Abstract
As the importance of renewable generating resources has grown around the world, South Korea is also trying to expand the proportion of renewable generating resources in the power generation sector. Among the various renewable energy sources, wind generating resources are emerging as a key alternative to conventional power generations in the electricity sector in Korea accounted for 17.7 GW of total capacity by 2030. As wind generating resources are gradually replacing traditional generating resources, the system security and reliability are negatively affected because of the variability, due to intermittent outputs. Therefore, existing power grids will need to be correctly re-measured to cover the large scale of renewable energy, including wind generation. To expand the grid, we must understand the characteristics of renewable energy and the impact of its adoption in the grid. In this paper, we analyze various characteristics of wind power generation, and then we propose a probabilistic power output modeling method to consider the uncertainty of wind power generation. For the probabilistic approach, Monte-Carlo simulation is used in the modeling method. The modeled wind power outputs can help planning for the reinforcement and expansion of power systems to expand the capacity for large-scale renewable energy in the future. To verify the proposed method, some case studies were performed using empirical data, and probabilistic power flow calculation was performed by integrating large-scale wind power generation to the Jeju Island power system. The probabilistic method proposed in this paper can efficiently plan power system expansion and play a key strategy of evaluating the security of the power system through the results of stochastic power flow calculation.
Highlights
As a solution to the exhaustion of fossil fuel energy, the importance of renewable energy has been recognized by the world; the introduction of renewable energy as a key industry in each country is becoming a significant issue
Wind generation resources (WGR) are highly variable power sources affected by meteorological factors, such as temperature, wind speed, and wind direction
If the large-scale wind power generation is integrated into the existing power grid, it can have a significant impact on the reliability of the power system
Summary
As a solution to the exhaustion of fossil fuel energy, the importance of renewable energy has been recognized by the world; the introduction of renewable energy as a key industry in each country is becoming a significant issue. In this paper, we propose a probabilistic method that can be the basic study for future expansion planning by modeling the actual power grid of Korea and conducting security assessments using historical data. The best method is to estimate the characteristics through in situ tests for several years Another way to employ the probabilistic approach is to use the probability density function with less time investment and data as this is useful and necessary [4]. A Weibull distribution function makes it possible to estimate the characteristics of wind power data. We propose various scenarios for case studies based on the wind power outputs modeled by the probabilistic method. The Monte-Carlo simulation was performed considering the correlation of the wind farms, and the seasonal scenarios were constructed based on the simulation results.
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