Economic model for an electric vehicle charging station with v ehicle‐to‐grid functionality

Abstract

Summary Energy consumption is increasing in parallel with the population and technological advancements. Albeit the energy efficiency efforts, industrial consumption, and transportation have quite important roles in this increase. The electric vehicles (EVs) are expected to constitute a positive solution to mitigate energy use in transportation. Increasing penetration of EVs into public transport provides new opportunities both for environmental sustainability and transportation infrastructure. To project the potential operator revenue, we set up a hybrid model (solar and storage), which optimizes scheduling for the EV charging unit and evaluates environmental and economic benefits. Different operational scenarios of PV‐assisted charging stations will be simulated and solved with Rule‐based decision making. Since regulations have an important role in building the optimization model, scenarios are created considering different European regulations. Uncertainties depending on the traffic jam (arrival‐departure times), technological differences of the charging stations are encountered in the model. The results are compared among three different scenarios. Net present value of the system changes for different scenarios and electricity sale price is one of the main factors. This value tends to increase after an annual electricity sale price increase rate of 11%. Novelty statement In this study, the effect of different economic parameters on an electric vehicle charging station were analyzed. A system with electric vehicles, solar panel support, and external battery was mathematically modeled and a case study was done.

An overview and performance evaluation of open charge point protocol from an electromobility concept perspective

“…The proposed Bayesian Network is an optimization model from the perspective of social, environmental, and economic criteria. 39 Reddy et al 40 analyze multiple elements connected with the CSs such as their power, uncertainty of electricity price, and load uncertainty. The proposed method uses an unbalanced radial distribution system (URDS) by using a particle swarm optimization (PSO) algorithm.…”

Solar Photovoltaic Power Forecasting

“…erefore, the IEEE 90-bus and IEEE 33-bus were used for testing the results which effectively improved the voltage deviations and optimized the charging/discharging rate of EVs. Other studies were found in the literature which carried out the EVs such as [114,115].…”

A centralized vehicle‐to‐grid scheme with distributed computing capacity engaging internet of smart charging points: Case study

“…24 From the technological perspective, the models with the target of minimizing load variance, [25][26][27] minimizing power loss, [28][29][30] and minimizing load peak 31,32 are presented to improve the power quality of the grid and satisfy the energy requirements of PEV users. From the economic perspective, either the total charging cost of PEV users [33][34][35] or the total operating profit of EC 36,37 is considered for improving the financial benefit of each stakeholder. From the environmental perspective, minimizing carbon emissions is investigated and optimized, in which emissions resulting from PEVs charging varying with time and region are taken into account.…”