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Several cities worldwide are focused to reduce the environmental degradation based on the deployment a nd integration of renewable energies and electric vehicles (EV) into the distribution network. The first one replaces el ectricity produced by fossil fuels with solar, wind or hydro power plants, whilst the second one i s a feasible alternative to substitute internal com bustion engine (ICE) vehicles with eco-friendly vehicles. Set in this context, this paper proposes an examination about the main effects in a georefer enced distribution system when non-linear loads are connected to the grid. The distribution network model contemplates georeferenced data from custome rs, where unbalanced currents due to the customer’s consumption in each distribution transfo rmer is evaluated using a variety of coefficient fo r c mmercial and residential load models. Voltage unbalance, harmonics and load flow analysis is performed in PowerFactory to determine the impa cts of EVs to the grid. Keywords– Harmonics analysis, unbalanced loads, non-linear lo ds, georeferenced distribution network, electric v ehicle. RESUMEN– En la actualidad la sociedad está enfocada en la mi tigación del daño ambiental basado en la integració n de energía renovable y vehículos eléctricos en las redes eléctricas. Energ ías limpias como energía solar y eólica en la gener ación de electricidad están destinadas a reemplazar los derivados de combustible fósil, mien tras que los vehículos eléctricos substituyen a los vehículos de combustión interna. En este contexto, el presente proyecto propone un análisis a una red eléctrica real georreferenciada considera n o los principales retos que involucran la conexión de cargas no lineales al sistema eléctrico . El modelo utiliza información georreferenciada de los usuarios y la red eléctrica existente, donde corrientes desbalanceadas consumidas por los usuari o son evaluadas basado en modelos de carga para cl ientes residenciales y comerciales. El impacto debido a la inclusión de vehículos eléctric os es desarrollado en el software PowerFactory mediante análisis de flujos de potenc ia, análisis de amónicos y desbalance de voltajes. Palabras clave– Análisis de armónicos, carga desbalanceada, carga n o lineal, red de distribución georreferenciada, veh ículos eléctricos. 1. Introducción Electric vehicles deployment into the power distribution network is by far the biggest challeng in electrical and transport engineering, because it no t o ly relates electrical facilities but also involves cus tomer behaviors, transport patterns, infrastructure, tech nology advances and environmental concerns. The last one h as become a paramount theme in the contemporary societ y, consequently some issues have been identified and possible solutions has been stated by academics [1] . Within this background, the environmental degradati on has been mainly produced by the extensive utilizati on of ICE on transport sector, which consume considerable quantities of fossil fuels. Novel and modern techno logies have been developed by transport industry, which is focused to deplete the consumption of petroleum derivatives and extend the deployment of EV worldwi de. Some countries have started to replace electrical v ehicles instead of conventional vehicles due to fossil fuel limitations, and the results have been positive [2] [3]. The international transport industry market is primarily dominated by ICE vehicles due to customer reliance in traditional vehicles. The customer’s co ncerns about the transition from conventional fuel vehicle s to eco-friendly vehicles are related with the insuffic ient battery capacity, the longer charging times, and la ck of charging infrastructure. Nevertheless, technologica l advances are being developed to promote the enlargement of EV fleets since new models present a n enhanced battery performance, increasing the energe tic autonomy and reducing the charging times. Consequently, rapid chargers could be located in zo nes with high urban density such as shopping centers, p arks and municipal parking lots [4]. With a raising environmental concerns and technological advances, the electric industry world wide has improved considerably in recent years. Generati on, transmission and distribution systems have been renewed, and thus, thermal power plants which consu me significant amounts of fossil fuels have been repla ced by renewable energy like solar, wind and hydropower generation. Transmission corridors have been enhanc ed with the inclusion of several transmission lines connecting power plants with load centers, improvin g the flexibility and operability of the system [5]. The last stage of the system has been upgraded since daily operati v works are achieved in distribution system to offer a better service to the customers. As consequence, medium an d low voltage networks are undergoing rapid changes, therefore identification of impacts of EV and distr ibuted generators have been carry out evaluating the balan ce between demand and supply and the potential violati on of statutory limits [6], real cases has been invest igated in [2], [7], where probabilistic approximations are ut ilized to determine impact on LV networks. The deployment of EV around world is constantly growing, then public policies has been declared, wh ich are focused with reduction of taxes for green vehic l s, investments in mobility programs, replacing the conventional cars in governmental institutions by vehicles with low emissions [8]. Additionally, tech nical and commercial approaches has been stated to develo p rapid charging infrastructure in parking zones and commercial areas with high traffic and population demand [9]. Consequently, not only a structural cha nge in transport sector is imminent due to the introduc tion of electrical vehicles in medium and long term, but al so distribution networks will face several effects and impacts in their assets, then planning, maintenance d operation policies should be evaluated [1], [7]. Several research has been conducted for planning in distribution networks considering georeferenced dat a, providing security and reliability at minimum cost with a coverage of 100% since it is mandatory to supply electricity to the totality of end customers [10], [11]. Georeferenced data can be obtained from OSM files, which contribute with information about location an d functionality of essential facilities and systems s erving a city. Electricity networks, roads, streets, reside ntial and commercial buildings are acquired from georeference d files. The aforementioned information is characteri zed in three forms nodes, ways and relations [12]. Nodes a r the virtual representation of specific points on the Ea rth’s surface, which are expressed in its geographical coordinates (latitude and longitude), whilst ways a re the computer-generated combination of nodes, which are well-arranged to form closed features such as build ings or non-closed features like a street section. Final ly, the gathered data, which relates information among diff erent objects is named relations [11], [13]. Set in this context, the present paper analyses the influence, impacts and assessment of proliferation of electrical vehicles into distribution networks. The main assets such as distribution transformers and cables are studied when unbalanced non-linear loads are connec ted to the distribution system. The rest of the present is structured as follows: Section II presents a descri ption of the study case considering the EV model when it is connected to residential and commercial end users b ased on georeferenced data. Section III presents simulat ions performed in DIgSILENT PowerFactory, and a comprehensive asset assessment on distribution netw ork is stated in Section IV followed by the conclusions drawn in Section V. 2. Case study and EV load model The present section focuses in a detailed model of the case study, where the network topology is based fro m georeferenced data. The loads data consider a perio d of time of 24 hours, then a peak and the lowest demand is analyzed. Additionally, EV and traditional loads ar e modelled considering unbalanced behaviors due to it s natural features in distribution networks, see figu re 1. 2.1 Case study based on OpenStreetMap (OSM) data The topology of the selected distribution network i s based on data from OSM files, where both closed and nonclosed features permit to reconstruct location o f buildings, streets and revision boxes. Buildings an d infrastructure represent to end customers, which ca n be divided in different categories or strata depending their electrical demand. The selected case study is compo sed by 368 closed features, which are represented as en d users (buildings), and 204 non-closed features whic h are related with roads, avenues and streets. Additional ly, recreational area is depicted where rapid charging stations and distributed generation will be modelle d to determine the effect of by bi-directional load flow s on their distribution transformers. Set in this contex t, the selected case study is located in one of the most p r fi able and commercial zones in Quito, the capital of Ecuad or. Not only the central business district, but also lu xury residential buildings, shopping centers and governm nt institutions are located in this area. Consequently , the zone presents a higher urban density than the surroundings districts in Quito. Currently, more th an one substation is needed to supply the enough electrici ty demand for the entire zone. Figure 1. Georeference distribution network. The chosen substation is connected to the sub transmission grid at a primary voltage level of 46 kV. It transfers down to the medium voltage level of 6.3 k V by two power transformers connected in parallel with a capacity of 15/20 MVA each. The substation is not o nly comprised by switching and protection systems, but also control and energy management system is available, where cont

Electrical assessment of georeferenced distribution network due to electric vehicles deployment