Economic Feasibility of Solar-Powered Electric Vehicle Charging Stations: A Case Study in Ngawi, Indonesia
Journal Title: Mechatronics and Intelligent Transportation Systems - Year 2023, Vol 2, Issue 4
Abstract
In the context of increasing electric vehicle (EV) prevalence, the integration of renewable energy sources, particularly solar energy, into EV charging infrastructure has gained significant attention. This study investigates the economic viability of grid-connected photovoltaic (PV) systems for EV charging stations in Ngawi City, Indonesia, selected due to its substantial solar energy potential and ongoing renewable energy initiatives. Key factors influencing the economic feasibility of these systems include load requirements, renewable energy potential, system capacity, levelized cost of electricity, payback period, net present cost (NPC), and cost of energy (COE). A comprehensive techno-economic assessment was conducted to estimate the capital recovery time, incorporating both utilization costs and payback periods. The analysis utilized the Hybrid Optimization Model for Electric Renewables (HOMER) software, focusing on the application of PV energy in EV charging stations within Ngawi Regency. Findings indicate that a PV system-based generation approach can adequately meet the power needs of EV charging stations. Notably, this system is capable of generating surplus energy, which presents an opportunity for additional revenue, thus enhancing its economic attractiveness. The analysis determined that to produce an annual output of 562,227 kWh, a total of 1245 PV modules, each with a 370-watt capacity, are necessary. This off-grid PLTS system, relying exclusively on PV modules for electrical energy generation, can sufficiently supply a daily load of 342.99 kWh for an EV charging station. The study underscores the potential of solar-powered EV charging stations in contributing to sustainable urban development, reinforcing the integration of renewable energy into urban infrastructure.
Authors and Affiliations
Singgih Dwi Prasetyo, Farrel Julio Regannanta, Mochamad Subchan Mauludin, Zainal Arifin
Regional Classification of Serbian Railway Transport System Through Efficient Synthetic Indicator
The railway transport system is one of the most important elements in the development of the economy and the social space of any area. The main objective of the study is to analyse the regional differentiation in railway...
DSTGN-ExpertNet: A Deep Spatio-Temporal Graph Neural Network for High-Precision Traffic Forecasting
Accurate traffic prediction is essential for optimizing urban mobility and mitigating congestion. Traditional deep learning models, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), str...
A Region-Based Fuzzy Logic Approach for Enhancing Road Image Visibility in Foggy Conditions
An innovative context-aware fuzzy logic transmission map adjustment method is proposed for road image defogging, aimed at improving visibility and clarity under varying fog conditions. Unlike conventional defogging techn...
China-Europe Container Multimodal Transport Path Selection Based on Multi-objective Optimization
With the advancement of the "Belt and Road" initiative, trade between China and Europe has been steadily growing, and China-Europe container transportation has received increasing attention. This study analyzes the influ...
Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm
This study aims to assess the safety level of the Automatic Dependent Surveillance-Broadcast (ADS-B) signal quality during airplane departures at Sultan Mahmud Badaruddin II Airport. The Aero-track application was utiliz...