A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis
- 주제(키워드) wind power output , electric vehicles charging demands , Monte-Carlo simulation , Gaussian mixture distribution , Weibull distribution , steady-states security analysis
- 주제(기타) Energy & Fuels
- 설명문(일반) [Kim, Sunoh] Sangmyung Univ, Dept Elect Engn, Seoul 03016, South Korea; [Hur, Jin] Ewha Womans Univ, Dept Climate & Energy Syst Engn, Seoul 03760, South Korea
- 관리정보기술 faculty
- 등재 SCIE, SCOPUS
- OA유형 gold, Green Published
- 발행기관 MDPI
- 발행년도 2020
- URI http://www.dcollection.net/handler/ewha/000000175105
- 본문언어 영어
- Published As http://dx.doi.org/10.3390/en13205260
초록/요약
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.
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