Abstract
As renewable energy resources such as wind and solar power are developing and the penetration of electric vehicles (EVs) is increasingly integrated into existing systems, uncertainty and variability in power systems have become important issues. The charging demands for EVs and wind power output are recognized as highly variable generation resources (VGRs) with uncertainty, which can cause unexpected disturbances such as short circuits. This can deteriorate the reliability of existing power systems. In response, research is required to identify the uncertainties presented by VGRs and is required to examine the ability of power system models to reflect those uncertainties. The deterministic method, which is the most basic method that is currently in use, does not reflect the uncertainty of system components. Therefore, this paper proposes a probabilistic method to assess the steady-state security of power systems, reflecting the uncertainty of VGRs using Monte Carlo simulation (MCS). In the proposed method, the empirical EVs charging demand and wind power output data are modeled as a probability distribution, and then MCS is performed, integrating the power system operation to represent the steady-state security as a probability index. To verify the method proposed in this paper, a security analysis was performed based on the systems in Jeju Island, South Korea, where the penetration of wind power and EVs is expanding rapidly.
Highlights
In an effort toward reducing greenhouse gas emissions, renewable energy resources, especially wind and solar power, are drawing significant attention worldwide
To achieve Korea’s energy policy goals, larger amounts of variable generation resources will be integrated into the power system, which may cause power system uncertainties in system operations and planning to increase, resulting in a reduction in the power system’s security
In response to the overall plan, it is essential to model the uncertainty of the variable generation resources such as the charging demand of electric vehicles (EVs) and wind power outputs based on the probabilistic method
Summary
Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis. Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul 03760, Korea.
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