考虑源荷不确定性的电热系统联合调度

针对风电和电热负荷不确定的问题，提出计及源荷不确定性的旋转备用容量的优化方法，建立考虑电热备用耦合影响的调度模型。在日前阶段，以能源与负荷的预测量制定机组的出力方案，风电由于其预测精度较低，利用Beta概率密度函数来拟合风电出力，从而确定风电的不确定性带来的旋转备用容量，利用机会约束规划来处理不确定问题；负荷有较高的预测精度，但其波动性较强，使用概率场景生成和削减的方法制定不同场景下负荷备用需求的调整量，以日运行成本最低建立目标函数，运用改进的粒子群算法在IEEE30节点系统上验证了所提模型的经济性和鲁棒性。

Combined Dispatch of Electricity and Heat System Considering the Uncertainty of Source and Load

Aiming at the uncertainty of wind power electricity and heat coupling system， spinning reserve to deal with the uncertainty of source and load is proposed. The dispatch model is established considering the influence of electricity and heat standby coupling. In the day-ahead stage，based on the forecast of energy and load， the output plan of the unit is formulated. The forecasting accuracy of wind power is low， and the Beta probability density function is used to calculate wind power which is combined to determine its spinning reserve capacity demand to deal with the uncertainty of wind power. Opportunity constrained planning is used to deal with uncertain issues； load has higher prediction accuracy， but its volatility is strong， and it is generated and reduced using probability scenario method. The adjustment of reserve demands is formulated under different scenarios. The target function is established with the lowest daily operating cost， the improved particle swarm algorithm is used to verify the economics and robustness of the model on IEEE30 nodes system.