基于模糊云理论模型的智能配电云网络化控制识别方法

由于基于传统的不确定时滞鲁棒控制系统不能满足新型电力云网络化控制用户的需求,提出了一种基于模糊云理论系统模型的感知智能配电云网络化控制识别方法,该方法采用优化传统数据值和电力云网络化控制数据的一种云理论系统模型,并用云理论结果代替被控节点预测值,攻破了不确定滞鲁棒控制系统控制效果不能及时反馈的问题,同时将供电系统性能指标引入到电力云网络化控制计算器中,运用性能指标的云模型中正向运算法修正加权系数,实现了感知智能配电云网络化的最优控制。基于实验仿真证明,该识别方法可以优化传统的不确定滞鲁棒控制系统,并具有良好的适应性、鲁棒性、控制性,同时可以进一步改善智能配电云网络化控制的各种性能指标。

Network control recognition of intelligent power distribution cloud based on fuzzy cloud theory model

For traditional uncertain time delay robust control system can not meet the demand of users of new power cloud networked control, a kind of network control recognition of intelligent power distribution cloud is proposed, which is based on fuzzy cloud theory model. A cloud theory system model is adopted, which is based on the optimization of the traditional data values and power cloud networked control data, and the problem of untimely control effect feedback of the uncertain and robust control system is solved with the cloud theoretical result instead of predictive value of controlled node. Meanwhile, the power supply system performance index is introduced into the power cloud networked control calculator to modify the weighting coefifcient through positive operation method, and realized the optimal control of smart distribution cloud networked control. Simulation results show that the recognition method can optimize traditional uncertain delay robust control system, and has good adaptability, robustness, and controllability. Meanwhile, it can further improve the control performance of smart distribution cloud networked control.