面向低碳灵活运行的超临界机组模糊预测控制策略

Fuzzy Predictive Control Strategy for Low-carbon Flexible Operation of Supercritical Unit

为实现“碳达峰、碳中和”目标下超临界机组的低碳灵活运行,提出一种计及机组灵活性、经济性和环保性的模糊广义预测控制策略。基于超临界机组调峰需求下的预测模型,首先构建包含一般控制目标和节能减排需求的综合滚动优化目标。然后,利用模糊选择确定目标函数中各子目标的加权系数以消除参数不确定性的影响。其中,模糊选择过程中模糊规则的制定以跟踪误差和碳排放增量为输入,加权系数为输出。进而通过预测模型、反馈校正与所设计滚动优化的协调配合求取最优控制律。最后,立足于我国大连某电厂600MW超临界机组运行数据进行所提控制策略的有效性验证。该方法在机组快速负荷调控、抗扰动及节能减排等方面均具有显著优势。

In order to realize the low-carbon flexible operation of supercritical units under the goal of“peaking carbon dioxide emission and achieving carbon neutrality”,a fuzzy generalized predictive control strategy considering the flexibility,economy and environmental protection is proposed.Based on the prediction model of supercritical unit under peak shaving demand,a comprehensive rolling optimization objective including general control objectives and emission reduction requirements is constructed.Then,the fuzzy selection is used to determine the weighting coefficients of each sub-objective in the objective function to eliminate the influence of parameter uncertainty.In the fuzzy rules defined for coefficient selection,tracking error and carbon emission increment are taken as input variables while the weighting coefficients are deemed as output variables.Next,the optimal control law is obtained through coordination of the prediction model,feedback correction and the designed rolling optimization.Finally,the effectiveness of the proposed control strategy is verified using the on-site data of a 600MW supercritical unit in Dalian,China.The proposed method reveals its superiority in fast load regulation,disturbance rejection,energy conservation and emission reduction.