Earticle

초록

영어

The rapid of electric vehicles (EVs) is challenges and opportunities for energy grid management and infrastructure planning. This research is aims to fill the knowledge gap by employing advanced analytical methods on a 503-day time series dataset from Thailand's EV charging stations. The dataset includes information on date, station name, connector type, energy consumed in kWh, payment in Baht, vehicle brand and model, as well as customer ID. This study focuses on three main objectives: (1) Forecasting daily energy demand with a focus on the top 5 stations in terms of kWh consumption to identify seasonality and trends, (2) Predicting daily revenue based on energy consumption, and (3) Conducting a Geo-Spatial Analysis to recommend optimal locations for installing new EV charging stations. The insights derived are expected to assist in efficient grid management, revenue planning, and strategic infrastructure deployment.

목차

Abstract
I. INTRODUCTION
II. RELATED WORKS
A. Demand prediction of electric Energy and revenue prediction for charging station
B. Location and geo-spatial of charging station
III. METHODLOGY
A. Data Source
B. Data Preparation
C. Well-Formed Format
D. Model Selection
E. Objective of Experiment
IV. EXPERIMENT AND REULT
A. Objective 1: Seasonality and Trends for Efficient Grid Management
B. Objective 2: Predict Daily Revenue (in Baht) Based on Energy Consumption between weekdays and weekends.
C. Objective 3: Geo-Spatial Analysis to Predict Optimal Locations for New Charging Stations Based on Demand.
V. CONCLUSION
REFERENCES

저자

• Kotchakan Fuangngam [ Collage of Information Technology and Digital Innovation King Mongkut's University of Technology North Bangkok,Thailand ]
• Supanan Tantayakul [ Collage of Information Technology and Digital Innovation King Mongkut's University of Technology North Bangkok,Thailand ]
• Arthittaya Narak [ Collage of Information Technology and Digital Innovation King Mongkut's University of Technology North Bangkok,Thailand ]
• Maleerat Maliyeam [ Lecture, Department of innovation technology. King Mongkut's University of Technology North Bangkok,Thailand ]

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