Visualization of time-sequential simulation for large power distribution systems

Many graphical alternatives are useful to demonstrate critical characteristics of distribution systems such as voltage regulation or power flow. The visualization of electrical variables can also be an effective approach to analyze, compare and evaluate large-scale systems. However, visual analysis of large power distribution systems is increasing in complexity for operational and research purposes. In this paper, we show a proposed approach to take advantage of the statistical inference to visualize complex behaviors in time-sequential simulations. This method provides a meaningful representation to millions of simulation results that can be used for analysis and validation of smart grid strategies and devices. The visual examples show a fast identification of electrical phenomena obtained from the OpenDSS simulation of the EPRI Ckt24 test circuit. This approach can be applied to the volt-var control, topological reconfiguration, distributed generation management, storage control, and operation assessment among others.

[1]  R. C. Dugan,et al.  Distribution System Analysis and the Future Smart Grid , 2011, IEEE Transactions on Industry Applications.

[2]  Dirk P. Kroese,et al.  Kernel density estimation via diffusion , 2010, 1011.2602.

[3]  Thomas J. Overbye,et al.  Visualizing the electric grid , 2001 .

[4]  Mingguo Hong An Approximate Method for Loss Sensitivity Calculation in Unbalanced Distribution Systems , 2014, IEEE Transactions on Power Systems.

[5]  Seddik Bacha,et al.  Multilevel A-Diakoptics for the Dynamic Power-Flow Simulation of Hybrid Power Distribution Systems , 2016, IEEE Transactions on Industrial Informatics.

[6]  Raja Ayyanar,et al.  Design and Strategy for the Deployment of Energy Storage Systems in a Distribution Feeder With Penetration of Renewable Resources , 2015, IEEE Transactions on Sustainable Energy.

[7]  Santiago Grijalva,et al.  Leveraging AMI Data for Distribution System Model Calibration and Situational Awareness , 2015, IEEE Transactions on Smart Grid.

[8]  Surya Santoso,et al.  Electric Vehicle Charging on Residential Distribution Systems: Impacts and Mitigations , 2015, IEEE Access.

[9]  Blake Lundstrom,et al.  A Power Hardware-in-the-Loop Platform With Remote Distribution Circuit Cosimulation , 2015, IEEE Transactions on Industrial Electronics.

[10]  Thomas J. Overbye,et al.  New methods for the visualization of electric power system information , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[11]  D. Czarkowski,et al.  Three–Phase Time–Domain Simulation of Very Large Distribution Networks , 2012, IEEE Transactions on Power Delivery.

[12]  Juan A. Martinez-Velasco,et al.  Parallel Monte Carlo approach for distribution reliability assessment , 2014 .