Abstract
After the integration of high-proportion renewable energy into the power system, the output volatility and load forecasting deviation significantly increase the uncertainty of system operation, posing new challenges to unit commitment. Demand Response (DR), as an important means to improve system flexibility, can guide users to adjust their electricity consumption behaviour when the power grid is in tight operation. Among various DR measures, Interruptible Load (IL) has been widely applied in the power market due to its fast and flexible response characteristics. This paper proposes a unit commitment model based on chance constraints, which comprehensively considers wind power output fluctuations, load forecasting errors, and IL response uncertainty. Multiple scenarios are generated through Monte Carlo simulation, and combined with mixed-integer linear programming for solving, to achieve the dual goals of minimizing system operation costs and maximizing renewable energy absorption capacity. Case study results on the modified New England-39 bus system show that the proposed method can effectively balance the system operation cost and IL compensation cost, reduce the volatility of unit output, and significantly improve the wind power absorption level. The results verify the effectiveness of the proposed method in enhancing system economy and flexibility.