基于模型预测控制的多能源微网仿射优化调度

Affine optimal dispatch of multi-energy microgrid based on model predictive control

受源荷日前预测误差较大的影响,多能源微网存在优化调度方案变化范围较大,且难有足够的不确定性应对裕度的问题。为解决上述问题,提出一种基于模型预测控制的多能源微网仿射优化调度方法。首先,通过不断更新预测信息以保证源荷预测精度。在此基础上,采用仿射算法表征源荷预测的不确定性。然后,将仿射优化调度模型嵌入滚动优化中,并在每次滚动优化中求解仿射优化调度模型。最后,仿真结果验证了所提方法能够有效降低优化调度方案的保守性与提高不确定性应对能力。

Affected by the large error in the day-ahead prediction of source and load,the multi-energy microgrid has the problems that the change range of the optimal dispatching scheme is wide,and has no sufficient margin for uncertainty.To solve these problems,an affine optimal dispatching method of multi-energy microgrid based on model predictive control is proposed.Firstly,the prediction information is updated continuously to ensure the accuracy of the source and load prediction.On this basis,the affine arithmetic is used to characterize the uncertainty of source and load prediction.Secondly,an affine optimal dispatching model is embedded in the rolling optimization and the affine optimal dispatching model is solved in each rolling optimization.Finally,the simulative results verify that the proposed method can effectively reduce the conservativeness of the optimal dispatching scheme and improve the ability to deal with uncertainty.