一种基于模型预测控制的主动配电网实时优化调度方法

A Real-time Optimization Dispatching Method for Active Distribution Networks based on Model Predictive Control

针对新能源发电的不确定性,本文提出了一种基于模型预测控制的主动配电网实时优化调度方法,对可控负荷进行建模,建立以主动配电网有功调整量最小为目标的实时反馈校正模型,并通过二阶锥松弛将非凸非线性规划问题转化为二阶锥规划问题,保证有效求解,在改进的IEEE33节点系统中进行仿真分析,结果验证了所提方法的有效性和优越性,对提高新能源的消纳率和系统的经济性具有重要作用。

In response to the uncertainty of new energy power generation,a real-time optimization dispatching method is proposed for active distribution networks based on model predictive control.The controllable loads are modelled and a real-time feedback correction model is constructed with the minimum active power adjustment in the active distribution network as the objective.The second-order cone relaxation is adopted to transform the non-convex nonlinear programming problem into a second-order cone programming problem to ensure its effective solution.Simulation analysis is then carried out in an improved IEEE33 node system.The results verify the effectiveness and superiority of the proposed method,which can play an important role in improving the absorption rate of new energies and the economy of the system.