Application Research of BP Neural Network Algorithm in Power Line Loss Calculation

In recent years, it is still a difficult problem to calculate the line loss of distribution system. The main reason is that China’s power system data is not perfect, the components are huge, the management function does not exist, the network structure is directly connected. Therefore, reducing the loss rate of power system has become an urgent problem for energy companies to solve. Developing effective methods for line loss reduction evidence and line loss assessment requires careful calculation and analysis of line loss, which ultimately contributes to and guides line loss management.

Cluster analysis of time series K-Means line loss based on DWT distance

This paper constructs an indicator system composed of inherent attributes and time characteristics of the line based on the line loss, and proposes a K-Means line loss cluster analysis model based on this indicator system. The line is classified according to the clustering results. The result is 314.51 on the CH index (Calinski Harabasz Index), 0.19 on the Silhouette Cofficient (Silhouette Cofficient), and a running time of 0.508s. Compared with the traditional algorithm, it is greatly improved. The field of line loss analysis has guiding significance.

Modified Analytical Approach for PV-DGs Integration into a Radial Distribution Network Considering Loss Sensitivity and Voltage Stability

Achieving the goals of distribution systems operation often involves taking vital decisions with adequate consideration for several but often contradictory technical and economic criteria. Hence, this paper presents a modified analytical approach for optimal location and sizing of solar PV-based DG units into radial distribution network (RDN) considering strategic combination of important power system planning criteria. The considered criteria are total planning cost, active power loss and voltage stability, under credible distribution network operation constraints. The optimal DG placement approach is derived from the modification of the analytical approach for DG placement using line-loss sensitivity factor and the multiobjective constriction factor-based particle swarm optimization is adopted for optimal sizing. The effectiveness of the proposed procedure is tested on the IEEE 33-bus system modeled using Matlab considering three scenarios. The results are compared with existing reports presented in the literature and the results obtained from the proposed approach shows credible improvement in the RDN steady-state operation performance for line-loss reduction, voltage profile improvement and voltage stability improvement.