (Spain). In the proposed novel solution, a stand-alone PV system is built for the free recharge of e-scooters using an original system that supports new sustainable means of transport. The design of the PV system considers the size limitations of the equipment, where a single PV module must generate the energy needed to recharge the e-scooters. A battery is used to store the energy and adjust power generation and consumption profiles. A commercial electronic converter adjusts the various electrical characteristics of generation, storage, and consumption. As a result of the system analysis, the surplus autonomy provided for the e-scooter recharging dock is calculated. Potential stakeholders in the use of the proposed system and their reasons for adopting this sustainable solution are identified. Experimental results of the first months of operation are included and these demonstrate the correct operation of the proposed system.