This article proposes a novel design methodology for hybrid isolated microgrids, integrating electric vehicles (EV) as additional loads and also as additional storage systems in the microgrid design stage. The proposed method highlights the application of electric vehicles in rural environments. Two types of electric vehicles were considered: (1) EV that only operate in charging mode; and (2) EV that can interchange power with the microgrid (V2G). For both EV types, a dispatch strategy was developed to optimize the use of the system resources during the charging process. As an application example of the proposed design methodology, a hybrid microgrid was designed for the rural Colombian village of Unguía. The results show the advantages of the inclusion of EV as ancillary services providers for the system and also as public transportation agents.

The increasing use of renewable technologies such as wind turbines in power systems may require the contribution of these new sources into grid ancillary services, such as Load Frequency Control. Hence, this work dealt with the performance comparison of two traditional control structures, PI and LQR, for secondary regulation of Load Frequency Control with the participation of variable-speed wind turbines. For this purpose, the doubly-fed induction generator wind turbine was modeled with additional control loops for emulation of the inertial response of conventional machines for frequency regulation tasks. Performance of proposed strategies was verified through simulation in a benchmark adapted from the WSCC 3 machines 9-bus test system. Results showed overall superior performance for LQR controller, although requiring more strenuous control effort from conventional units than PI control.

This article presents a novel scheduling strategy for charging and dispatching electric heterogeneous Bus Rapid Transit (BRT) fleets equipped with batteries. A key feature of this strategy is that it is formulated as a model-based convex optimization problem, which takes into account a horizon corresponding to an entire day and incorporates proper selection matrices for restricting the operation and charging status of each BRT. The approach is economic, since it considers the energy price variation during the day. The scheduling strategy is tested with a fleet of BRTs, considering two vehicle classes which differ mainly in their dimensions and capacities. Using the Simulation of Urban MObility (SUMO) package, a simplified rule-based algorithm gives which type of BRT is needed in order to satisfy a given demand of passengers. This information is sent to the optimization which is solved in Matlab®. Simulation results show the effectiveness of the scheduling method and its capacity to compute an economic optimal solution.

An analysis of the harmonic pollution produced by different load scenarios in an office is presented in this paper. An experiment was carried out, in which typical load scenarios in office environments were reproduced. The devices used in the experiment were selected based on the characterization of the consumption groups in office environments in several countries. The analysis shows that THDi and TDD were different for each load scenarios, so the scenario of highest consumption was not the most polluted. Moreover, it was concluded that scenarios, which include plug-load devices, has the highest harmonic pollution.

La estabilidad de los sistemas de potencia, en los cuales se implementan fuentes renovables como la eólica, es un área de gran atención en la actualidad ya que se requiere cumplir con una calidad en el servicio energético suministrado, y las fuentes renovables, ante su variabilidad en la potencia generada por la dependencia de las condiciones climáticas, pueden afectar dicha calidad. Por esta razón, es necesario aplicar estrategias de control que permitan realizar una integración de las fuentes renovables para tratar de minimizar los efectos adversos de estas sobre la red y que además admitan incluir los límites operativos de estas fuentes para evitar daños en ellas. En este trabajo se plantean dos estrategias de control, LQPC y GPC, para controlar la velocidad angular y el torque de un aerogenerador con el objetivo de garantizar un determinado valor para la potencia de salida de este y evitar variaciones bruscas en la velocidad angular que puedan generar desgaste o estrés mecánico.