Combined Heat and Power Dispatch under Different Control Modes Based on Probabilistic Prediction of Wind Power

High proportion of new energy has become a remarkable feature of modern power system. The intermittency and volatility of new energy generation power bring significant uncertainty to the power system, which greatly increases the risk of the safety and stable operation of the power system. The multi-energy complementarity can efficiently promote the integration of renewable energy. This paper proposes a method of combined heat and power dispatch under different control modes of heat system based on probabilistic prediction of wind power. Firstly, an extreme learning machine method is used as probabilistic prediction model of wind power. The combined heat and power dispatch model is constructed then considering the different heat network control modes constraints. Finally, a case study is performed based on the test system of an integrated electric-thermal energy system and the results indicates the optimality of the control modes considering the uncertainty of wind power prediction.