基于多重灵敏度的有源配电网有功无功联合优化方法

Active and reactive joint optimization method of active distribution network based on multiple sensitivities

针对分布式电源接入后配电网实时优化维度高、复杂性增强以及部分量测缺失导致传统潮流计算无法进行等问题,提出一种基于多重灵敏度的主动配电网有功无功联合优化方法。针对配电网实时优化模型复杂度高的问题,推导一种多重灵敏度系数矩阵,简化传统潮流模型;针对因配电网部分量测缺失而导致多重灵敏度难以通过潮流物理模型实时获取的问题,建立基于社交网络搜索算法与径向基神经网络的多重灵敏度实时感知模型;结合模型预测控制理论,设计以可实时量测线路线损最小以及可调节设备调节成本最低为目标的配电网实时有功无功联合优化调控策略,并基于多重灵敏度感知模型实现灵敏度实时校正,提高配电网控制精度。通过IEEE 33节点系统验证了所提方法的有效性。

The real-time optimization of distribution network is highly dimensional and complex after the access of distributed power supply,and the traditional power flow calculation cannot be carried out due to the missing of partial measurements.To solve these problems,an active and reactive power joint optimization method of active distribution network based on multiple sensitivities is proposed.Aiming at the problem of high complexity of real time optimization model for distribution network,a multiple sensitivity coefficient matrix is derived to simplify the traditional power flow model.Aiming at the problem that the multiple sensitivities are difficult to obtain in real time through the power flow physical model caused by partial measurements missing of distribution network,a real-time sensing model of multiple sensitivities based on social network search and radial basis function neural network is established.Combining with the model predictive control theory,a real-time active and reactive power joint optimization control strategy of distribution network is designed with the minimum real-time measurement line loss and the minimum adjustment costs of adjustable equipment as the objects.The sensitivity real time correction is realized based on the multiple sensitivity sensing model to improve the control accuracy of distribution network.The effectiveness of the proposed method is verified by IEEE 33-bus system.