Stochastic Unit Commitment with High-penetration Offshore Wind Power Generation in Typhoon Scenarios
Yanqi Liu, Dundun Liu, Hongcai Zhang
Abstract
To tackle the energy crisis and climate change, wind farms are being heavily invested in across the world. In China's coastal areas, there are abundant wind resources and numerous offshore wind farms are being constructed. The secure operation of these wind farms may suffer from typhoons, and researchers have studied power system operation and resilience enhancement in typhoon scenarios. However, the intricate movement of a typhoon makes it challenging to evaluate its spatial-temporal impacts. Most published papers only consider predefined typhoon trajectories neglecting uncertainties. To address this challenge, this study proposes a stochastic unit commitment model that incorporates high-penetration offshore wind power generation in typhoon scenarios. It adopts a data-driven method to describe the uncertainties of typhoon trajectories and considers the realistic anti-typhoon mode in offshore wind farms. A two-stage stochastic unit commitment model is designed to enhance power system resilience in typhoon scenarios. We formulate the model into a mixed-integer linear programming problem and then solve it based on the computationally-efficient progressive hedging algorithm (PHA). Finally, numerical experiments validate the effectiveness of the proposed method.