A region-based method for high-risk wind power ramp events detection

Over the past decade, wind energy has become one of the most prevalent renewable resources. The installed wind capacity continues to increase and the penetration of wind power has reached a relatively high level in some area. In this context, extreme volatility of wind power, i.e., ramp event can bring serious challenges to maintaining balance between the generation and the demand. Most ramp forecasting methods use event detection models based on series analysis of wind power forecast data or regression models based on data mining of historical data. However, real-time risk assessment on power system during the ramp process is almost neglected in these methods, which means that the forecast results are incomplete and operators can´t get sufficient risk information of ramps. This paper proposes a region-based method for high-risk wind power ramp events detection. In this method, an algorithm is developed to find the border of secure region of wind power integrated to power system considering several security constraints, the result of which is then used for recognition of high-risk ramps during the forecast process. Case study shows the effectiveness and practical application value of this method.