Affiliation:
1. University of Rwanda (UR-CST), African Center for Excellence in Energy for Sustainable Development, Kigali, Rwanda
2. Imperial College London, Electrical and Electronic Department, London, United Kingdom
3. Departament d’Enginyeria Elèctrica, Universitat Politècnica de Catalunya, Spain
Abstract
Electric vehicles (EVs) are being introduced in Rwanda and becoming attractive for different reasons. For instance, these types of vehicles can help decrease air pollution and noise emissions. In addition, it presents an alternative to combustion engines, given the increased price of fuel resources in Rwanda and around the world. This paper presents a tool tailored to optimize the design of an electrical charging station serving small-sized electric vehicles, utilizing the algorithm to assist in sizing stand-alone mopped charging stations. The developed tool is based on the toolbox EventSim from MathWorks, which permits the combination of the simulation of discrete events (such as the arrival of customers at the station) with continuous states (such as the simulation of the charging process). The required PV power was estimated by utilizing solar resources, for the location, from renewables. Ninja. The number of customers arriving at the existing oil station is normalized to estimate the energy requirements of the mopped fleet. A Poisson distribution was proposed to model the battery discharge upon arrival, and different related parameters were evaluated through a sensitivity analysis to identify their effects on the performance of photovoltaic charging station. For the testing values, the station parameters were changed by ±25% to determine the impact of key design parameters on station performance, as well as other satisfaction measures such as average waiting time and average queue length. With a 25% increase in photovoltaic panels, the blackout period decreases by 2.12%, while a 25% decrease in photovoltaic panels causes an increase of 2.18% in the blackout period. Utilizing the energy management system (EMS), the waiting time was reduced by 8%.
Publisher
Center of Biomass and Renewable Energy Scientia Academy
Cited by
1 articles.
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