Designing a Solar PV-Battery based on Electric Vehicle Charging Station

Year 2023, Volume: 5 Issue: 2, 123 - 136, 30.06.2023

Samatar Abdı Yonıs Ziyodulla Yusupov Muhammet Tahir Guneser

https://doi.org/10.47933/ijeir.1231500

Abstract

Increasing transport demand necessitates higher oil consumption, resulting in an increase in carbon dioxide (CO2) emissions, which is a major cause of air pollution. The use of electric vehicles (EVs) is becoming more common around the world. Recent advancements in lithium-ion battery technology have increased the improvement of EVs. In this work, a solar photovoltaic (PV) battery-based EV charging station is designed. Meanwhile, the overall system comprises a battery energy storage system (BESS), solar PV module, grid and EV charging station. Thus, the primary source for the charging station is the PV source but due to less power during the night, we included battery storage as a backup. Grid source is also recommendable for an uninterruptable power supply. An artificial neural network strategy is developed in MATLAB/Simulink for proper power management of the solar PV-battery based EV charging station connected to the AC grid. Moreover, by employing an adaptive neuro-fuzzy inference system (ANFIS) and PI controller-based MPPT, the grid voltage and current, real/reactive grid power and the maximum output power are obtained. The overall system is evaluated under different scenarios of irradiance level and temperature with a state of charge (SOC) greater than 10 % for simulation purposes. The result shows that during the night hour due to less power from the PV source, an artificial neural network begins to regulate the grid power so that it supplies power to the stationary storage and EV battery.

Keywords

Solar PV, Electric vehicle, Stationary storage, ANFIS MPPT, PI controller, Neural network.

Elektrikli Araç Şarj İstasyonuna Dayalı Bir Solar FV-Pil Tasarlamak

Abstract

Artan ulaşım talebi, daha fazla petrol tüketimini zorunlu kılarak, hava kirliliğinin önemli bir nedeni olan karbondioksit (CO2) emisyonlarında artışa neden olur. Elektrikli araçların (EA) kullanımı tüm dünyada giderek yaygınlaşıyor. Lityum-iyon pil teknolojisindeki son gelişmeler, EA'lerin gelişimini artırdı. Bu çalışmada, bir solar fotovoltaik (FV) pil tabanlı EA şarj istasyonu tasarlanmıştır. Bu arada, genel sistem bir pil enerji depolama sistemi (PEDS), güneş FV modülü, şebeke ve EA şarj istasyonundan oluşur. Bu nedenle, şarj istasyonu için birincil kaynak FV kaynağıdır, ancak gece boyunca daha az güç olması nedeniyle yedek olarak pil depolamayı dahil ettik. Kesintisiz bir güç kaynağı için şebeke kaynağı da tavsiye edilir. MATLAB/Simulink'te AC şebekesine bağlı solar FV-pil tabanlı EA şarj istasyonunun uygun güç yönetimi için bir yapay sinir ağı stratejisi geliştirilmiştir. Ayrıca, uyarlanabilir bir nöro-bulanık çıkarım sistemi (NBÇS) ve PI denetleyici tabanlı MPPT kullanılarak, şebeke gerilimi ve akımı, gerçek/reaktif şebeke gücü ve maksimum çıkış gücü elde edilir. Genel sistem, simülasyon amacıyla %10'dan daha yüksek bir şarj durumu (SOC) ile farklı ışınım seviyesi ve sıcaklık senaryoları altında değerlendirilir. Sonuç, gece saatlerinde FV kaynağından daha az güç gelmesi nedeniyle yapay bir sinir ağının şebeke gücünü düzenlemeye başladığını ve böylece sabit depolamaya ve EA piline güç sağladığını gösteriyor.

Keywords

Solar PV, Electric vehicle, Stationary storage, ANFIS MPPT, PI controller, Neural network.

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