Asignación de recursos para la recarga de vehículos eléctricos en estaciones de servicios basado en la respuesta a la demanda

Abstract

La Respuesta a la Demanda (DR), dirigida a la carga de la red eléctrica ocasionada al incorporar Vehículos Eléctricos (EVs), es considerada de gran importancia debido a un alto impacto que provocan dichos vehículos a los sistemas eléctricos. El presente trabajo tiene como finalidad desarrollar asignación de recursos energéticos para la recarga de EVs en estaciones de servicio y así atenuar el impacto que los mismos generan, además de los distintos tipos de carga ante la red eléctrica con varios escenarios. Se plantea un modelo heurístico que se basa en la respuesta a la demanda por medio del algoritmo Húngaro, es decir, se consiguió la adecuada asignación de recursos energéticos para la carga de EVs.

Estimated cost of electricity with time horizon for micro grids based on the policy response of demand for real price of energy

“…The management is based on the optimization which is a method consists of a single source of energy that is the distribution company therefore the energy that is reduced in peak hours of the demand is energy previously stored in hours of the night and at the level of the distribution company it does not have any surcharge (E. M. Meza Cartagena & García Torres, 2018). The objective function of the optimization is to reduce peak demand and maximize comfort by increasing the number of equipment connected and used.…”

“…For this purpose, an average power representing the energy consumption in one hour is determined. With the hourly historical data, at the time The customer's The average power factor is calculated by relating the average power and the maximum power (Caracterización de la Carga en Sistemas Eléctricos de Distribución, n.d.;Grainger & Stevenson, 1996; E. M. ; E. M. García Torres, Águila, Isaac, González, & López, 2016; E. M. ; E. M. García Torres & Isaac, 2017;Guerrón, García Torres, & Montero, 2014;Meza Cartagena & García Torres, 2018), as shown in equation 17. 17Where:…”

“…This demand is fed by a distributed generator, which supplies the demand in its entirety during the off-peak and half load hours, but the problem occurs during the peak load period, During this period, in order to avoid load disconnection (de-energizing certain users), it is necessary to connect to a system that provides energy to this sector, causing additional costs for the use of energy storage or for the use of energy from thermal power plants that use fossil fuels. García Torres & Isaac, 2018;Meza Cartagena & García Torres, 2018). In view of the problems described above, it is necessary to optimize demand without affecting the comfort of users, in addition to using an energy storage bank.…”

“…The distributed generators are shown in table 2. The first two generators are established as preferential dispatch type, with solar radiation and wind speed data analyzed in the city of Quito with latitude -0° 12' 29.55", longitude -78° 29' 16.55", as presented in Figure 2 (E. M. García Torres & Isaac, 2018;Meza Cartagena & García Torres, 2018). Additionally, three loads are connected to the microgrid of the Microgrid Case StudyDiagram, in Figure 1, 7 generators (GD) are connected, with the characteristics shown in the Table (2"CENACE," n.d.; Glover, 2012;Grainger & Stevenson, 1996).…”